No. 102 On the Value of Individual Athletes in Team Sports Falk Scherzer July 2010 An analysis conducted by the Chair of Macroeconomics at HHL Leipzig Graduate School of Management
HHL-Arbeitspapier HHL Working Paper No. 102 On the Value of Individual Athletes in Team Sports Falk Scherzer ISSN 1864-4562 (Online version) HHL Leipzig Graduate School of Management
On the Value of Individual Athletes in Team Sports July 2010 Abstract This paper deals with the valuation of individuals in teams. Historical data for the National Basketball Association(NBA) was used to analyze the individual athletes contribution to team success. The analysis is conducted with data of all players who have played in the NBA since its foundation in 1946. A panel analysis is used to measure age effects. After adjusting the data for these effects, a multiple regression is applied to examine the players value assuming constant returns to added value. In a final step, the marginal returns to added value are examined and individual effective talent is calculated. Key words: production function, basketball, talent, team sports, evaluation 1 Introduction This papers deals with the valuation of individuals in teams. To examine this question, historical data for the North American National Basketball Association (NBA) was used to analyze the individual athletes contribution to team success. The discussion about players individual value was especially vital after the National Basketball Association (NBA) published a list of the 50 Greatest Players in NBA History at the 50th anniversary of the league in 1996. The players were chosen by a panel consisting of media, former players and coaches, current and former general managers and team executives 1. Panelists were asked for the 50 greatest players of all time without ranking them. However, it is difficult to define greatness and criteria obviously considered in the selection include standard basketball statistics like points scored, rebounds, assists, shots blocked and championships won. But since basketball is a team sport, even the 1 http://www.nba.com/ 1
statistics of great players will deteriorate when they team up with other great players and certain decisive contributions like defense, hustle or clutch plays do not show up in any statistic. Did the 1996-97 Chicago Bulls win a record of 72 of their 82 regular season games just because of Micheal Jordan scoring 30 points per game? How big was the impact of the newly acquired defensive specialist Dennis Rodman who scored a mediocre 5.5 points per game but grabbed a league high of 14.9 rebounds per game. One could argue about this endlessly...or make use of the fact that NBA players usually change teams several times in their career and simply run a multiple regression. The economic analysis of sports has become a vital field of research as documented by the growing number of journals specialized on this topic. Since basketball is a team game and the team constitution varies each season, the impact of single players can be calculated. A data set containing all 3478 players who have played at least one regular season game since the NBA was founded in 1946 until 2008 is used to calculate the individual value of each player and analyze the marginal effect of adding player value to a team. 2 Theoretical Foundation The evaluation of athletes in team sports and the analysis of a production function are an uncommon but interesting field of economic research. Stadelmann and Eichenberger [2008] evaluate the talent of Formula One drivers using a multiple regression. 2 One of the first authors to deal with the topic was Scully [1974] who estimated a production function for Major League Baseball (MLB). Scully uses team statistics as the slugging average and the average strikeout-to-walk ratio as well as overall team quality dummies as input and the winning percentage as output to estimate a linear production function. Other studies like Berri [1999] evaluate individual talent by estimating a team production function based on individual statistics. The contribution of each statistic to team success is estimated and the players value is calculated based on individual statistics. These studies are useful to measure individual contribution to team success but not to asses individual talent of team members. 3 Chatterjee et al. [1994] use team statistics instead of 2 Formula One races are not a typical team sport. The fact that there are always two drivers in one team who use the same material is used to compare teammates. 3 It can regularly be observed that individual player statistics change significantly after players move from a mediocre team to a top contender or vice versa. This should not be interpreted as a change in talent. Individual statistics depend on individual talent but also on the teammates talent, amongst other things. This method could also create a bias towards front court players due to unobserved defensive skills. Good defense causes the opponents shooting percentage to drop and will be measured as an increase in defensive rebounds - but not necessarily by the player who defended the shot but likely by the team s front court 2
individual statistics as input to estimate the winning percentage of NBA teams for 1991-92 and try to make mid-season predictions for the play-offs and the 1992-93 season based one these estimates. Gustafson et al. [1999] estimate a joint production function for MLB using individual statistics as inputs and victories as well as attendance as output. Kahane [2005] analyzes the efficiency in the National Hockey League (NHL). A production function which uses player ability as proxied by team payroll as input is estimated using a stochastic frontier analysis. In order to determine the effective talent of individual athletes, the effect of aging on performance has to be considered. In this paper, this will be done by an adjustment of the impact proxies (games played per season) based on an analysis of individual performance over time. This aspect has been studied by Sowell et al. [2005], among others. The authors perform a aging frontier analysis to asses the development of performance over time using data from the Iron Man Triathlon World Championship. Fair [1994] uses a similar technique to analyze the effect of aging using data of men s track and field competitions. As the wages of professional athletes in the major sports are enormous and continue to rise, the valuation of these athletes is of high economic interest. Players are often evaluated based on individual statistics. While most individual statistics certainly are good indicators of a player s value, they leave much room for interpretation in team sports. Individual statistics will depend on a player s position, his team mates abilities, and the team s tactic, for example. The evaluation of individual players value is based on the following function of performance: P = F(talent,effort,training,age) (1) Performance (P) is a function of inherent talent, effort, training and age, where talent, effort, and training are assumed to be constant over time for each individual. It is further assumed that training is equally well for all professional basketball players. The effect of age here contains not only the pure effect of aging but also the gain of experience. This combined effect will be calculated and controlled for. What is left is talent and effort. Since it cannot be assumed that effort is identical for all athletes, the analysis will yield estimators of a combination talent and effort. This combination can be called the effective talent of an players. 3
individual athlete. Initially, it is assumed that the strength of a team is a linear function of the values of the team s individual players and that team strength translates into victories: n V ij = ( P kij GP kij ) α +ǫ ij. (2) k=1 Here, V ij is the percentage of regular season games won by team i in season j, P kij is the value of the n players who are on team i in season j, GP kij is the number of games played by player k and α is the elasticity of team success with regard to the combined player value. After initially assuming α to be equal to 1, the value which optimizes the fit of the regression will be determined. This function recognizes the fact that players miss games due to injuries or suspensions and that, unlike other team sports, in basketball, players on every position have equal influence on the game s outcome. The assumption of a linear strength function is a simplification but seems to be appropriate for the case of NBA basketball. Of course, if a team hoarded star players and barely used them, the marginal effect of adding a strong player would be decreasing. This possibility is however dampened by the restrictions for the roster size and the NBA salary cap rules which severely punish teams that spend more than a certain amount of money on salaries. The result is a fairly balanced league. Different assumptions regarding the marginal returns to adding player value to a team are analyzed in Section 7. The number of regular season victories is chosen as the measure of success. This could create a possible bias since not every NBA team plays the same number of games against all opponent teams. Currently, the league is divided into the Eastern and the Western Conference. During the regular season, each team plays four games against each team from its respective conference and two games against each team from the other conference. A bias could stem from possible imbalances between the two conferences. However, even if such imbalances should temporarily exist, they can expected to be considerably small. The inclusion of play-off games as in Berri [1999], would create a bias against players in strong teams who reach the play-offs, since these teams face only opponents with above average strength in the post season. 4 A point which is of more importance in certain sports than in others is average playing time. In a basketball game, players are substituted several times each game and playing time varies. This aspect will 4 The eight teams with the best regular season record in each of the two conferences reach the play-offs. Since the 2002-2003 season, the team that prevails in a best-of-seven series advances to the next round. Before 2003, there have been several changes in the number of required victories in the different play-off rounds. Today, a team could play up to 28 additional games in the play-offs. 4
remain disregarded in this analysis. The differences in playing time among players of a certain status are fairly small, however. The analysis also implicitly assumes that the average strength of opponent teams is constant over time. Should this assumption not hold true, only a comparison of players that played at about the same time would be possible and the estimates would be the athletes effective talent relative to players of a similar time period. An increase in average team strength could be attributed mainly to improvements in training, however. Assuming this factor to be constant over time also allows us to assume the average team strength to be fairly constant over time without creating a bias in measurement of effective talent. The result will be an estimation of the constant effective talent of individual athletes. Applying the estimated age function to these estimates results in individual values which are not constant over time. 3 Data The data set includes accurate data for all 3800 players who have played at least one minute in the NBA or the American Basketball Association (ABA) - a rival league that existed from 1967 until it merged with NBA in 1976 - between 1946 and 2008. 5 Between 1967 and 1976, several players switched between the two competing leagues. After the merger in 1976, the Denver Nuggets, Indiana Pacers, San Antonio Spurs and New York Nets were integrated into the NBA. Because of differences in the rules 6 in these two leagues, statistics of ABA seasons are not included in the analysis. Of the 3800 players, 322 players have not played in the NBA. The player statistics used are the player s age, the number of games played for a certain team in a certain season and the average points scored with that team. For players who were traded to another team during the regular season, the games for the respective teams are considered. With the data available it is impossible however, to determine the exact date of player trades. The measure of team performance used is the total number of regular season wins. The number of teams in the NBA has continuously increased from eleven in 1946 to 30 in 2004. The total number of seasons played by all teams was 1141 in 2008. 5 All data was gathered from http://www.basketballreference.com/. 6 One of the most important differences was the new three point line. 5
4 Age Adjustment Since the aim of this paper is to shed light on the evaluation of individual athletes contribution in team sports, the final multiple regression should yield a time constant effective talent factor for each individual player. The number of games played in a particular season for a particular team is used as a proxy for each player s influence on this teams total number of regular season victories. However, the impact of a player with a certain constant talent and effort will vary over time due to unobservable changes in physical condition and experience. Leaving these changes over time unaccounted for would result in a meaningless regression biased towards players who ended their career early or are still active (See Section 8 for results without age adjustment). It seems reasonable to expect the impact which a 35 year old Jason Kidd has on the number of regular season victories to be smaller than the impact of a 26 year old Jason Kidd, for example. Since this difference is not related to the time constant effective talent, it has to be controlled for in the final multiple regression. To control for the effects of physical deterioration and experience, the players impact factors (i.e. the number of games played in a particular season for a particular team) are weighted according to an estimated career performance function. To estimate this function, a panel regression with cross-section fixed effects is conducted. This career performance function expresses the average performance development of each player over his career, assuming cross-section fixed talent and effort for each player. Here, points per game are used as a proxy for individual performance. Of course, comparing different players only on the basis of this criterion would be misleading but accounting for cross-section fixed effects eliminates individual differences (which are of no interest here). For the career performance function, a polynomial function of the 3rd degree is estimated. In the panel analysis, only the 2514 cross-sections consisting of more than one season are considered. 7 The results are shown in table 1. The estimated polynomial of the 3rd degree has a local maximum at 25.54. The values for the variable AGE are the ages the individual players reach in the year a season started 8, so many players will be older than the value of AGE at the end of that particular season. This means according to the chosen specification, an average NBA player s prime age is about 26. From this point on, physical deterioration outweighs gains in experience. The 3rd degree polynomial has a value of 10.32 at the local maximum. This value is regarded as the prime performance value. The ratios of the performance values for the different ages relative to the 7 That means 964 of 3478 players got to play only one season. 8 The NBA season usually starts at the beginning of November and ends in the middle of April. 6
Table 1: Age Adjustment Variable Coefficient Std.Error t-statistic Prob. C 156.743068 6.897752 22.72379 0.0000 AGE 16.344105 0.734799 22.24296 0.0000 AGE 2 0.511547 0.025811 19.81929 0.0000 AGE 3 0.005001 0.000299 16.72694 0.0000 R 2 0.755857 Adjusted R 2 0.716945 Prob (F-statistic) 0.000000 Number of Cross-Sections: 2514 prime performance value are used as weights for the impact proxies (games per season). 9 5 Methodology Since a regression with 3478 explanatory and 1141 observations would be underidentified, not all players could be included. Of the 3478 players who have played at least one game in the NBA between 1946 and 2008, 964 have played only one season. It can be expected that the impact of those players on the total number of regular season victories is negligible. In order to decrease the number of explanatories further, only the 949 players who have played at least 400 regular season games in their career are included in the regression. The number of regular season games has increased over time with the number of teams. In 1946, the regular season included 62 games. The number dropped to 48 the next season but from then increased steadily to reach 80 in 1962 and now stands at 82 since 1968. To play 400 games, players had to be in the league for at least 4 seasons. This can be justified since the objective is to find the most valuable players and to determine their impact on team success. It can be expected that the most valuable players played long enough to fulfill this criterion. Problematic are the early years of the league because of the smaller number of regular season games and the time between 1967 and 1976 when several star players switch between the NBA and the ABA. This exclusion of players creates a further problem: Since many players who were active in the early years of the league, the ABA time, or have started their career after 2003 did not or not yet play 9 The weight for games played at the age of 26 is 0.997, 0.8715 for the age of 29, 0.6121 for the age of 32. 7
400 career games, there are team seasons with very few players who are actually included in the regression. 10 This problem renders these seasons useless as observations of the dependent variable since their inclusion would result in poor coefficient estimates. In order to receive meaningful results, those observations had to be excluded. In the preferred specification, the 58 team seasons were excluded in which on average less than 3.1 players included in the regression were used per game (cut), leaving us with 1083 observations and 949 independent variables plus a constant. A lower barrier would result in low t-values for the parameters and lower the overall fit. Increasing this barrier would further decrease the degrees of freedom and a lower overall fit. A higher barrier would also mean that more players who are included in the regression lose part of their seasons which decreases the significance of the estimated coefficient for those players. These difficulties also determined the choice of the minimum number of 400 career games. With a less restrictive mark, more players would be included in the regression but due to the very few degrees of freedom, only very few team seasons (i.e. observations) could have been excluded resulting in a meaningless regression. Alternative specifications are discussed in Section 8. The equation to be estimated is of the form y = X β +ǫ (3) where y is the vector of regular season victories for the different teams and years (for i team seasons). X is a i k matrix of the age adjusted numbers of games played by the k 1 players in the i team seasons and a constant. β is the vector of the estimated values of effective talent. The estimation equation takes the following form: 10 There are six team seasons in which no player was used who ever reached the 400 game mark and in 18 team seasons less than two included players were used on average per game. 8
ATL70 ATL71... ATL08 BOS47 BOS48... WAS08 = A.Jabbar ATL70 A.Rauf ATL70... Young ATL70 1 A.Jabbar ATL71 A.Rauf ATL71... Young ATL71 1............... A.Jabbar WAS07 A.Rauf WAS07... Young WAS07 1 A.Jabbar WAS08 A.Rauf WAS08... Young WAS08 1. β 1 β 2... β 949 C + ǫ 1 ǫ 2... ǫ 1083. 6 Results assuming Constant Marginal Returns The results of the preferred specification regarding the cut value are shown in table 2. In this regression, age adjustment is applied and only players with at least 400 NBA career games are included. Also, only team seasons, in which at least 3.1 players considered in the regression were used on average are included. In this specification, the overall fit is maximized. Of the 949 calculated parameters, 649 are significant at the 1 percent level, 70 are significant at the 5 percent level and 35 are significant at the 10 percent level. The lower significance of the 195 parameters stems from the necessity to exclude several team seasons. This results in a decrease of the number of games actually considered in the regression for some players with 400 and more career games and in a deterioration in the level of significance for those coefficients. The estimates represent the constant effective talent of the individual athletes. Applying the age adjustment function would yield individual values for certain seasons in the individuals careers. The average effective talent is 0.06. The individual values can be interpreted as individual values relative other players values. Players with estimated effective talent of more than 0.06 can be regarded as above average (relative to this group of 949 players). The null hypothesis of no heteroscedasticity can not be rejected with the Breusch-Pagan-Godfrey-Test. Of the 30 players with the highest estimated effective talent, twelve are already in the Basketball Hall of Fame 11 and twelve are still active. 12 11 Players can only be inaugurated into the Hall of Fame after their retirement. 12 Still active are Parker, Kirilenko, Marion, Prince, Nowitzki, Miles, Garnett, Haywood, Maggette, Ilgauskas, Iverson and 9
The high and insignificant coefficients for George Senesky and Bob Davies are the results of the necessary cutting off of several seasons. These two coefficients are, unlike the majority of coefficients, not robust to changes in the cut level. With a cut level of 3.0 instead of 3.1, none of the two players ranks among the top 30 (see table 8). George Senesky played eight seasons from 1946 until 1954, all with the Philadelphia Warriors. Five of these eight seasons are cut off in the preferred specification and only 180 of his 482 games are considered in the regression. One of the two seasons that are lost by the increase of the cut level from 3.0 to 3.1 is the 1950-51 season of the Philadelphia Warriors in which George Senesky played 69 games. This could be considered a small sample problem due to the required negligence of several seasons. The lack of robustness in the Bob Davies coefficient is caused by a high correlation with other coefficients. Davies played seven seasons of professional basketball (1948-55), all with the Rochester Royals. The 1948-49 season is the second season which is lost by increasing the cut level from 3.0 to 3.1. In all of the other seasons, Bob Davies played together with Arnie Risen, Bobby Wanzer and Jack Coleman. The only other players considered in the regression who played together with these four are Jack McMahon (1952-55) and Alex Hannum (1951-54). After the 1954-55 season, Davies, Risen and Coleman leave the Royals together. This unusual correlation leads to the insignificance of the estimated coefficient. Jack Coleman joined the team only after the cut off 1948-49 season. The inclusion of this season in the specification with the 3.0 cut level diminishes the very high correlation of these four variables. The estimated effective talent of Bob Davies in the 3.0 specification is 0.6234 as compared to 1.2210 in the preferred specification. The estimated effective talent of Jack Coleman increases to -0.0132 in the 3.0 specification as compared to -0.5151 in the preferred specification. These are unusually high changes representing the lack of robustness in these coefficients. As a result of this multiple regression analysis, Tony Parker seems to be the NBA player with the greatest effective talent in NBA history. The insignificant estimates for George Senesky and Bob Davies are results of the above mentioned data problems. Is this result plausible? Parker, a French, turned 27 in 2009. He entered the league in 2001 and spent all his first seven NBA seasons with the San Antonio Spurs. The Spurs have been one of the most successful teams in the NBA since 1989. In the 18 seasons from 1989-90 to 2007-08 they won at least 57 percent of their regular season games except for the dismal 1996-97 season. In the seven seasons with Parker on their roster they won at least 68 percent of their regular season games each season and three championships in 2003, 2005 and 2007. Turkoglu. 10
Table 2: Regression Results (400G; cut 3.1; α = 1) Rank Name β Standard Error 1 Senesky,George 6.5304 110.2833 2 Davies,Bob (HOF)1 1.2210 2.9845 3 Parker,Tony 1.1527 0.1013 4 Russell,Bill (HOF) 0.9742 0.7337 5 Olajuwon,Hakeem (HOF) 0.7709 0.0715 6 Kirilenko,Andrei 0.7651 0.0853 7 Schayes,Dolph (HOF) 0.7095 0.2567 8 Marion,Shawn 0.7085 0.0324 9 Abdul-Jabbar,Kareem (HOF) 0.6609 0.1207 10 Thomas,Isiah (HOF) 0.6487 0.0623 11 Bradley,Bill (HOF) 0.5958 0.1916 12 Prince,Tayshaun 0.5909 0.0465 13 Nowitzki,Dirk 0.5825 0.0501 14 Miles,Darius 0.5782 0.0697 15 Garnett,Kevin 0.5662 0.0291 16 Catchings,Harvey 0.5294 0.0950 17 Thompson,Lasalle 0.5279 0.0794 18 Macauley,Ed (HOF) 0.5275 0.1730 19 Barkley,Charles (HOF) 0.5213 0.0327 20 Haywood,Brendan 0.5195 0.0519 21 Maggette,Corey 0.5184 0.0237 22 Ilgauskas,Zydrunas 0.5164 0.0309 23 Mullin,Chris 0.5143 0.0498 24 Unseld,Wes (HOF) 0.5142 0.0355 25 Gale,Mike 0.5060 0.0482 26 Iverson,Allen 0.5013 0.0289 27 Pollard,Jim (HOF) 0.4957 0.0599 28 Turkoglu,Hidayet 0.4945 0.0136 29 Jones,Bobby 0.4923 0.0679 30 Sharman,Bill (HOF) 0.4881 0.1568 R 2 0.9734 Adjusted R 2 0.7833 *** : significant at 1 percent level (649 of 949) ** : significant at 5 percent level (70 of 949) * : significant at 10 percent level (35 of 949) 1 HOF indicates that the player is a member of the Basketball Hall of Fame 11
7 Analysis of non-constant Returns to Value The results in Section 6 assumed constant returns to value added to a team. In this section, different values for the elasticity of team success with regard to the combined player value (see equation 2 in Section 2) and the impact on the overall fit of the regression are examined. The elasticity that maximizes the overall fit for the preferred regression specification (cut level 3.1) is 0.75. 13 For values smaller or larger than 0.75, the overall fit is constantly decreasing. Furthermore, regarding only team seasons where at least 3.1 players considered in the regression where used (cut level 3.1) is also maximizing the overall fit when an elasticity of 0.75 is assumed. Table 3: Regression Characteristics with different Elasticities cut 3.1 cut 3.0 cut 3.3 α 0.71 0.75 0.79 1.0 0.75 0.75 R 2 0.974155 0.974178 0.974150 0.973365 0.973674 0.974143 adj.r 2 0.789745 0.789928 0.789793 0.783316 0.788610 0.788243 *** 645 650 648 649 645 643 ** 61 60 57 70 70 64 * 44 39 40 35 39 42 *** : coefficients significant at 1 percent level ** : coefficients significant at 5 percent level * : coefficients significant at 10 percent level The regression results for a cut level of 3.1 and an elasticity of team success with regard to the combined player value of 0.75 are reported in table 4. The value of adjusted R 2 increases by 0.006612. Even though this value seems to be small, it indicates that this specification describes the translation of combined player value into victories better than the model with constant returns to value. 13 The precision of examination is 0.01. 12
Table 4: Regression Results (400G; cut 3.1; α = 0.75) Rank Name β Standard Error 1 Senesky,George 6.069222 114.5482 2 Davies,Bob (HOF)1 1.604724 3.1000 3 Parker,Tony 1.171252 0.1053 4 Russell,Bill (HOF) 1.139786 0.7621 5 Olajuwon,Hakeem (HOF) 0.823782 0.0742 6 Schayes,Dolph (HOF) 0.792839 0.2666 7 Kirilenko,Andrei 0.788791 0.0886 8 Thomas,Isiah (HOF) 0.730043 0.0647 9 Marion,Shawn 0.654463 0.0336 10 Nowitzki,Dirk 0.641779 0.0521 11 Abdul-Jabbar,Kareem (HOF) 0.623396 0.1253 12 Prince,Tayshaun 0.620207 0.0483 13 Garnett,Kevin 0.604069 0.0303 14 Thompson,Lasalle 0.591433 0.0825 15 Mullin,Chris 0.582369 0.0517 16 Bradley,Bill (HOF) 0.575740 0.1990 17 Miles,Darius 0.571254 0.0724 18 Macauley,Ed (HOF) 0.560595 0.1796 19 Pollard,Jim (HOF) 0.552907 0.0622 20 Sharman,Bill (HOF) 0.537741 0.1629 21 Catchings,Harvey 0.535172 0.0987 22 Kersey,Jerome 0.525826 0.0625 23 Iverson,Allen 0.513277 0.0300 24 Unseld,Wes (HOF) 0.508085 0.0369 25 Gale,Mike 0.503575 0.0500 26 Barkley,Charles (HOF) 0.499925 0.0340 27 Dawkins,Darryl 0.493097 0.0469 28 Robertson,Oscar (HOF) 0.488487 0.0469 29 Smith,Phil 0.485816 0.0368 30 Jones,Bobby 0.484186 0.0705 R 2 0.9742 Adjusted R 2 0.7899 *** : significant at 1 percent level (650 of 949) ** : significant at 5 percent level (60 of 949) * : significant at 10 percent level (39 of 949) 1 HOF indicates that the player is a member of the Basketball Hall of Fame 13
8 Robustness The results of the multiple regression including only players who played at least 400 regular season games and excluding all team seasons in which less than 3.1 of these players have played per game on average (cut) is relatively robust to changes in the exact specification. The applied age adjustment increases the overall fit. As can be seen in table 5, the difference in the adjusted R 2 is 0.0358. In the panel regression which yielded the career performance function, only those players were considered who played at least two regular seasons in the NBA. Table 6 shows the estimation results when all players are included in the estimation. 14 The estimated function is much flatter, the overall fit is lower and the estimator for the intercept term is not significant at the 5 percent level. Table 7 shows the results for the estimation of the career performance function including only players who have played at least three seasons in the NBA. 15 The estimated function differs only slightly from the one estimated with the preferred specification (table 1) but the overall fit is slightly lower. Tables 8, 9 and 10 give an overview of the estimation results for different specifications concerning the cut level. Decreasing the cut value from 3.1 to 3.0 would increase the number of degrees of freedom from 133 to 135 but lower the adjusted R 2 by 0.0072. An increase of the cut value from 3.1 to 3.2 does not result in any changes. An increase to 3.3 would reduce the degrees of freedom from 133 to 132. In this specification, 649 (70, 35) of the 949 parameter estimates are significant at the 1 (5, 10) percent level as compared to 667 (61, 31) in the preferred specification which includes one more team season and adjusted R 2 decreases by 0.0017. A further increase of the cut level to 4 (which is equivalent to a decrease of the number of degrees of freedom to 98) leads to even less significant coefficient estimates and a lower overall fit (see table 10). The ranking varies since the differences between the estimated coefficients of players with similar effective talent are very small. The actual estimates do not vary much in the different cut-specifications. The high and insignificant coefficients for George Senesky and Bob Davies, who rank at the top two positions in the preferred specification are the results of the necessary cutting off of several seasons. These two coefficients are, unlike the majority of coefficients, not robust to changes in the cut level. With a cut level of 3.0 instead of 3.1, none of the two players ranks among the top 30 (see table 8. In the case of George Senesky, it is simply a short sample problem since changing the cut level from 3.0 to 3.1 decreases the number of Senesky s games considered in the regression from 249 to only 180. In the case of Bob Davies, the high, insignificant and non-robust coefficient results from an unusually high correlation between his career and 14 The number of cross-sections increases by 964; the number of players who left the league after one season. 15 The number of cross-sections decreases by 432 as compared to the preferred specification. 14
the careers of Arnie Risen, Bobby Wanzer and Jack Coleman. Increasing the cut level to 3.1 would add one season in which Davies has not played together with Coleman and therefore decease this correlation. Regardless of these obstacles, the cut level of 3.1 is the preferred specification since it yields the highest overall fit. 15
Table 5: Regression Results without Age Adjustment (400G; cut 3.1; α = 0.75) Rank Name β Standard Error 1 Wanzer,Bobby (HOF)1 1.9739 1.7299 2 Senesky,George 1.1786 5.9860 3 Marion,Shawn 0.7663 0.0499 4 Ilgauskas,Zydrunas 0.7403 0.0290 5 Prince,Tayshaun 0.7370 0.0878 6 Gasol,Pau 0.6501 0.0696 7 Thomas,Isiah (HOF) 0.6403 0.0401 8 Collins,Jason 0.6230 0.0544 9 Miles,Darius 0.6104 0.0436 10 Ellis,Joe 0.6014 0.1908 11 Peterson,Morris 0.6001 0.0230 12 Bradley,Bill (HOF) 0.5876 0.0963 13 Schayes,Dolph (HOF) 0.5583 0.0750 14 Jones,Bobby 0.5394 0.0380 15 Parker,Tony 0.5317 0.0881 16 Blount,Mark 0.5280 0.0360 17 West,Doug 0.5273 0.0520 18 McGrady,Tracy 0.4982 0.0325 19 Anderson,Derek 0.4968 0.0210 20 Nowitzki,Dirk 0.4939 0.0515 21 McMillan,Nate 0.4929 0.0340 22 Smith,Phil 0.4876 0.0216 23 Stockton,John 0.4813 0.0409 24 Catledge,Terry 0.4614 0.0239 25 Lewis,Rashard 0.4608 0.0320 26 Miller,Brad 0.4601 0.0275 27 Unseld,Wes (HOF) 0.4599 0.0216 28 Macauley,Ed (HOF) 0.4578 0.0310 29 Williams,Monty 0.4522 0.0548 30 Maggette,Corey 0.4518 0.0299 R 2 0.9694 Adjusted R 2 0.7541 *** : significant at 1 percent level (730 of 949) ** : significant at 5 percent level (37 of 949) * : significant at 10 percent level (29 of 949) 1 HOF indicates that the player is a member of the Basketball Hall of Fame 16
Table 6: Age Adjustment (Data from all Players) Variable Coefficient Std.Error t-statistic Prob. C 2.09495 1.21998 1.71720 0.0860 AGE 0.55630 0.13808 4.02868 0.0001 AGE 2 0.07739 0.00563 13.75519 0.0000 AGE 3 0.00174 0.00008 22.40331 0.0000 R 2 0.759607 Adjusted R 2 0.707364 Prob (F-statistic) 0.000000 Number of Cross-Sections: 3478 Table 7: Age Adjustment (Data from Players who playeda min. of 3 Seasons) Variable Coefficient Std.Error t-statistic Prob. C -160.78296 7.04867-22.81039 0.0000 AGE 16.77703 0.75024 22.36219 0.0000 AGE 2-0.52577 0.02633-19.96775 0.0000 AGE 3 0.00516 0.00031 16.91399 0.0000 R 2 0.747523 Adjusted R 2 0.713070 Prob (F-statistic) 0.000000 Number of Cross-Sections: 2082 17
Table 8: Regression Results (400G; cut 3.0; α = 0.75) Rank Name β Standard Error 1 Parker,Tony 1.174145 0.1061 2 Olajuwon,Hakeem (HOF) 1 0.840222 0.0748 3 Kirilenko,Andrei 0.788865 0.0893 4 Thomas,Isiah (HOF) 0.715460 0.0650 5 Schayes,Dolph (HOF) 0.679768 0.2639 6 Marion,Shawn 0.657190 0.0339 7 Abdul-Jabbar,Kareem (HOF) 0.650409 0.1262 8 Nowitzki,Dirk 0.644412 0.0525 9 Thompson,Lasalle 0.638763 0.0824 10 Prince,Tayshaun 0.628995 0.0487 11 Davies,Bob (HOF) 0.623297 2.7625 12 Hagan,Cliff (HOF) 0.611505 0.1403 13 Garnett,Kevin 0.599919 0.0305 14 Mullin,Chris 0.594626 0.0521 15 Miles,Darius 0.564872 0.0730 16 Russell,Bill (HOF) 0.560776 0.6616 17 Kersey,Jerome 0.544696 0.0628 18 Pollard,Jim (HOF) 0.542488 0.0616 19 Iverson,Allen 0.523742 0.0302 20 Dawkins,Darryl 0.523537 0.0468 21 Robertson,Oscar (HOF) 0.522566 0.0458 22 Gale,Mike 0.522313 0.0503 23 Catchings,Harvey 0.521079 0.0992 24 Unseld,Wes (HOF) 0.520992 0.0371 25 Barkley,Charles (HOF) 0.508831 0.0342 26 Dunn,T.r. 0.490538 0.0412 27 Issel,Dan (HOF) 0.490276 0.1286 28 Turkoglu,Hidayet 0.489453 0.0143 29 Smith,Phil 0.488432 0.0364 R 2 0.9729 Adjusted R 2 0.7827 *** : significant at 1 percent level (667 of 949) ** : significant at 5 percent level (61 of 949) * : significant at 10 percent level (31 of 949) 1 HOF indicates that the player is a member of the Basketball Hall of Fame 18
Table 9: Regression Results (400G; cut 3.3; α = 0.75) Rank Name β Standard Error 1 Senesky,George 6.158393 115.1403 2 Davies,Bob (HOF) 1 1.626560 3.1167 3 Parker,Tony 1.150434 0.1070 4 Russell,Bill (HOF) 1.135268 0.7659 5 Olajuwon,Hakeem (HOF) 0.838693 0.0752 6 Kirilenko,Andrei 0.790633 0.0890 7 Schayes,Dolph (HOF) 0.778523 0.2686 8 Thomas,Isiah (HOF) 0.732367 0.0650 9 Marion,Shawn 0.654509 0.0338 10 Abdul-jabbar,Kareem (HOF) 0.639485 0.1267 11 Nowitzki,Dirk 0.628137 0.0529 12 Prince,Tayshaun 0.612023 0.0488 13 Garnett,Kevin 0.596467 0.0306 14 Thompson,Lasalle 0.596396 0.0829 15 Bradley,Bill (HOF) 0.579517 0.2000 16 Mullin,Chris 0.570739 0.0523 17 Macauley,Ed (HOF) 0.559580 0.1805 18 Pollard,Jim (HOF) 0.553902 0.0625 19 Miles,Darius 0.533887 0.0768 20 Sharman,Bill (HOF) 0.532732 0.1638 21 Catchings,Harvey 0.522795 0.0996 22 Iverson,Allen 0.513598 0.0301 23 Kersey,Jerome 0.510182 0.0635 24 Unseld,Wes (HOF) 0.508970 0.0370 25 Barkley,Charles (HOF) 0.497935 0.0341 26 Gale,Mike 0.494841 0.0505 27 Dawkins,Darryl 0.494486 0.0472 28 Jones,Bobby 0.492615 0.0711 29 Smith,Phil 0.485849 0.0370 30 Robertson,Oscar (HOF) 0.484345 0.0472 R 2 0.9741 Adjusted R 2 0.7882 *** : significant at 1 percent level (643 of 949) ** : significant at 5 percent level (64 of 949) * : significant at 10 percent level (42 of 949) 1 HOF indicates that the player is a member of the Basketball Hall of Fame 19
Table 10: Regression Results (400G; cut 4; α = 0.75) Rank Name β StandardError 1 Wanzer,Bobby (HOF) 1 2.385169 41.3991 2 Russell,Bill (HOF) 1.786034 1.6458 3 Kirilenko,Andrei 1.337327 0.3416 4 Senesky,George 1.224706 821.3991 5 Parker,Tony 1.202966 0.1567 6 Greer,Hal (HOF) 1.160917 0.5874 7 Olajuwon,Hakeem (HOF) 1.019381 0.1020 8 Phillip,Andy (HOF) 1.017384 1.8497 9 Macauley,Ed (HOF) 0.921746 0.8243 10 Sharman,Bill (HOF) 0.916606 0.3811 11 Thomas,Isiah (HOF) 0.766716 0.0848 12 Thompson,Lasalle 0.721321 0.1297 13 Prince,Tayshaun 0.703031 0.0638 14 Jones,Bobby 0.685518 0.1042 15 Mullin,Chris 0.643933 0.0747 16 Pettit,Bob (HOF) 0.638497 0.4276 17 Garnett,Kevin 0.632584 0.0441 18 Yardley,George (HOF) 0.607463 0.0915 19 Marion,Shawn 0.605214 0.0430 20 Nowitzki,Dirk 0.587330 0.0729 21 Catchings,Harvey 0.585985 0.1485 22 Rollins,Tree 0.579635 0.0901 23 Kersey,Jerome 0.576088 0.0853 24 Pollard,Jim (HOF) 0.562129 0.0914 25 Bird,Larry (HOF) 0.560646 0.0525 26 Bridges,Bill 0.560328 0.0989 27 Unseld,Wes (HOF) 0.558477 0.0748 28 Iverson,Allen 0.549220 0.0446 29 Lanier,Bob (HOF) 0.547607 0.0926 30 Smith,Phil 0.542725 0.0552 R 2 0.9767 Adjusted R 2 0.7511 *** : significant at 1 percent level (516 of 949) ** : significant at 5 percent level (77 of 949) * : significant at 10 percent level (40 of 949) 1 HOF indicates that the player is a member of the Basketball Hall of Fame 20
9 Criticism Some problematic points have already been mentioned above. Since the number of players who have played at least one NBA game far exceeds the number of team seasons, it was necessary to exclude all players who have played less than 400 career games. Even though the impact on regular season victories of most of those players can be expected to be sufficiently small, problems arise with the early seasons, the ABA era and the seasons from 2004 on. In the early years, the number of regular season games was smaller and several star players simply did not reach the mark of 400 games because they were already relatively old when the league was founded. In the ABA era (1967-76), several very talented players spent significant parts of their careers in the ABA and therefore did not record 400 NBA games. Finally, none of the players who entered the league after the 2004 season is included in the analysis since in the four seasons from 2004 to 2008 only 328 games have been played per team. These exclusions made it necessary to skip 58 team seasons in the preferred specification because only a few number of players included in the regression where used by those teams. Another limitation is the complete negligence of coaches. A savvy head coach certainly has a significant impact on the number of regular season victories but the inclusion would have increased the number of dependent variables by several hundred and made a sensible regression impossible. The multiple regression takes into account that players sometimes change teams during a season. What it does not take into account, however, is the success of the player s old and new team before and after the trade. Trades during a season are common but their number is small relative to the total number of players. The assumption that individual values linearly add up to team strength is in this context not completely unrealistic but simplifying. Therefore, decreasing marginal returns to added player value are assumed in the preferred specification. Another possible shortcoming is the way the age adjustment is conducted. The method applied assumes that a player s performance is a function of his age (and talent, effort and training; see equation 1 in Section 2). The method, which yields quite reasonable results, could be improved by considering the age at which a player has entered the league. On the one hand, athletes who start their professional career at the age of 18 can be expected to be much more experienced at the age of 23 compared to others who played college basketball for several seasons. On the other hand, since the number of games per season on college is less than half the number of NBA regular season games, players who enter the league early might face physical problems earlier than those who enter at a higher age. The career performance could 21
be expressed using the two variables ( age, years as pro ). The effect of years as pro is expected to be strictly increasing. The effect of age on performance is expected to depend on years as pro since many players improve their physical condition in the first couple of years as professional athletes. From than on, their body deteriorates due to natural aging and the high physical loading. The career performance function estimated in Section 3, which estimates the combined effects of age and experience neglects the fact that not all players enter the professional league at the same age and therefore differ in their experience at a certain age. Other basketball specific shortcomings are the differences in playing time per game and play-off performance which are completely disregarded in this analysis. 10 Conclusion The focus of this work is on the value of individual athletes in a team sport. To analyze this value, the effects of aging and gathering experience where jointly estimated and applied to adjust data of 949 professional basketball players which was then used in a multiple regression to determine what could be called individual effective talent (which is constant over time). In this first step, constant marginal returns to adding player value to a team were assumed. The regression results improve when this function is altered in a way that recognizes the possibility, that the marginal value of a strong player is smaller in a strong team than in a weak one. This is done by simply weighting the values of the dependent variable accordingly. From the analysis in Section 7 it follows that the specification with a value of elasticity of success of 0.75 yields the highest overall fit for the multiple regression. The player with the highest effective talent in the history of NBA basketball (given the limitations regarding players included mentioned in Section 9) seems to be the French Tony Parker. A possible extension to this paper could be a panel analysis of the effect of team success on franchise revenue. Total franchise revenue can be expected to include a fixed component and variable components such as ticket and merchandise sales, TV earnings for nation wide televised games and revenues generated by playoff appearances. The revenue function will thus be a strictly increasing function of team success. Assuming that players are remunerated according to their performance (which is a function of effective talent, age and training), the team payroll is a convex and strictly increasing function of team success. 22
Depending on the characteristics of the revenue function, a situation with two equilibria is possible where certain franchises choose to form mediocre teams and others try to build teams as strong as possible. This phenomenon can be observed in the US professional leagues where franchises are not threatened by regulation. Of course, the techniques applied in this paper can not be used to assess the effective talent of young players who have played only a small number of games. For this purpose, the method used by Berri [1999] provides acceptable estimates of individual effective talent. Considering the age performance function calculated in section 4, these estimates can be used to determine the impact of a certain player on franchise revenue over the time of his contract. 23
References D.J. Berri. Who is most valuable? Measuring the player s production of wins in the National Basketball Association. Managerial and Decision Economics, pages 411 427, 1999. S. Chatterjee, M.R. Campbell, and F. Wiseman. Take that jam! An analysis of winning percentage for NBA teams. Managerial and Decision Economics, pages 521 535, 1994. R.C. Fair. How fast do old men slow down? The Review of Economics and Statistics, pages 103 118, 1994. E. Gustafson, L. Hadley, and J. Ruggiero. Alternative econometric models of production in major league baseball. Sports Economics: Current Research (Westport: CT, Praeger), 1999. http://www.basketballreference.com/. http://www.nba.com/. L.H. Kahane. Production efficiency and discriminatory hiring practices in the National Hockey League: A stochastic frontier approach. Review of Industrial Organization, 27(1):47 71, 2005. G.W. Scully. Pay and performance in major league baseball. The American Economic Review, pages 915 930, 1974. C.B. Sowell, W. Mounts, et al. Ability, Age, and Performance: Conclusions From the Ironman Triathlon World Championship. Journal of Sports Economics, 6(1):78, 2005. D. Stadelmann and R. Eichenberger. Wer ist der beste Formel 1 Fahrer? Eine okonometrische Talentbewertung. Perspektiven der Wirtschaftspolitik, 9(4):486 512, 2008. 24
Table 11: Results 25 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 11 Abdul-jabbar,Kareem (HOF) 0.6234 0.1253 0.6504 0.1262 0.6395 0.1267 129 Abdul-rauf,Mahmo 0.2796 0.0343 0.2788 0.0346 0.2707 0.0347 902 Abdur-rahim,Shareef 0.2607 0.0172 0.2635 0.0174 0.2470 0.0178 236 Adams,Alvan 0.1831 0.0917 0.1528 0.0916 0.1808 0.0921 511 Adams,Don 0.0218 0.0123 0.0152 0.0123 0.0232 0.0123 482 Adams,Michael 0.0417 0.0219 0.0285 0.0220 0.0372 0.0221 335 Aguirre,Mark 0.1214 0.0382 0.1353 0.0384 0.1094 0.0388 579 Ainge,Danny 0.0091 0.0126 0.0169 0.0127 0.0130 0.0127 361 Allen,Lucius 0.1063 0.0308 0.1074 0.0308 0.1060 0.0309 650 Allen,Ray 0.0497 0.0336 0.0475 0.0339 0.0400 0.0341 311 Alston,Rafer 0.1341 0.0126 0.1375 0.0127 0.1396 0.0128 777 Anderson,Cadillac 0.1342 0.0164 0.1328 0.0165 0.1308 0.0165 86 Anderson,Derek 0.3281 0.0167 0.3234 0.0168 0.3142 0.0173 399 Anderson,Kenny 0.0810 0.0222 0.0746 0.0223 0.0708 0.0226 936 Anderson,Nick 0.4537 0.0627 0.4460 0.0632 0.4916 0.0672 709 Anderson,Richard 0.0872 0.0144 0.0864 0.0145 0.0890 0.0144 595 Anderson,Ron 0.0198 0.0478 0.0161 0.0480 0.0111 0.0482 646 Anderson,Shandon 0.0490 0.0085 0.0493 0.0085 0.0506 0.0085 432 Anderson,Willie 0.0649 0.0695 0.0535 0.0699 0.0385 0.0718 600 Anthony,Greg 0.0220 0.0178 0.0231 0.0179 0.0340 0.0183 702 Archibald,Nate (HOF) 0.0835 0.0238 0.0738 0.0237 0.0833 0.0239 730 Arenas,Gilbert 0.0999 0.0180 0.0983 0.0181 0.0892 0.0184 190 Arizin,Paul (HOF) 0.2198 0.0469 0.1180 0.0168 0.2186 0.0471 900 Armstrong,B.j. 0.2565 0.0391 0.2653 0.0394 0.2635 0.0395 142 Armstrong,Darrell 0.2698 0.0731 0.2738 0.0737 0.3057 0.0772 689 Arroyo,Carlos 0.0745 0.0205 0.0701 0.0207 0.0811 0.0207 384 Artest,Ron 0.0910 0.0242 0.0914 0.0244 0.0653 0.0262 373 Askew,Vincent 0.0964 0.0180 0.0902 0.0182 0.0962 0.0181 767 Askins,Keith 0.1277 0.0469 0.1335 0.0473 0.1196 0.0473 387 Atkins,Chucky 0.0868 0.0309 0.0847 0.0312 0.0751 0.0315 831 Attles,Alvin 0.1721 0.0388 0.1824 0.0391 0.1733 0.0390 114 Augmon,Stacey 0.2926 0.0248 0.2857 0.0250 0.2973 0.0250 180 Austin,Isaac 0.2318 0.0261 0.2323 0.0264 0.2288 0.0263 470 Awtrey,Dennis 0.0475 0.0151 0.0525 0.0150 0.0477 0.0151 463 Bagley,John 0.0520 0.0309 0.0674 0.0311 0.0650 0.0315 165 Bailey,James 0.2524 0.0239 0.2571 0.0240 0.2474 0.0241 713 Bailey,Thurl 0.0887 0.0477 0.0916 0.0481 0.0843 0.0480 604 Baker,Vin 0.0246 0.0207 0.0232 0.0209 0.0087 0.0215 572 Ballard,Greg 0.0061 0.0526 0.0071 0.0530 0.0039 0.0531 349 Banks,Gene 0.1125 0.0711 0.1359 0.0709 0.1056 0.0716 552 Bantom,Mike 0.0003 0.0131 0.0046 0.0131 0.0006 0.0132 26 Barkley,Charles (HOF) 0.4999 0.0340 0.5088 0.0342 0.4979 0.0341 783 Barnes,Jim 0.1388 0.0348 0.1516 0.0351 0.1404 0.0350 771 Barnett,Dick 0.1301 0.0151 0.1298 0.0150 0.1298 0.0151 319 Barnett,Jim 0.1307 0.0228 0.1269 0.0229 0.1302 0.0229 856 Barnhill,John 0.1937 0.0377 0.1603 0.0376 0.1949 0.0379 799 Barros,Dana 0.1502 0.0174 0.1426 0.0175 0.1510 0.0175 581 Barry,Brent 0.0105 0.0141 0.0116 0.0142 0.0076 0.0142 305 Barry,Jon 0.1380 0.0155 0.1400 0.0156 0.1513 0.0161 524 Barry,Rick (HOF) 0.0143 0.0266 0.0369 0.0266 0.0161 0.0267 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 26 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 879 Battie,Tony 0.2288 0.0209 0.2301 0.0211 0.2444 0.0217 278 Battier,Shane 0.1538 0.0293 0.1590 0.0295 0.1675 0.0300 97 Battle,John 0.3124 0.0536 0.3070 0.0540 0.2957 0.0547 351 Baylor,Elgin (HOF) 0.1112 0.0182 0.1109 0.0183 0.1092 0.0183 468 Beard,Butch 0.0496 0.0066 0.0462 0.0067 0.0489 0.0066 653 Beaty,Zelmo 0.0515 0.0357 0.0654 0.0359 0.0561 0.0360 678 Bell,Raja 0.0688 0.0147 0.0680 0.0149 0.0680 0.0148 224 Bellamy,Walt (HOF) 0.1925 0.0207 0.2098 0.0205 0.1867 0.0209 887 Benjamin,Benoit 0.2411 0.0225 0.2351 0.0227 0.2420 0.0226 398 Benoit,David 0.0812 0.0173 0.0834 0.0175 0.0783 0.0175 303 Benson,Kent 0.1385 0.0287 0.1488 0.0288 0.1342 0.0289 451 Best,Travis 0.0549 0.0199 0.0584 0.0200 0.0381 0.0208 684 Bianchi,Al 0.0730 0.0688 0.1147 0.0670 0.0723 0.0691 417 Bibby,Henry 0.0715 0.0205 0.0928 0.0204 0.0667 0.0206 69 Bibby,Mike 0.3917 0.0252 0.3918 0.0255 0.3687 0.0269 813 Billups,Chauncey 0.1568 0.0257 0.1513 0.0259 0.1563 0.0259 378 Bing,Dave (HOF) 0.0942 0.0213 0.1060 0.0214 0.0909 0.0215 33 Bird,Larry (HOF) 0.4762 0.0381 0.4558 0.0382 0.4699 0.0384 921 Birdsong,Otis 0.3371 0.0629 0.3767 0.0629 0.3341 0.0633 698 Blackman,Rolando 0.0805 0.1367 0.1133 0.1375 0.0857 0.1374 649 Blaylock,Mookie 0.0496 0.0225 0.0488 0.0227 0.0562 0.0228 791 Blount,Corie 0.1451 0.0341 0.1459 0.0344 0.1355 0.0346 700 Blount,Mark 0.0815 0.0390 0.0846 0.0393 0.0876 0.0393 141 Bockhorn,Arlen 0.2705 0.0559 0.2063 0.0550 0.2734 0.0562 509 Boerwinkle,Tom 0.0236 0.0303 0.0268 0.0303 0.0226 0.0305 84 Bogues,Muggsy 0.3313 0.0332 0.3457 0.0332 0.3253 0.0335 785 Bol,Manute 0.1399 0.0301 0.1502 0.0302 0.1338 0.0304 860 Boozer,Bob 0.1971 0.0165 0.1818 0.0163 0.1972 0.0166 317 Bowen,Bruce 0.1309 0.0303 0.1303 0.0306 0.1059 0.0323 316 Bowen,Ryan 0.1312 0.0315 0.1427 0.0317 0.1304 0.0316 940 Bowie,Anthony 0.4713 0.0313 0.4809 0.0314 0.4652 0.0315 894 Bowie,Sam 0.2494 0.0349 0.2529 0.0352 0.2531 0.0351 448 Boykins,Earl 0.0567 0.0214 0.0529 0.0216 0.0585 0.0215 16 Bradley,Bill (HOF) 0.5757 0.1990 0.4580 0.1960 0.5795 0.2000 291 Bradley,Dudley 0.1476 0.0171 0.1606 0.0170 0.1535 0.0173 727 Bradley,Shawn 0.0987 0.0382 0.0868 0.0385 0.0808 0.0394 670 Brand,Elton 0.0648 0.0127 0.0619 0.0128 0.0587 0.0129 745 Brandon,Terrell 0.1091 0.0434 0.1097 0.0438 0.0993 0.0439 425 Bratz,Mike 0.0662 0.0217 0.0678 0.0217 0.0720 0.0219 341 Braun,Carl 0.1164 0.0155 0.0947 0.0149 0.1153 0.0156 273 Breuer,Randy 0.1581 0.0698 0.1614 0.0703 0.1466 0.0705 601 Brewer,Jim 0.0221 0.0283 0.0461 0.0283 0.0230 0.0284 563 Brewer,Ron 0.0020 0.0308 0.0038 0.0309 0.0009 0.0310 409 Brickowski,Frank 0.0758 0.0236 0.0800 0.0237 0.0807 0.0238 94 Bridgeman,Junior 0.3138 0.0924 0.3173 0.0930 0.3213 0.0930 50 Bridges,Bill 0.4344 0.0536 0.4063 0.0528 0.4346 0.0538 61 Bristow,Allan 0.4044 0.0439 0.4452 0.0424 0.4067 0.0442 155 Brooks,Scott 0.2601 0.0188 0.2603 0.0189 0.2643 0.0189 498 Brown,Chucky 0.0293 0.0125 0.0270 0.0126 0.0251 0.0126 640 Brown,Dee 0.0467 0.0273 0.0312 0.0274 0.0321 0.0280 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 27 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 454 Brown,Fred 0.0540 0.0322 0.0581 0.0306 0.0509 0.0324 99 Brown,John 0.3075 0.0224 0.3012 0.0223 0.3098 0.0225 206 Brown,Kwame 0.2031 0.1118 0.2066 0.1127 0.1585 0.1182 323 Brown,Mike 0.1287 0.0252 0.1228 0.0253 0.1201 0.0255 824 Brown,P.J. 0.1674 0.0478 0.1619 0.0482 0.1582 0.0483 638 Brown,Randy 0.0463 0.0213 0.0543 0.0215 0.0485 0.0215 556 Brown,Roger A. 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 119 Bryant,Emmette 0.2901 0.0442 0.2574 0.0442 0.2899 0.0444 878 Bryant,Joe 0.2273 0.0256 0.2330 0.0255 0.2310 0.0258 73 Bryant,Kobe 0.3759 0.0566 0.3787 0.0570 0.3698 0.0569 873 Bryant,Mark 0.2159 0.0300 0.2225 0.0303 0.2186 0.0302 460 Buckner,Greg 0.0524 0.0136 0.0607 0.0137 0.0542 0.0137 721 Buckner,Quinn 0.0944 0.0226 0.1057 0.0227 0.0957 0.0227 441 Buechler,Jud 0.0605 0.0157 0.0726 0.0157 0.0563 0.0158 568 Bullard,Matt 0.0040 0.0168 0.0063 0.0169 0.0063 0.0169 826 Burleson,Tom 0.1694 0.0304 0.1708 0.0294 0.1729 0.0306 833 Buse,Don 0.1735 0.0539 0.1814 0.0541 0.1664 0.0544 642 Butler,Caron 0.0475 0.0399 0.0475 0.0403 0.0608 0.0406 60 Caffey,Jason 0.4097 0.0205 0.4154 0.0206 0.3984 0.0209 342 Cage,Michael 0.1164 0.0167 0.1251 0.0168 0.1150 0.0168 130 Caldwell,Joe 0.2795 0.0318 0.2851 0.0314 0.2811 0.0320 439 Calhoun,Corky 0.0606 0.0215 0.0534 0.0215 0.0602 0.0216 281 Camby,Marcus 0.1526 0.0263 0.1465 0.0265 0.1557 0.0264 331 Campbell,Elden 0.1241 0.0306 0.1253 0.0308 0.1370 0.0312 784 Campbell,Tony 0.1392 0.0231 0.1348 0.0233 0.1452 0.0234 841 Carr,Antoine 0.1832 0.0170 0.1776 0.0170 0.1893 0.0172 712 Carr,Austin 0.0886 0.0692 0.1173 0.0693 0.0796 0.0698 64 Carr,Kenny 0.4010 0.0475 0.4134 0.0478 0.4058 0.0478 90 Carr,M.l. 0.3175 0.0498 0.3572 0.0488 0.3180 0.0500 630 Carroll,Joe Barry 0.0401 0.0194 0.0428 0.0194 0.0434 0.0195 692 Carter,Anthony 0.0774 0.0200 0.0783 0.0202 0.0630 0.0207 861 Carter,Fred 0.1999 0.0105 0.2220 0.0103 0.2020 0.0106 218 Carter,Vince 0.1981 0.0498 0.2004 0.0502 0.2093 0.0504 372 Cartwright,Bill 0.0971 0.0327 0.0994 0.0330 0.1024 0.0329 521 Cassell,Sam 0.0163 0.0340 0.0112 0.0342 0.0317 0.0348 21 Catchings,Harvey 0.5352 0.0987 0.5211 0.0992 0.5228 0.0996 121 Catledge,Terry 0.2886 0.0249 0.2962 0.0251 0.2826 0.0252 929 Cato,Kelvin 0.3746 0.0344 0.3774 0.0347 0.3793 0.0346 72 Causwell,Duane 0.3761 0.0783 0.3656 0.0789 0.3448 0.0816 606 Ceballos,Cedric 0.0280 0.0228 0.0304 0.0230 0.0216 0.0231 202 Chamberlain,Wilt (HOF) 0.2061 0.0195 0.2242 0.0192 0.2053 0.0196 96 Chambers,Tom 0.3126 0.0199 0.3049 0.0198 0.3156 0.0200 35 Chandler,Tyson 0.4609 0.0245 0.4609 0.0247 0.4455 0.0253 79 Chaney,Don 0.3465 0.0450 0.3563 0.0440 0.3493 0.0452 283 Chapman,Rex 0.1516 0.0528 0.1455 0.0533 0.1428 0.0533 868 Chappell,Len 0.2097 0.0153 0.1615 0.0140 0.2084 0.0154 467 Cheaney,Calbert 0.0497 0.0355 0.0446 0.0358 0.0477 0.0357 696 Cheeks,Maurice 0.0799 0.0490 0.0805 0.0493 0.0877 0.0494 944 Chenier,Phil 0.5431 0.0651 0.5863 0.0651 0.5453 0.0654 284 Chilcutt,Pete 0.1506 0.0220 0.1563 0.0222 0.1391 0.0225 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 28 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 52 Childs,Chris 0.4276 0.0552 0.4295 0.0557 0.4284 0.0555 472 Chones,Jim 0.0468 0.0317 0.0483 0.0320 0.0527 0.0320 822 Christie,Doug 0.1643 0.0186 0.1692 0.0188 0.1600 0.0188 194 Clark,Archie 0.2128 0.0204 0.2304 0.0204 0.2131 0.0205 355 Cleamons,Jim 0.1091 0.0235 0.1252 0.0228 0.1093 0.0236 668 Clemens,John 0.0636 0.0200 0.0844 0.0193 0.0663 0.0201 587 Clifton,Nat 0.0168 0.0563 0.0643 0.0528 0.0182 0.0566 307 Coleman,Derrick 0.1366 0.0341 0.1471 0.0343 0.1530 0.0350 941 Coleman,Jack 0.5151 0.1226 0.0132 0.0321 0.5132 0.1232 904 Coles,Bimbo 0.2672 0.0393 0.2608 0.0396 0.2682 0.0395 863 Collins,Doug 0.2015 0.1044 0.2534 0.1042 0.2039 0.1049 853 Collins,Jarron 0.1919 0.0711 0.1972 0.0717 0.2023 0.0718 139 Collins,Jason 0.2713 0.0393 0.2741 0.0397 0.3000 0.0419 528 Colter,Steve 0.0108 0.0346 0.0127 0.0347 0.0207 0.0351 613 Conlin,Ed 0.0312 0.0231 0.0117 0.0223 0.0298 0.0232 905 Conner,Lester 0.2681 0.0442 0.2865 0.0445 0.2817 0.0450 390 Cook,Darwin 0.0829 0.0655 0.0510 0.0657 0.0770 0.0659 621 Cook,Jeff 0.0365 0.0244 0.0498 0.0245 0.0396 0.0245 871 Cooper,Chuck 0.2113 0.0320 0.0996 0.0277 0.2089 0.0322 415 Cooper,Michael 0.0731 0.0825 0.0789 0.0832 0.0463 0.0850 927 Cooper,Wayne 0.3700 0.0297 0.3950 0.0294 0.3759 0.0299 418 Corbin,Tyrone 0.0707 0.0164 0.0719 0.0165 0.0776 0.0166 320 Corzine,Dave 0.1305 0.0155 0.1323 0.0156 0.1218 0.0158 312 Costello,Larry 0.1339 0.0121 0.1563 0.0120 0.1333 0.0122 170 Counts,Mel 0.2472 0.0120 0.2564 0.0120 0.2441 0.0121 926 Cousy,Bob (HOF) 0.3681 0.2280 0.1010 0.2037 0.3704 0.2291 512 Cowens,Dave (HOF) 0.0217 0.0617 0.0697 0.0594 0.0249 0.0620 144 Crawford,Jamal 0.2681 0.0260 0.2689 0.0263 0.2568 0.0265 564 Criss,Charlie 0.0021 0.1259 0.0306 0.1255 0.0138 0.1269 178 Croshere,Austin 0.2350 0.0246 0.2325 0.0248 0.2339 0.0247 544 Crotty,John 0.0040 0.0192 0.0059 0.0193 0.0057 0.0193 686 Cummings,Pat 0.0732 0.0218 0.0659 0.0220 0.0707 0.0219 56 Cummings,Terry 0.4193 0.0544 0.4221 0.0548 0.4318 0.0551 598 Cunningham,Billy (HOF) 0.0201 0.0512 0.0239 0.0514 0.0229 0.0515 681 Cureton,Earl 0.0723 0.0161 0.0783 0.0162 0.0705 0.0162 685 Curry,Dell 0.0731 0.0220 0.0838 0.0221 0.0637 0.0224 647 Curry,Eddy 0.0492 0.0300 0.0469 0.0302 0.0487 0.0301 51 Curry,Michael 0.4284 0.0328 0.4379 0.0330 0.4290 0.0330 343 Dailey,Quintin 0.1161 0.0434 0.1088 0.0437 0.1140 0.0436 239 Dalembert,Samuel 0.1813 0.0120 0.1828 0.0121 0.1651 0.0128 710 Dampier,Erick 0.0874 0.0150 0.0822 0.0151 0.1068 0.0162 875 Dandridge,Bob 0.2181 0.1034 0.2112 0.1042 0.2365 0.1049 503 Daniels,Antonio 0.0281 0.0132 0.0274 0.0133 0.0227 0.0133 554 Daniels,Mel 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 523 Dantley,Adrian (HOF) 0.0145 0.0259 0.0180 0.0259 0.0063 0.0262 935 Daugherty,Brad 0.4536 0.1158 0.4578 0.1168 0.4476 0.1165 2 Davies,Bob (HOF) 1.6047 3.1000 0.6233 2.7625 1.6266 3.1167 487 Davis,Antonio 0.0373 0.0208 0.0369 0.0209 0.0431 0.0210 633 Davis,Baron 0.0418 0.0213 0.0416 0.0215 0.0913 0.0285 769 Davis,Brad 0.1283 0.1239 0.1323 0.1248 0.1281 0.1245 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 29 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 132 Davis,Charlie 0.2786 0.0349 0.2854 0.0352 0.2772 0.0351 255 Davis,Dale 0.1712 0.0376 0.1706 0.0380 0.1760 0.0379 123 Davis,Hubert 0.2870 0.0351 0.2841 0.0354 0.2618 0.0371 738 Davis,Jim 0.1053 0.0370 0.1554 0.0357 0.1055 0.0372 280 Davis,Johnny 0.1533 0.0257 0.1463 0.0257 0.1537 0.0259 916 Davis,Ricky 0.3214 0.0208 0.3164 0.0210 0.3121 0.0212 438 Davis,Terry 0.0611 0.0146 0.0594 0.0148 0.0662 0.0148 65 Davis,Walter 0.3987 0.0498 0.4124 0.0501 0.4012 0.0501 27 Dawkins,Darryl 0.4931 0.0469 0.5235 0.0468 0.4945 0.0472 583 Dawkins,Johnny 0.0118 0.0156 0.0152 0.0157 0.0161 0.0157 226 Day,Todd 0.1917 0.0376 0.1964 0.0378 0.1860 0.0378 322 Debusschere,Dave (HOF) 0.1297 0.0211 0.1572 0.0208 0.1304 0.0212 231 Declercq,Andrew 0.1866 0.0230 0.1906 0.0232 0.1884 0.0231 253 Dehere,Terry 0.1730 0.0277 0.1614 0.0279 0.1646 0.0280 212 Del Negro,Vinny 0.2016 0.0335 0.2054 0.0337 0.2093 0.0338 360 Dele,Bison 0.1075 0.0221 0.1083 0.0223 0.1076 0.0223 266 Delk,Tony 0.1627 0.0203 0.1566 0.0204 0.1789 0.0211 893 Dierking,Connie 0.2469 0.0171 0.2312 0.0167 0.2490 0.0172 217 Dietrick,Coby 0.1985 0.1178 0.1998 0.1180 0.1878 0.1187 488 Diop,Desagana 0.0370 0.0375 0.0388 0.0378 0.0547 0.0386 314 Dischinger,Terry 0.1332 0.0214 0.1107 0.0211 0.1324 0.0215 558 Divac,Vlade 0.0009 0.0339 0.0020 0.0342 0.0230 0.0355 392 Doleac,Michael 0.0828 0.0076 0.0892 0.0077 0.0752 0.0078 265 Donaldson,James 0.1631 0.0513 0.1844 0.0515 0.1579 0.0517 340 Dooling,Keyon 0.1179 0.0186 0.1130 0.0187 0.1330 0.0194 872 Douglas,Leon 0.2147 0.0512 0.2026 0.0516 0.2111 0.0515 306 Douglas,Sherman 0.1366 0.0177 0.1418 0.0178 0.1357 0.0178 922 Dreiling,Greg 0.3407 0.0742 0.3547 0.0748 0.3397 0.0746 821 Drew,John 0.1637 0.0665 0.2066 0.0665 0.1631 0.0669 609 Drew,Larry 0.0285 0.0350 0.0211 0.0351 0.0232 0.0352 760 Drexler,Clyde (HOF) 0.1213 0.0333 0.1259 0.0336 0.1160 0.0335 111 Duckworth,Kevin 0.2956 0.0440 0.3074 0.0444 0.3132 0.0452 244 Dudley,Chris 0.1781 0.0265 0.1837 0.0268 0.1738 0.0267 659 Dukes,Walter 0.0552 0.0412 0.0524 0.0397 0.0586 0.0414 445 Dumars,Joe (HOF) 0.0592 0.0477 0.0663 0.0479 0.0641 0.0480 688 Duncan,Tim 0.0738 0.0778 0.0645 0.0785 0.0596 0.0788 214 Dunleavy,Mike 0.2005 0.0671 0.1969 0.0674 0.1899 0.0678 38 Dunleavy,Mike 0.4545 0.0459 0.4521 0.0463 0.4462 0.0463 37 Dunn,T.r. 0.4547 0.0413 0.4905 0.0412 0.4514 0.0415 175 Eackles,Ledell 0.2431 0.0498 0.2606 0.0502 0.2260 0.0509 302 Eaton,Mark 0.1402 0.0516 0.1700 0.0518 0.1314 0.0521 238 Edwards,Blue 0.1819 0.0139 0.1926 0.0140 0.1814 0.0140 794 Edwards,James 0.1468 0.0174 0.1535 0.0176 0.1494 0.0175 154 Edwards,Kevin 0.2608 0.0422 0.2687 0.0424 0.2421 0.0434 191 Egan,Johnny 0.2175 0.0197 0.2352 0.0198 0.2167 0.0198 406 Ehlo,Craig 0.0767 0.0496 0.0680 0.0500 0.0607 0.0506 447 Eisley,Howard 0.0577 0.0149 0.0488 0.0150 0.0631 0.0150 541 Elie,Mario 0.0054 0.0294 0.0029 0.0296 0.0107 0.0303 855 Elliott,Sean 0.1937 0.0399 0.1872 0.0402 0.2081 0.0407 882 Ellis,Dale 0.2355 0.0179 0.2295 0.0180 0.2410 0.0180 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 30 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 233 Ellis,Joe 0.1840 0.3428 0.1978 0.3168 0.1729 0.3448 594 Ellis,Laphonso 0.0195 0.0115 0.0160 0.0116 0.0143 0.0117 122 Ellis,Leroy 0.2876 0.0198 0.2424 0.0192 0.2861 0.0199 397 Ellison,Pervis 0.0815 0.0399 0.0636 0.0401 0.0971 0.0408 634 Elmore,Len 0.0421 0.0256 0.0146 0.0255 0.0428 0.0257 465 Embry,Wayne 0.0505 0.0383 0.0918 0.0380 0.0505 0.0385 251 English,Alex (HOF) 0.1735 0.0231 0.1769 0.0227 0.1725 0.0232 494 Erickson,Keith 0.0320 0.0171 0.0400 0.0171 0.0333 0.0172 770 Erving,Julius (HOF) 0.1285 0.3004 0.1906 0.2984 0.1307 0.3019 294 Evans,Mike 0.1464 0.0321 0.1343 0.0324 0.1462 0.0323 353 Evans,Reggie 0.1094 0.0086 0.1104 0.0086 0.1257 0.0094 625 Ewing,Patrick (HOF) 0.0389 0.0825 0.0480 0.0832 0.0435 0.0830 105 Farmer,Mike 0.2991 0.0230 0.2798 0.0229 0.3009 0.0231 87 Felix,Ray 0.3281 0.0343 0.3018 0.0295 0.3254 0.0345 428 Ferrell,Duane 0.0655 0.0306 0.0688 0.0308 0.0692 0.0308 557 Ferry,Bob 0.0006 0.0560 0.0392 0.0551 0.0011 0.0563 42 Ferry,Danny 0.4418 0.0505 0.4488 0.0509 0.4479 0.0508 531 Finkel,Hank 0.0097 0.0768 0.0714 0.0751 0.0122 0.0772 846 Finley,Michael 0.1854 0.0339 0.1966 0.0341 0.1766 0.0343 766 Fisher,Derek 0.1244 0.0127 0.1230 0.0128 0.1162 0.0129 906 Fleming,Vern 0.2720 0.0367 0.2790 0.0370 0.2712 0.0368 910 Floyd,Sleepy 0.2795 0.0501 0.2778 0.0505 0.2738 0.0504 93 Ford,Chris 0.3162 0.0250 0.3064 0.0245 0.3139 0.0252 877 Ford,Don 0.2259 0.1048 0.2672 0.1048 0.2397 0.1059 381 Ford,Phil 0.0928 0.0408 0.0717 0.0410 0.0934 0.0410 157 Fortson,Danny 0.2582 0.0160 0.2580 0.0161 0.2583 0.0160 747 Foster,Fred 0.1102 0.0116 0.0937 0.0117 0.1104 0.0117 645 Foster,Greg 0.0485 0.0243 0.0465 0.0245 0.0596 0.0248 890 Foster,Jeff 0.2451 0.1289 0.2424 0.1301 0.2420 0.1296 592 Foust,Larry 0.0187 0.0673 0.0506 0.0669 0.0243 0.0678 580 Fox,Jim 0.0100 0.0211 0.0310 0.0205 0.0115 0.0212 559 Fox,Rick 0.0011 0.0176 0.0032 0.0177 0.0076 0.0178 751 Foyle,Adonal 0.1130 0.0336 0.1138 0.0339 0.0950 0.0347 88 Francis,Steve 0.3255 0.0454 0.3263 0.0457 0.3332 0.0458 806 Frazier,Walt (HOF) 0.1544 0.1054 0.1195 0.1058 0.1577 0.1060 348 Free,World 0.1126 0.0363 0.1252 0.0363 0.1164 0.0366 949 Fulks,Joe (HOF) 6.3002 131.5695 0.3915 30.3501 6.4018 132.2524 25 Gale,Mike 0.5036 0.0500 0.5223 0.0503 0.4948 0.0505 321 Gallatin,Harry (HOF) 0.1299 0.3657 0.2854 0.3414 0.1337 0.3675 778 Gambee,Dave 0.1345 0.0180 0.1759 0.0173 0.1366 0.0181 717 Gamble,Kevin 0.0928 0.0532 0.1050 0.0536 0.0964 0.0535 530 Garland,Winston 0.0098 0.0125 0.0044 0.0126 0.0074 0.0126 219 Garmaker,Dick 0.1951 0.0173 0.2008 0.0164 0.1955 0.0174 13 Garnett,Kevin 0.6041 0.0303 0.5999 0.0305 0.5965 0.0306 903 Garrity,Pat 0.2666 0.0413 0.2681 0.0417 0.2544 0.0420 47 Gasol,Pau 0.4370 0.0689 0.4385 0.0695 0.4429 0.0693 843 Gatling,Chris 0.1848 0.0322 0.1841 0.0325 0.1960 0.0327 693 Gattison,Kenny 0.0775 0.0291 0.0866 0.0293 0.0848 0.0294 145 Geiger,Matt 0.2664 0.0366 0.2739 0.0369 0.2567 0.0370 762 George,Devean 0.1232 0.0254 0.1270 0.0256 0.1109 0.0259 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 31 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 768 George,Jack 0.1282 0.0551 0.0214 0.0417 0.1292 0.0553 675 Gervin,George (HOF) 0.0667 0.2056 0.1228 0.2020 0.0561 0.2069 249 Gianelli,John 0.1747 0.0221 0.1837 0.0223 0.1788 0.0223 810 Gill,Kendall 0.1559 0.0198 0.1460 0.0199 0.1532 0.0199 817 Gilliam,Armen 0.1594 0.0243 0.1561 0.0245 0.1612 0.0244 338 Gilliam,Herm 0.1181 0.0123 0.1426 0.0122 0.1185 0.0124 222 Gilmore,Artis 0.1938 0.0288 0.2204 0.0286 0.1941 0.0289 942 Ginobili,Emmanuel 0.5158 0.0638 0.5166 0.0644 0.5049 0.0645 469 Glenn,Mike 0.0492 0.0239 0.0575 0.0240 0.0455 0.0240 754 Gminski,Mike 0.1149 0.0662 0.1143 0.0667 0.1323 0.0674 160 Gola,Tom (HOF) 0.2560 0.0125 0.2679 0.0119 0.2551 0.0126 779 Gondrezick,Glen 0.1355 0.0337 0.1503 0.0337 0.1321 0.0339 205 Gooden,Drew 0.2039 0.0280 0.2074 0.0282 0.1834 0.0294 345 Goodrich,Gail (HOF) 0.1157 0.0183 0.1278 0.0183 0.1151 0.0184 328 Graboski,Joe 0.1259 0.1248 0.2628 0.0494 0.1221 0.1254 240 Grant,Brian 0.1802 0.0312 0.1853 0.0314 0.2040 0.0330 421 Grant,Gary 0.0691 0.0549 0.0836 0.0553 0.0604 0.0554 519 Grant,Harvey 0.0173 0.0426 0.0189 0.0429 0.0204 0.0428 78 Grant,Horace 0.3565 0.0235 0.3625 0.0236 0.3609 0.0237 167 Grayer,Jeff 0.2504 0.0330 0.2399 0.0333 0.2515 0.0332 367 Green,A.c. 0.0992 0.0192 0.1051 0.0191 0.1015 0.0193 332 Green,Johnny 0.1236 0.0263 0.0361 0.0239 0.1183 0.0265 171 Green,Rickey 0.2467 0.0439 0.2241 0.0441 0.2448 0.0441 172 Green,Si 0.2461 0.0301 0.2520 0.0304 0.2463 0.0303 588 Green,Sidney 0.0172 0.0070 0.0198 0.0070 0.0167 0.0070 66 Greenwood,David 0.3955 0.0417 0.4310 0.0416 0.4024 0.0421 108 Greer,Hal (HOF) 0.2969 0.1760 0.4261 0.1703 0.3023 0.1770 724 Grevey,Kevin 0.0977 0.0369 0.1048 0.0370 0.0943 0.0372 715 Griffin,Adrian 0.0896 0.0268 0.0903 0.0270 0.0685 0.0282 618 Griffin,Paul 0.0340 0.0382 0.0143 0.0381 0.0411 0.0385 151 Griffith,Darrell 0.2619 0.0316 0.2757 0.0318 0.2584 0.0318 55 Gross,Bob 0.4241 0.0610 0.4309 0.0615 0.4317 0.0615 546 Grunfeld,Ernie 0.0034 0.0462 0.0095 0.0466 0.0026 0.0466 823 Guerin,Richie 0.1668 0.0199 0.1307 0.0193 0.1675 0.0200 462 Gugliotta,Tom 0.0522 0.0336 0.0643 0.0339 0.0567 0.0338 565 Guokas,Matt 0.0024 0.0124 0.0259 0.0115 0.0011 0.0125 204 Hagan,Cliff (HOF) 0.2042 0.1911 0.6115 0.1403 0.2075 0.1920 507 Hairston,Happy 0.0270 0.0128 0.0150 0.0125 0.0298 0.0129 383 Ham,Darvin 0.0918 0.0180 0.0872 0.0181 0.0889 0.0181 742 Hamilton,Richard 0.1076 0.0747 0.1256 0.0752 0.1066 0.0750 484 Hammonds,Tom 0.0396 0.0215 0.0363 0.0217 0.0365 0.0217 413 Hannum,Alex (HOF) 0.0739 0.0068 0.0654 0.0069 0.0736 0.0069 464 Hansen,Bob 0.0513 0.0190 0.0480 0.0192 0.0496 0.0191 911 Hanzlik,Bill 0.2810 0.0697 0.3171 0.0693 0.2723 0.0703 100 Hardaway,Anfernee 0.3067 0.0317 0.2933 0.0319 0.3302 0.0335 149 Hardaway,Tim 0.2627 0.0306 0.2710 0.0308 0.2643 0.0308 91 Harper,Derek 0.3174 0.0311 0.3183 0.0314 0.3351 0.0322 486 Harper,Ron 0.0391 0.0476 0.0282 0.0479 0.0458 0.0479 449 Harpring,Matt 0.0552 0.0165 0.0560 0.0166 0.0456 0.0168 118 Harrington,Al 0.2904 0.0131 0.2926 0.0132 0.3404 0.0204 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 32 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 245 Harrington,Othella 0.1759 0.0172 0.1783 0.0174 0.1741 0.0173 566 Harris,Lucious 0.0034 0.0329 0.0090 0.0331 0.0020 0.0331 39 Harrison,Bob 0.4525 0.0451 0.4632 0.0440 0.4523 0.0453 388 Haskins,Clem 0.0847 0.0260 0.0730 0.0250 0.0852 0.0262 424 Hassell,Trenton 0.0674 0.0134 0.0743 0.0135 0.0650 0.0135 543 Hastings,Scott 0.0040 0.0580 0.0050 0.0584 0.0004 0.0584 869 Havlicek,John (HOF) 0.2100 0.0335 0.1353 0.0318 0.2119 0.0337 477 Hawes,Steve 0.0439 0.0303 0.0462 0.0305 0.0447 0.0304 179 Hawkins,Connie (HOF) 0.2341 0.0217 0.2397 0.0217 0.2331 0.0218 429 Hawkins,Hersey 0.0655 0.0123 0.0744 0.0124 0.0680 0.0123 818 Hawkins,Tom 0.1603 0.0144 0.1920 0.0132 0.1590 0.0145 192 Hayes,Elvin (HOF) 0.2175 0.0360 0.2146 0.0362 0.2206 0.0362 46 Haywood,Brendan 0.4375 0.0539 0.4393 0.0544 0.4509 0.0547 628 Hazzard,Walt 0.0391 0.0152 0.0315 0.0153 0.0396 0.0153 476 Heard,Garfield 0.0448 0.0193 0.0533 0.0188 0.0447 0.0194 444 Heinsohn,Tom (HOF) 0.0596 0.0865 0.0761 0.0870 0.0587 0.0869 246 Henderson,Alan 0.1759 0.0212 0.1808 0.0214 0.1854 0.0216 529 Henderson,Gerald 0.0108 0.0167 0.0026 0.0167 0.0123 0.0168 148 Henderson,Tom 0.2651 0.0413 0.2966 0.0413 0.2668 0.0415 884 Herrera,Carl 0.2399 0.0596 0.2491 0.0601 0.2483 0.0601 242 Hetzel,Fred 0.1795 0.0185 0.1778 0.0182 0.1762 0.0186 914 Higgins,Rod 0.3073 0.0294 0.3162 0.0296 0.3043 0.0296 695 Hill,Armond 0.0792 0.0526 0.0628 0.0528 0.0832 0.0529 106 Hill,Grant 0.2989 0.0319 0.3015 0.0322 0.2975 0.0321 870 Hill,Tyrone 0.2110 0.0303 0.2248 0.0305 0.1948 0.0312 143 Hillman,Darnell 0.2685 0.0266 0.3113 0.0260 0.2660 0.0267 200 Hinson,Roy 0.2085 0.0340 0.2107 0.0342 0.2104 0.0342 706 Hitch,Lew 0.0860 0.0115 0.1056 0.0110 0.0855 0.0116 840 Hodges,Craig 0.1825 0.0236 0.1694 0.0237 0.1930 0.0241 729 Hoiberg,Fred 0.0993 0.0186 0.1021 0.0188 0.0861 0.0192 827 Hollins,Lionel 0.1695 0.0308 0.1886 0.0309 0.1773 0.0311 682 Hornacek,Jeff 0.0724 0.0200 0.0675 0.0201 0.0670 0.0202 247 Horry,Robert 0.1755 0.0326 0.1841 0.0329 0.1710 0.0328 757 House,Eddie 0.1162 0.0080 0.1174 0.0081 0.1285 0.0085 648 Houston,Allan 0.0493 0.0298 0.0481 0.0301 0.0462 0.0300 755 Howard,Juwan 0.1149 0.0148 0.1178 0.0150 0.1074 0.0151 59 Howell,Bailey (HOF) 0.4106 0.0276 0.3581 0.0268 0.4080 0.0277 419 Hubbard,Phil 0.0695 0.0376 0.0857 0.0377 0.0651 0.0378 697 Hudson,Lou 0.0800 0.0212 0.0531 0.0212 0.0844 0.0214 708 Hudson,Troy 0.0865 0.0223 0.0848 0.0225 0.0907 0.0224 731 Hughes,Larry 0.1002 0.0169 0.1028 0.0171 0.0952 0.0171 539 Humphries,Jay 0.0056 0.0200 0.0275 0.0200 0.0085 0.0201 324 Hundley,Rod 0.1280 0.0804 0.1974 0.0781 0.1267 0.0808 624 Hunter,Lindsey 0.0386 0.0124 0.0392 0.0125 0.0317 0.0126 851 Huston,Geoff 0.1908 0.0186 0.2013 0.0187 0.1933 0.0187 270 Hutchins,Mel 0.1601 0.0890 0.1957 0.0861 0.1587 0.0894 293 Iavaroni,Marc 0.1464 0.0355 0.1562 0.0357 0.1461 0.0356 45 Ilgauskas,Zydrunas 0.4398 0.0321 0.4407 0.0324 0.4410 0.0323 691 Imhoff,Darrall 0.0762 0.0268 0.0535 0.0266 0.0753 0.0270 40 Issel,Dan (HOF) 0.4456 0.1281 0.4903 0.1286 0.4242 0.1301 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 33 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 23 Iverson,Allen 0.5133 0.0300 0.5237 0.0302 0.5136 0.0301 819 Jackson,Bobby 0.1621 0.0185 0.1589 0.0187 0.1699 0.0188 48 Jackson,Jaren 0.4357 0.0277 0.4379 0.0280 0.4220 0.0284 254 Jackson,Jim 0.1726 0.0145 0.1713 0.0146 0.1608 0.0149 389 Jackson,Lucious 0.0835 0.0219 0.0966 0.0218 0.0831 0.0220 617 Jackson,Mark 0.0337 0.0203 0.0245 0.0204 0.0440 0.0207 848 Jackson,Phil 0.1856 0.0180 0.1717 0.0181 0.1860 0.0181 263 Jackson,Stephen 0.1642 0.0056 0.1661 0.0056 0.1613 0.0057 401 James,Mike 0.0796 0.0133 0.0788 0.0134 0.0852 0.0135 485 Jamison,Antawn 0.0396 0.0190 0.0383 0.0192 0.0244 0.0198 452 Jefferson,Richard 0.0543 0.0339 0.0497 0.0342 0.0256 0.0365 297 Johnson,Anthony 0.1430 0.0096 0.1440 0.0097 0.1411 0.0097 241 Johnson,Avery 0.1800 0.0215 0.1736 0.0216 0.1872 0.0217 446 Johnson,Buck 0.0580 0.0326 0.0659 0.0329 0.0511 0.0329 534 Johnson,Charlie 0.0079 0.0381 0.0189 0.0383 0.0116 0.0384 912 Johnson,Clemon 0.2811 0.0288 0.2756 0.0290 0.2825 0.0290 857 Johnson,Dennis 0.1939 0.0244 0.1761 0.0244 0.1922 0.0245 844 Johnson,Eddie 0.1851 0.0905 0.1671 0.0911 0.1911 0.0910 615 Johnson,Eddie A. 0.0334 0.0255 0.0417 0.0257 0.0320 0.0256 308 Johnson,Ervin 0.1364 0.0205 0.1369 0.0207 0.1310 0.0207 752 Johnson,Frank 0.1140 0.0463 0.1205 0.0466 0.1251 0.0469 845 Johnson,George L. 0.1854 0.0167 0.1877 0.0168 0.1858 0.0168 515 Johnson,George T. 0.0189 0.0394 0.0309 0.0396 0.0135 0.0396 867 Johnson,Gus 0.2096 0.0360 0.1861 0.0361 0.2062 0.0362 185 Johnson,Joe 0.2289 0.0811 0.2282 0.0817 0.2458 0.0823 208 Johnson,John 0.2026 0.0172 0.1882 0.0173 0.2056 0.0173 146 Johnson,Kevin 0.2658 0.0767 0.2855 0.0772 0.2820 0.0778 442 Johnson,Larry 0.0601 0.0231 0.0620 0.0233 0.0550 0.0232 89 Johnson,Magic (HOF) 0.3241 0.0712 0.3172 0.0718 0.3437 0.0727 924 Johnson,Marques 0.3548 0.1254 0.3407 0.1259 0.3658 0.1263 346 Johnson,Mickey 0.1131 0.0165 0.1133 0.0165 0.1108 0.0166 743 Johnson,Ollie 0.1077 0.0208 0.1251 0.0207 0.1084 0.0209 437 Johnson,Steve 0.0613 0.0226 0.0491 0.0227 0.0590 0.0227 816 Johnson,Vinnie 0.1592 0.0485 0.1656 0.0489 0.1545 0.0488 422 Johnston,Neil (HOF) 0.0687 0.0557 0.0711 0.0148 0.0694 0.0560 30 Jones,Bobby 0.4842 0.0705 0.4850 0.0701 0.4926 0.0711 723 Jones,Caldwell 0.0977 0.2336 0.0463 0.2348 0.0871 0.2351 545 Jones,Charles 0.0037 0.1112 0.0345 0.1109 0.0003 0.1119 315 Jones,Damon 0.1328 0.0072 0.1376 0.0073 0.1442 0.0076 917 Jones,Dwight 0.3253 0.0301 0.3442 0.0302 0.3295 0.0303 256 Jones,Eddie 0.1711 0.0280 0.1660 0.0282 0.1507 0.0294 669 Jones,Jumaine 0.0643 0.0452 0.0658 0.0455 0.0909 0.0474 626 Jones,K.c. (HOF) 0.0389 0.0532 0.0378 0.0518 0.0369 0.0534 801 Jones,Popeye 0.1518 0.0307 0.1431 0.0309 0.1437 0.0311 803 Jones,Sam (HOF) 0.1530 0.1534 0.0520 0.1414 0.1525 0.1542 732 Jones,Wali 0.1027 0.0300 0.1209 0.0294 0.1022 0.0301 147 Jordan,Eddie 0.2657 0.0811 0.2617 0.0816 0.2675 0.0816 126 Jordan,Michael 0.2842 0.0488 0.2783 0.0492 0.2988 0.0497 197 Jordon,Phil 0.2104 0.0169 0.1894 0.0157 0.2110 0.0170 627 Kauffman,Bob 0.0390 0.0167 0.0438 0.0163 0.0409 0.0168 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 34 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 235 Keefe,Adam 0.1832 0.0205 0.1872 0.0206 0.1912 0.0207 553 Keller,Billy 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 525 Kelley,Rich 0.0142 0.0236 0.0013 0.0237 0.0098 0.0237 718 Kemp,Shawn 0.0931 0.0264 0.0872 0.0266 0.0943 0.0265 603 Kenon,Larry 0.0223 0.0436 0.0225 0.0439 0.0273 0.0439 899 Kerr,Johnny 0.2556 0.0319 0.2721 0.0300 0.2548 0.0321 350 Kerr,Steve 0.1123 0.0278 0.1071 0.0280 0.1207 0.0282 22 Kersey,Jerome 0.5258 0.0625 0.5447 0.0628 0.5102 0.0635 847 Kidd,Jason 0.1856 0.0279 0.1821 0.0281 0.2053 0.0292 759 King,Albert 0.1192 0.0352 0.1253 0.0352 0.1049 0.0360 407 King,Bernard 0.0763 0.0384 0.0533 0.0385 0.0739 0.0386 186 King,George 0.2250 0.0517 0.1986 0.0516 0.2268 0.0520 644 King,Jim 0.0478 0.0233 0.0650 0.0208 0.0462 0.0235 68 King,Reggie 0.3918 0.0405 0.4278 0.0404 0.3960 0.0407 112 King,Stacey 0.2952 0.0400 0.3047 0.0403 0.3011 0.0403 7 Kirilenko,Andrei 0.7888 0.0886 0.7889 0.0893 0.7906 0.0890 395 Kite,Greg 0.0820 0.0236 0.0595 0.0235 0.0796 0.0237 135 Kittles,Kerry 0.2754 0.0366 0.2818 0.0368 0.2799 0.0368 363 Kleine,Joe 0.1022 0.0308 0.0787 0.0307 0.0996 0.0309 115 Knight,Billy 0.2923 0.0299 0.2999 0.0297 0.2880 0.0301 934 Knight,Brevin 0.4158 0.0267 0.4144 0.0269 0.4056 0.0271 136 Kojis,Don 0.2751 0.0226 0.2820 0.0228 0.2726 0.0227 740 Komives,Howard 0.1069 0.0269 0.0645 0.0265 0.1071 0.0270 458 Koncak,Jon 0.0528 0.0256 0.0637 0.0258 0.0471 0.0258 561 Krebs,Jim 0.0018 0.0917 0.0631 0.0906 0.0027 0.0922 657 Krystkowiak,Larry 0.0532 0.0162 0.0502 0.0164 0.0577 0.0164 479 Kuberski,Steve 0.0435 0.0103 0.0377 0.0103 0.0413 0.0104 168 Kukoc,Toni 0.2488 0.0339 0.2625 0.0341 0.2414 0.0342 412 Kunnert,Kevin 0.0746 0.0353 0.0880 0.0352 0.0754 0.0355 166 Kupchak,Mitch 0.2509 0.0357 0.2567 0.0356 0.2423 0.0361 223 Lacey,Sam 0.1935 0.0237 0.1973 0.0238 0.1924 0.0238 426 Laettner,Christian 0.0662 0.0216 0.0749 0.0218 0.0567 0.0220 327 Lafrentz,Raef 0.1264 0.0241 0.1215 0.0243 0.1121 0.0248 804 Laimbeer,Bill 0.1534 0.0598 0.1442 0.0602 0.1538 0.0600 641 Lambert,John 0.0472 0.0766 0.0025 0.0758 0.0576 0.0773 920 Landsberger,Mark 0.3345 0.0334 0.3244 0.0336 0.3403 0.0336 569 Lang,Andrew 0.0044 0.0251 0.0017 0.0253 0.0009 0.0253 152 Lanier,Bob (HOF) 0.2613 0.0505 0.2560 0.0499 0.2597 0.0508 140 Larusso,Rudy 0.2706 0.0298 0.3172 0.0272 0.2694 0.0300 434 Leavell,Allen 0.0634 0.0784 0.0287 0.0787 0.0506 0.0792 661 Leckner,Eric 0.0577 0.0249 0.0582 0.0252 0.0511 0.0252 520 Lee,Clyde 0.0167 0.1433 0.0950 0.1402 0.0263 0.1443 772 Lee,Ron 0.1310 0.0145 0.1520 0.0145 0.1323 0.0146 551 Lenard,Voshon 0.0007 0.0112 0.0012 0.0113 0.0004 0.0113 932 Leonard,Bob 0.4057 0.0168 0.4160 0.0164 0.4050 0.0169 169 Lever,Lafayette 0.2484 0.0451 0.2615 0.0450 0.2487 0.0453 196 Levingston,Cliff 0.2106 0.0158 0.2142 0.0159 0.2115 0.0159 946 Lewis,Freddie 0.6278 0.4889 0.8394 0.4219 0.6314 0.4914 304 Lewis,Rashard 0.1383 0.0283 0.1381 0.0286 0.1130 0.0304 211 Lewis,Reggie 0.2019 0.0269 0.2059 0.0270 0.1967 0.0271 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 35 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 252 Lister,Alton 0.1731 0.0208 0.1843 0.0209 0.1716 0.0209 573 Lloyd,Earl 0.0062 0.1926 0.1188 0.1843 0.0051 0.1936 269 Lohaus,Brad 0.1607 0.0255 0.1418 0.0256 0.1649 0.0257 749 Long,Grant 0.1123 0.0348 0.1100 0.0351 0.1197 0.0352 58 Long,John 0.4173 0.0414 0.4037 0.0411 0.4144 0.0416 526 Longley,Luc 0.0114 0.0314 0.0148 0.0317 0.0129 0.0316 758 Loscutoff,Jim 0.1177 0.0144 0.0894 0.0142 0.1172 0.0144 722 Loughery,Kevin 0.0962 0.0330 0.1153 0.0325 0.0965 0.0331 631 Love,Bob 0.0412 0.0510 0.0019 0.0478 0.0441 0.0513 81 Lovellette,Clyde (HOF) 0.3398 0.0334 0.3318 0.0335 0.3404 0.0336 535 Lucas,Jerry (HOF) 0.0074 0.0186 0.0383 0.0184 0.0054 0.0187 83 Lucas,John 0.3315 0.0194 0.3361 0.0194 0.3270 0.0196 513 Lucas,Maurice 0.0214 0.0284 0.0037 0.0286 0.0180 0.0286 891 Lue,Tyronn 0.2451 0.0156 0.2431 0.0158 0.2138 0.0186 92 Lynch,George 0.3173 0.0195 0.3235 0.0196 0.3261 0.0198 18 Macauley,Ed (HOF) 0.5606 0.1796 0.2306 0.1428 0.5596 0.1805 195 Macy,Kyle 0.2128 0.0404 0.2274 0.0399 0.2272 0.0412 380 Madsen,Mark 0.0934 0.0278 0.0890 0.0280 0.0890 0.0280 36 Maggette,Corey 0.4566 0.0246 0.4587 0.0249 0.4450 0.0251 210 Magloire,Jamaal 0.2022 0.0196 0.2081 0.0198 0.2123 0.0200 410 Mahorn,Rick 0.0752 0.0162 0.0830 0.0163 0.0700 0.0163 538 Majerle,Dan 0.0058 0.0239 0.0051 0.0241 0.0117 0.0241 550 Malone,Jeff 0.0007 0.0300 0.0048 0.0303 0.0016 0.0302 334 Malone,Karl 0.1216 0.0568 0.1342 0.0573 0.1255 0.0572 243 Malone,Moses (HOF) 0.1791 0.0434 0.1905 0.0435 0.1804 0.0436 77 Manning,Danny 0.3636 0.0442 0.3609 0.0446 0.3614 0.0444 301 Maravich,Pete (HOF) 0.1410 0.0254 0.1396 0.0254 0.1449 0.0256 602 Marbury,Stephon 0.0222 0.0136 0.0169 0.0137 0.0280 0.0137 537 Marin,Jack 0.0060 0.0226 0.0375 0.0224 0.0044 0.0227 9 Marion,Shawn 0.6545 0.0336 0.6572 0.0339 0.6545 0.0338 787 Marshall,Donyell 0.1408 0.0131 0.1439 0.0132 0.1422 0.0131 411 Martin,Darrick 0.0749 0.0225 0.0735 0.0227 0.0784 0.0226 359 Martin,Kenyon 0.1084 0.0167 0.1066 0.0168 0.1221 0.0173 939 Martin,Slater (HOF) 0.4674 0.0877 0.4460 0.0867 0.4710 0.0882 181 Mashburn,Jamal 0.2317 0.0196 0.2336 0.0198 0.2249 0.0199 636 Mason,Anthony 0.0436 0.0280 0.0367 0.0282 0.0290 0.0288 385 Mason,Desmond 0.0874 0.0164 0.0923 0.0166 0.0875 0.0165 805 Massenburg,Tony 0.1538 0.0198 0.1649 0.0200 0.1554 0.0199 643 Matthews,Wes 0.0475 0.0224 0.0520 0.0225 0.0572 0.0227 776 Maxwell,Cedric 0.1337 0.0348 0.1720 0.0342 0.1364 0.0350 502 Maxwell,Vernon 0.0283 0.0261 0.0342 0.0262 0.0263 0.0262 915 Mayberry,Lee 0.3119 0.0270 0.3220 0.0272 0.3195 0.0273 456 McAdoo,Bob (HOF) 0.0535 0.0290 0.0225 0.0288 0.0524 0.0291 43 McCarty,Walter 0.4414 0.0298 0.4356 0.0300 0.4179 0.0315 164 McCloud,George 0.2534 0.0277 0.2501 0.0279 0.2581 0.0279 808 McCormick,Tim 0.1550 0.0323 0.1652 0.0325 0.1641 0.0327 838 McCray,Rodney 0.1795 0.0443 0.1656 0.0445 0.1989 0.0456 189 McDaniel,Xavier 0.2199 0.0126 0.2150 0.0127 0.2129 0.0128 590 McDyess,Antonio 0.0176 0.0176 0.0180 0.0177 0.0128 0.0177 309 McElroy,Jim 0.1358 0.0447 0.1402 0.0451 0.1434 0.0451 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 36 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 763 McGee,Mike 0.1235 0.0191 0.1168 0.0192 0.1153 0.0194 103 McGinnis,George 0.3027 0.0737 0.3192 0.0740 0.3078 0.0742 371 McGlocklin,Jon 0.0985 0.0285 0.0559 0.0279 0.1015 0.0287 158 McGrady,Tracy 0.2568 0.0304 0.2539 0.0307 0.2295 0.0327 781 McGuire,Dick (HOF) 0.1383 0.3708 0.2732 0.3353 0.1451 0.3728 457 McHale,Kevin (HOF) 0.0534 0.0908 0.1035 0.0908 0.0626 0.0915 215 McIlvaine,Jim 0.2003 0.0176 0.1960 0.0177 0.2002 0.0176 453 McInnis,Jeff 0.0542 0.0160 0.0581 0.0161 0.0604 0.0162 292 McKey,Derrick 0.1470 0.0295 0.1531 0.0297 0.1564 0.0299 725 McKie,Aaron 0.0981 0.0510 0.1080 0.0514 0.1033 0.0513 296 McKinney,Billy 0.1441 0.0327 0.1511 0.0329 0.1439 0.0328 834 McLemore,Mccoy 0.1755 0.0191 0.1969 0.0190 0.1739 0.0192 161 McMahon,Jack 0.2557 0.0231 0.0728 0.0107 0.2554 0.0232 104 McMillan,Nate 0.2998 0.0574 0.2933 0.0578 0.3068 0.0579 330 McMillen,Tom 0.1241 0.0249 0.1304 0.0248 0.1266 0.0250 267 McMillian,Jim 0.1617 0.0193 0.1748 0.0192 0.1591 0.0194 654 Meminger,Dean 0.0518 0.0152 0.0623 0.0152 0.0541 0.0153 400 Mengelt,John 0.0807 0.0254 0.0909 0.0244 0.0815 0.0255 798 Mercer,Ron 0.1500 0.0217 0.1570 0.0219 0.1509 0.0218 492 Meriweather,Joe 0.0345 0.0252 0.0249 0.0254 0.0302 0.0254 228 Meschery,Tom 0.1884 0.0413 0.2496 0.0248 0.1862 0.0415 874 Mihm,Chris 0.2162 0.0730 0.2109 0.0736 0.1778 0.0776 680 Mikan,George (HOF) 0.0705 0.0350 0.0982 0.0338 0.0701 0.0352 137 Mikkelsen,Vern (HOF) 0.2745 0.0458 0.2950 0.0453 0.2705 0.0461 17 Miles,Darius 0.5713 0.0724 0.5649 0.0730 0.5339 0.0768 471 Miles,Eddie 0.0475 0.0239 0.0764 0.0237 0.0453 0.0241 405 Miller,Andre 0.0777 0.0142 0.0794 0.0143 0.0698 0.0145 98 Miller,Brad 0.3090 0.0234 0.3172 0.0236 0.3167 0.0237 607 Miller,Mike 0.0283 0.0427 0.0275 0.0430 0.0291 0.0429 501 Miller,Oliver 0.0284 0.0191 0.0324 0.0193 0.0209 0.0194 374 Miller,Reggie 0.0961 0.0740 0.0873 0.0746 0.0960 0.0744 376 Mills,Chris 0.0953 0.0193 0.0895 0.0195 0.0882 0.0196 416 Mills,Terry 0.0717 0.0159 0.0692 0.0160 0.0700 0.0160 138 Ming,Yao 0.2736 0.0272 0.2727 0.0274 0.2761 0.0273 436 Mitchell,Mike 0.0614 0.0169 0.0731 0.0168 0.0595 0.0170 593 Mitchell,Sam 0.0188 0.0706 0.0264 0.0711 0.0418 0.0725 632 Mix,Steve 0.0413 0.0201 0.0299 0.0199 0.0436 0.0202 250 Mobley,Cuttino 0.1736 0.0172 0.1776 0.0173 0.1698 0.0173 258 Mohammed,Nazr 0.1708 0.0144 0.1734 0.0145 0.1587 0.0149 575 Mokeski,Paul 0.0066 0.0583 0.0238 0.0587 0.0027 0.0586 474 Moncrief,Sidney 0.0463 0.0932 0.0538 0.0938 0.0581 0.0940 773 Money,Eric 0.1312 0.0670 0.1345 0.0673 0.1346 0.0674 134 Monroe,Earl (HOF) 0.2770 0.0258 0.3040 0.0256 0.2744 0.0260 237 Montross,Eric 0.1819 0.0341 0.1883 0.0343 0.1750 0.0344 300 Moore,Johnny 0.1412 0.0612 0.1304 0.0608 0.1479 0.0617 402 Moore,Mikki 0.0794 0.0175 0.0805 0.0177 0.0792 0.0176 560 Moore,Otto 0.0012 0.0067 0.0064 0.0067 0.0006 0.0067 286 Morris,Chris 0.1496 0.0225 0.1475 0.0227 0.1512 0.0226 116 Mourning,Alonzo 0.2921 0.0201 0.2903 0.0202 0.2844 0.0203 369 Mueller,Erwin 0.0988 0.0191 0.0846 0.0192 0.0991 0.0192 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 37 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 15 Mullin,Chris 0.5824 0.0517 0.5946 0.0521 0.5707 0.0523 789 Mullins,Jeff 0.1433 0.0793 0.2489 0.0754 0.1463 0.0797 800 Murdock,Eric 0.1509 0.0192 0.1495 0.0194 0.1467 0.0193 852 Murphy,Calvin (HOF) 0.1918 0.2027 0.1893 0.2036 0.1957 0.2038 608 Murphy,Troy 0.0284 0.0527 0.0243 0.0532 0.0130 0.0537 62 Murray,Lamond 0.4032 0.0255 0.4034 0.0258 0.4081 0.0257 612 Murray,Tracy 0.0302 0.0191 0.0261 0.0193 0.0132 0.0200 101 Mutombo,Dikembe 0.3055 0.0339 0.2983 0.0342 0.3038 0.0341 522 Najera,Eduardo 0.0157 0.0212 0.0187 0.0213 0.0160 0.0242 836 Nance,Larry 0.1783 0.0237 0.1809 0.0239 0.1837 0.0239 497 Nash,Steve 0.0294 0.0372 0.0284 0.0375 0.0298 0.0374 711 Nater,Swen 0.0885 0.0268 0.0934 0.0258 0.0867 0.0269 268 Natt,Calvin 0.1611 0.0437 0.1558 0.0439 0.1582 0.0439 382 Naulls,Willie 0.0928 0.0185 0.1528 0.0172 0.0917 0.0186 274 Neal,Lloyd 0.1574 0.0740 0.2429 0.0717 0.1615 0.0744 885 Nealy,Ed 0.2407 0.0319 0.2504 0.0322 0.2500 0.0324 574 Nelson,Don 0.0062 0.0313 0.0376 0.0308 0.0069 0.0314 753 Nesterovic,Radoslav 0.1143 0.0156 0.1194 0.0157 0.1062 0.0158 555 Netolicky,Bob 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 394 Neumann,Paul 0.0825 0.0310 0.0547 0.0294 0.0806 0.0311 567 Newlin,Mike 0.0035 0.0771 0.0038 0.0778 0.0047 0.0775 201 Newman,Johnny 0.2085 0.0169 0.2087 0.0170 0.2143 0.0170 662 Nichols,Jack 0.0599 0.0107 0.0393 0.0107 0.0593 0.0108 74 Nimphius,Kurt 0.3741 0.0378 0.3810 0.0380 0.3743 0.0380 95 Nixon,Norm 0.3129 0.0537 0.3035 0.0541 0.3230 0.0542 404 Noble,Chuck 0.0790 0.0293 0.0038 0.0272 0.0768 0.0295 329 Norman,Ken 0.1258 0.0196 0.1259 0.0197 0.1255 0.0197 313 Norris,Moochie 0.1333 0.0233 0.1320 0.0235 0.1209 0.0238 517 Norwood,Willie 0.0179 0.0268 0.0052 0.0269 0.0162 0.0269 10 Nowitzki,Dirk 0.6418 0.0521 0.6444 0.0525 0.6281 0.0529 275 O Koren,Mike 0.1560 0.1907 0.2235 0.1909 0.1664 0.1919 450 O neal,jermaine 0.0550 0.0884 0.0543 0.0892 0.0211 0.0922 71 O neal,shaquille 0.3816 0.0530 0.3797 0.0535 0.3687 0.0538 124 Oakley,Charles 0.2867 0.0264 0.2961 0.0266 0.2845 0.0265 318 Odom,Lamar 0.1307 0.0468 0.1279 0.0472 0.1294 0.0471 663 Ohl,Don 0.0610 0.0685 0.0252 0.0659 0.0604 0.0688 637 Okur,Mehmet 0.0443 0.0214 0.0366 0.0216 0.0358 0.0217 5 Olajuwon,Hakeem (HOF) 0.8238 0.0742 0.8402 0.0748 0.8387 0.0752 481 Olberding,Mark 0.0417 0.0268 0.0475 0.0270 0.0374 0.0270 701 Ollie,Kevin 0.0816 0.0153 0.0848 0.0154 0.0716 0.0156 901 Olowokandi,Michael 0.2587 0.0470 0.2555 0.0474 0.2326 0.0492 344 Orr,Louis 0.1158 0.0651 0.1145 0.0655 0.1036 0.0659 473 Ostertag,Greg 0.0464 0.0159 0.0464 0.0161 0.0595 0.0165 414 Outlaw,Bo 0.0735 0.0083 0.0715 0.0083 0.0760 0.0083 876 Overton,Doug 0.2240 0.0282 0.2179 0.0284 0.2350 0.0287 611 Owens,Billy 0.0297 0.0291 0.0240 0.0294 0.0133 0.0301 651 Owens,Tom 0.0503 0.0429 0.0594 0.0432 0.0455 0.0432 850 Pack,Robert 0.1903 0.0143 0.1931 0.0145 0.1872 0.0144 719 Padgett,Scott 0.0934 0.0120 0.0907 0.0121 0.0936 0.0121 820 Palacio,Milt 0.1636 0.0084 0.1644 0.0085 0.1689 0.0085 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 38 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 159 Parish,Robert (HOF) 0.2567 0.0705 0.2602 0.0711 0.2529 0.0709 948 Parker,Sonny 0.8629 0.1199 0.8795 0.1207 0.8620 0.1205 3 Parker,Tony 1.1713 0.1053 1.1741 0.1061 1.1504 0.1070 886 Parks,Cherokee 0.2411 0.0146 0.2367 0.0148 0.2354 0.0148 585 Patterson,Ruben 0.0142 0.0148 0.0143 0.0149 0.0121 0.0148 945 Paultz,Billy 0.5937 0.1566 0.5995 0.1580 0.5863 0.1575 811 Paxson,Jim 0.1561 0.0360 0.1658 0.0363 0.1555 0.0362 925 Paxson,John 0.3606 0.0471 0.3663 0.0474 0.3693 0.0475 57 Payton,Gary 0.4173 0.0282 0.4163 0.0284 0.4097 0.0285 221 Peeler,Anthony 0.1940 0.0244 0.1976 0.0246 0.2054 0.0249 63 Perdue,Will 0.4015 0.0382 0.4082 0.0385 0.3996 0.0384 736 Perkins,Sam 0.1047 0.0327 0.0972 0.0329 0.1125 0.0330 690 Perry,Curtis 0.0752 0.0232 0.0717 0.0233 0.0803 0.0234 703 Perry,Elliot 0.0848 0.0230 0.0899 0.0231 0.0944 0.0233 75 Perry,Tim 0.3737 0.0530 0.3633 0.0534 0.3555 0.0543 913 Person,Chuck 0.2833 0.0288 0.2860 0.0290 0.2974 0.0295 892 Person,Wesley 0.2460 0.0200 0.2545 0.0201 0.2563 0.0204 746 Petersen,Jim 0.1101 0.0560 0.1198 0.0564 0.1080 0.0562 354 Peterson,Morris 0.1092 0.0147 0.1113 0.0148 0.1053 0.0148 815 Petrie,Geoff 0.1591 0.0384 0.1561 0.0382 0.1617 0.0386 532 Pettit,Bob (HOF) 0.0086 0.1816 0.3451 0.1436 0.0022 0.1826 225 Phillip,Andy (HOF) 0.1922 0.1135 0.1991 0.1092 0.1944 0.1141 480 Phills,Bobby 0.0422 0.0603 0.0582 0.0608 0.0168 0.0625 370 Piatkowski,Eric 0.0986 0.0583 0.0995 0.0588 0.0810 0.0595 53 Pierce,Paul 0.4266 0.0242 0.4325 0.0244 0.4356 0.0246 687 Pierce,Ricky 0.0736 0.0319 0.0906 0.0321 0.0857 0.0325 352 Pinckney,Ed 0.1100 0.0186 0.1114 0.0187 0.1056 0.0187 163 Piontek,Dave 0.2543 0.0248 0.2908 0.0231 0.2521 0.0249 765 Pippen,Scottie 0.1240 0.0505 0.1316 0.0509 0.1292 0.0508 19 Pollard,Jim (HOF) 0.5529 0.0622 0.5425 0.0616 0.5539 0.0625 188 Pollard,Scot 0.2203 0.0266 0.2233 0.0268 0.2414 0.0280 864 Polynice,Olden 0.2015 0.0229 0.2016 0.0231 0.2184 0.0239 889 Poquette,Ben 0.2430 0.0262 0.2790 0.0257 0.2452 0.0263 660 Porter,Howard 0.0569 0.0277 0.0963 0.0274 0.0588 0.0279 679 Porter,Kevin 0.0697 0.0223 0.0715 0.0224 0.0713 0.0224 672 Porter,Terry 0.0655 0.0436 0.0717 0.0440 0.0751 0.0441 368 Posey,James 0.0988 0.0143 0.0994 0.0144 0.0890 0.0147 365 Potapenko,Vitaly 0.1008 0.0223 0.1053 0.0225 0.1077 0.0226 666 Pressey,Paul 0.0631 0.0749 0.0714 0.0755 0.0630 0.0753 652 Price,Brent 0.0509 0.0184 0.0520 0.0186 0.0500 0.0185 734 Price,Jim 0.1039 0.0156 0.1127 0.0157 0.1056 0.0157 117 Price,Mark 0.2921 0.0778 0.2941 0.0785 0.2916 0.0782 12 Prince,Tayshaun 0.6202 0.0483 0.6290 0.0487 0.6120 0.0488 761 Przybilla,Joel 0.1214 0.0242 0.1147 0.0244 0.1082 0.0248 430 Radmanovic,Vladimir 0.0650 0.0425 0.0643 0.0428 0.0615 0.0427 733 Rambis,Kurt 0.1032 0.0235 0.0926 0.0236 0.1065 0.0237 923 Ramsey,Frank (HOF) 0.3541 0.0467 0.2422 0.0427 0.3522 0.0469 656 Randolph,Zachary 0.0529 0.0129 0.0509 0.0130 0.0462 0.0131 802 Ransey,Kelvin 0.1525 0.0307 0.1722 0.0308 0.1551 0.0309 391 Rasmussen,Blair 0.0829 0.0234 0.0884 0.0236 0.0799 0.0235 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 39 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 829 Ratliff,Theo 0.1703 0.0179 0.1673 0.0180 0.1699 0.0180 279 Ray,Clifford 0.1536 0.0333 0.1917 0.0325 0.1538 0.0335 347 Redd,Michael 0.1129 0.0219 0.1107 0.0221 0.0932 0.0232 862 Reed,Hub 0.2003 0.0231 0.1664 0.0218 0.2011 0.0232 493 Reed,Willis (HOF) 0.0340 0.0300 0.0340 0.0303 0.0353 0.0302 182 Reid,Don 0.2313 0.0427 0.2226 0.0430 0.2201 0.0433 364 Reid,J.r. 0.1022 0.0411 0.1030 0.0415 0.1089 0.0415 408 Reid,Robert 0.0763 0.0480 0.0743 0.0484 0.0855 0.0485 193 Restani,Kevin 0.2160 0.0303 0.2426 0.0291 0.2186 0.0305 866 Reynolds,Jerry 0.2072 0.0312 0.2153 0.0313 0.1972 0.0316 310 Rice,Glen 0.1350 0.0247 0.1362 0.0249 0.1430 0.0250 333 Richardson,Clint 0.1224 0.0468 0.1021 0.0468 0.1137 0.0473 508 Richardson,Jason 0.0257 0.0099 0.0279 0.0100 0.0273 0.0100 177 Richardson,Micheal Ray 0.2423 0.0240 0.2514 0.0242 0.2443 0.0242 918 Richardson,Pooh 0.3284 0.0673 0.3173 0.0678 0.3193 0.0679 705 Richardson,Quentin 0.0859 0.0201 0.0848 0.0203 0.0844 0.0202 741 Richmond,Mitch 0.1073 0.0219 0.1005 0.0221 0.1125 0.0221 897 Rider,Isaiah 0.2534 0.0171 0.2528 0.0173 0.2470 0.0173 260 Riordan,Mike 0.1682 0.0836 0.2262 0.0830 0.1619 0.0841 809 Risen,Arnie (HOF) 0.1553 0.0801 0.0730 0.0782 0.1535 0.0805 70 Rivers,Doc 0.3874 0.0322 0.3894 0.0324 0.3891 0.0324 774 Roberson,Rick 0.1313 0.0143 0.1192 0.0143 0.1340 0.0144 540 Roberts,Fred 0.0054 0.0124 0.0082 0.0124 0.0022 0.0124 203 Robertson,Alvin 0.2050 0.0275 0.2130 0.0277 0.2091 0.0277 28 Robertson,Oscar (HOF) 0.4885 0.0469 0.5226 0.0458 0.4843 0.0472 909 Robey,Rick 0.2786 0.0428 0.2715 0.0428 0.2793 0.0430 187 Robinson,Clifford R. 0.2218 0.0364 0.2200 0.0367 0.2289 0.0367 478 Robinson,Clifford T. 0.0435 0.0507 0.0305 0.0504 0.0333 0.0512 109 Robinson,David 0.2965 0.0695 0.3008 0.0700 0.3048 0.0701 261 Robinson,Flynn 0.1676 0.0181 0.1919 0.0179 0.1648 0.0182 120 Robinson,Glenn 0.2895 0.0251 0.2917 0.0253 0.2657 0.0269 677 Robinson,Truck 0.0680 0.0157 0.0684 0.0158 0.0678 0.0158 577 Robinzine,Bill 0.0078 0.0279 0.0038 0.0277 0.0120 0.0281 786 Robisch,Dave 0.1402 0.0432 0.1343 0.0429 0.1428 0.0434 547 Rodgers,Guy 0.0016 0.0351 0.0462 0.0290 0.0008 0.0353 828 Rodman,Dennis 0.1702 0.1046 0.1719 0.1055 0.1625 0.1052 796 Rogers,Rodney 0.1490 0.0197 0.1498 0.0199 0.1543 0.0199 41 Rollins,Tree 0.4432 0.0654 0.4363 0.0654 0.4538 0.0661 865 Rooks,Sean 0.2055 0.0154 0.2077 0.0156 0.2141 0.0157 605 Rose,Jalen 0.0256 0.0154 0.0263 0.0155 0.0189 0.0156 420 Rose,Malik 0.0694 0.0414 0.0607 0.0418 0.0724 0.0417 156 Roundfield,Dan 0.2588 0.0207 0.2539 0.0207 0.2556 0.0209 888 Rowe,Curtis 0.2426 0.0278 0.1944 0.0272 0.2411 0.0279 133 Royal,Donald 0.2772 0.0248 0.2799 0.0249 0.2875 0.0253 506 Ruffin,Michael 0.0271 0.0175 0.0281 0.0176 0.0301 0.0176 174 Rule,Bob 0.2457 0.0289 0.2435 0.0276 0.2439 0.0290 4 Russell,Bill (HOF) 1.1398 0.7621 0.5608 0.6616 1.1353 0.7659 49 Russell,Bryon 0.4348 0.0242 0.4460 0.0244 0.4148 0.0255 658 Russell,Campy 0.0538 0.0538 0.0654 0.0540 0.0583 0.0541 427 Russell,Cazzie 0.0659 0.0202 0.0811 0.0199 0.0645 0.0203 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 40 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 207 Sabonis,Arvydas 0.2029 0.1159 0.2108 0.1169 0.2001 0.1165 366 Salley,John 0.1002 0.0395 0.1000 0.0398 0.0884 0.0401 635 Salmons,John 0.0422 0.0158 0.0457 0.0159 0.0361 0.0160 835 Sampson,Ralph 0.1763 0.0780 0.1534 0.0785 0.1635 0.0789 287 Sanders,Mike 0.1494 0.0259 0.1445 0.0261 0.1516 0.0261 234 Sanders,Thomas 0.1839 0.0263 0.2262 0.0259 0.1819 0.0264 788 Sauldsberry,Woody 0.1432 0.0118 0.1779 0.0109 0.1425 0.0119 596 Schayes,Danny 0.0198 0.0248 0.0063 0.0250 0.0243 0.0250 6 Schayes,Dolph (HOF) 0.7928 0.2666 0.6798 0.2639 0.7785 0.2686 570 Schlueter,Dale 0.0053 0.0110 0.0334 0.0104 0.0068 0.0111 356 Schrempf,Detlef 0.1089 0.0340 0.1003 0.0342 0.1169 0.0343 379 Scott,Alvin 0.0939 0.0860 0.1057 0.0853 0.0813 0.0869 230 Scott,Byron 0.1867 0.0508 0.1807 0.0511 0.1946 0.0512 110 Scott,Charlie 0.2957 0.0243 0.3016 0.0241 0.2961 0.0244 325 Scott,Dennis 0.1273 0.0158 0.1340 0.0159 0.1224 0.0159 832 Scott,Ray 0.1733 0.0200 0.2037 0.0198 0.1746 0.0201 455 Sealy,Malik 0.0537 0.0169 0.0658 0.0170 0.0455 0.0172 623 Sears,Ken 0.0380 0.0259 0.0960 0.0242 0.0372 0.0260 571 Seikaly,Rony 0.0059 0.0548 0.0124 0.0552 0.0066 0.0555 728 Selvy,Frank 0.0989 0.0220 0.0654 0.0217 0.1017 0.0222 1 Senesky,George 6.0692 114.5482 0.1990 24.7607 6.1584 115.1403 943 Seymour,Paul 0.5314 0.4589 0.5079 0.4557 0.5254 0.4613 582 Share,Charlie 0.0112 0.1277 0.1392 0.1217 0.0110 0.1284 20 Sharman,Bill (HOF) 0.5377 0.1629 0.4833 0.1627 0.5327 0.1638 298 Shaw,Brian 0.1425 0.0146 0.1410 0.0147 0.1392 0.0147 232 Shelton,Lonnie 0.1845 0.0159 0.2020 0.0160 0.1842 0.0160 125 Short,Purvis 0.2856 0.0601 0.3187 0.0602 0.3052 0.0615 665 Shue,Gene 0.0622 0.0213 0.0003 0.0195 0.0604 0.0214 209 Sichting,Jerry 0.2022 0.0262 0.1889 0.0263 0.2047 0.0263 931 Siegfried,Larry 0.3956 0.0537 0.2982 0.0508 0.3914 0.0541 504 Sikma,Jack 0.0277 0.0469 0.0368 0.0473 0.0188 0.0474 589 Silas,James 0.0174 0.0389 0.0125 0.0390 0.0149 0.0391 357 Silas,Paul 0.1087 0.0109 0.1075 0.0109 0.1107 0.0110 54 Simmons,Connie 0.4262 0.0625 0.4528 0.0538 0.4246 0.0628 895 Simmons,Lionel 0.2506 0.1354 0.2614 0.1365 0.2259 0.1378 113 Skiles,Scott 0.2946 0.0296 0.2979 0.0297 0.3029 0.0299 199 Skinner,Brian 0.2092 0.0115 0.2069 0.0116 0.1955 0.0121 153 Sloan,Jerry 0.2609 0.0623 0.3593 0.0591 0.2619 0.0626 32 Smith,Adrian 0.4792 0.0454 0.4334 0.0444 0.4820 0.0457 150 Smith,Bingo 0.2625 0.0376 0.3006 0.0370 0.2514 0.0382 536 Smith,Charles 0.0072 0.0363 0.0077 0.0366 0.0052 0.0365 928 Smith,Derek 0.3741 0.0464 0.3987 0.0465 0.3682 0.0467 290 Smith,Don 0.1487 0.0219 0.1260 0.0217 0.1477 0.0220 257 Smith,Elmore 0.1710 0.0221 0.1828 0.0222 0.1727 0.0222 549 Smith,Greg 0.0010 0.0191 0.0055 0.0192 0.0029 0.0192 584 Smith,Joe 0.0125 0.0156 0.0160 0.0157 0.0038 0.0164 807 Smith,Kenny 0.1547 0.0247 0.1616 0.0249 0.1543 0.0248 34 Smith,Larry 0.4662 0.0466 0.4514 0.0469 0.4477 0.0478 229 Smith,Michael 0.1876 0.0201 0.1992 0.0202 0.1889 0.0202 29 Smith,Phil 0.4858 0.0368 0.4884 0.0364 0.4858 0.0370 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 41 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 423 Smith,Randy 0.0685 0.0163 0.0669 0.0161 0.0655 0.0164 295 Smith,Steve 0.1452 0.0200 0.1423 0.0201 0.1456 0.0201 671 Smith,Tony 0.0649 0.0409 0.0626 0.0412 0.0805 0.0418 393 Smits,Rik 0.0826 0.0964 0.0801 0.0973 0.0743 0.0971 735 Snow,Eric 0.1044 0.0166 0.1077 0.0167 0.1063 0.0166 518 Snyder,Dick 0.0179 0.0168 0.0384 0.0163 0.0147 0.0169 282 Sobers,Ricky 0.1523 0.0280 0.1433 0.0281 0.1556 0.0282 748 Sparrow,Rory 0.1123 0.0260 0.0946 0.0261 0.1153 0.0261 720 Spencer,Felton 0.0939 0.0127 0.0956 0.0128 0.0956 0.0128 527 Sprewell,Latrell 0.0110 0.0235 0.0087 0.0237 0.0023 0.0238 842 Stackhouse,Jerry 0.1845 0.0205 0.1965 0.0206 0.1926 0.0208 597 Stallworth,Dave 0.0200 0.0188 0.0474 0.0187 0.0195 0.0189 277 Starks,John 0.1545 0.0447 0.1573 0.0451 0.1714 0.0458 673 Steele,Larry 0.0656 0.0520 0.0996 0.0521 0.0688 0.0523 578 Stevenson,Deshawn 0.0079 0.0096 0.0060 0.0097 0.0086 0.0096 276 Stipanovich,Steve 0.1551 0.0311 0.1642 0.0313 0.1490 0.0314 326 Stith,Bryant 0.1267 0.0284 0.1235 0.0286 0.1308 0.0285 599 Stockton,John 0.0209 0.0644 0.0551 0.0646 0.0217 0.0647 499 Stojakovic,Peja 0.0289 0.0233 0.0255 0.0235 0.0482 0.0245 491 Stoudamire,Damon 0.0365 0.0245 0.0396 0.0248 0.0366 0.0247 514 Strickland,Erick 0.0203 0.0206 0.0212 0.0208 0.0163 0.0208 683 Strickland,Rod 0.0726 0.0266 0.0749 0.0268 0.0674 0.0268 830 Strong,Derek 0.1718 0.0285 0.1678 0.0287 0.2008 0.0311 933 Sundvold,Jon 0.4097 0.0540 0.4479 0.0540 0.4198 0.0546 358 Sura,Bob 0.1086 0.0201 0.1093 0.0202 0.1040 0.0202 930 Swift,Stromile 0.3887 0.0229 0.3859 0.0231 0.3849 0.0230 475 Szczerbiak,Wally 0.0460 0.0317 0.0481 0.0320 0.0223 0.0335 797 Taylor,Maurice 0.1495 0.0153 0.1475 0.0154 0.1451 0.0154 443 Teagle,Terry 0.0597 0.0355 0.0602 0.0357 0.0629 0.0357 272 Terry,Jason 0.1594 0.0251 0.1602 0.0254 0.1575 0.0253 629 Theus,Reggie 0.0392 0.0288 0.0618 0.0289 0.0389 0.0290 8 Thomas,Isiah (HOF) 0.7300 0.0647 0.7155 0.0650 0.7324 0.0650 775 Thomas,Kenny 0.1336 0.0282 0.1317 0.0285 0.1175 0.0291 183 Thomas,Kurt 0.2310 0.0329 0.2377 0.0332 0.2355 0.0331 782 Thomas,Tim 0.1385 0.0164 0.1426 0.0165 0.1366 0.0164 937 Thompson,David (HOF) 0.4606 0.0941 0.5142 0.0929 0.4509 0.0948 14 Thompson,Lasalle 0.5914 0.0825 0.6388 0.0824 0.5964 0.0829 288 Thompson,Mychal 0.1490 0.0328 0.1641 0.0330 0.1476 0.0329 907 Thorn,Rod 0.2727 0.0248 0.3188 0.0204 0.2730 0.0250 707 Thorpe,Otis 0.0864 0.0335 0.0867 0.0338 0.0946 0.0339 664 Threatt,Sedale 0.0618 0.0151 0.0689 0.0152 0.0564 0.0152 184 Thurmond,Nate (HOF) 0.2289 0.0219 0.2404 0.0174 0.2283 0.0220 176 Tisdale,Wayman 0.2428 0.0405 0.2548 0.0408 0.2482 0.0408 102 Tomjanovich,Rudy 0.3034 0.1113 0.3113 0.1118 0.3040 0.1119 128 Toney,Andrew 0.2829 0.0614 0.3186 0.0607 0.2877 0.0618 859 Traylor,Robert 0.1966 0.0180 0.1963 0.0182 0.1954 0.0181 495 Trent,Gary 0.0307 0.0177 0.0374 0.0178 0.0255 0.0178 576 Tresvant,John 0.0068 0.0435 0.1027 0.0402 0.0057 0.0437 898 Tripucka,Kelly 0.2545 0.0537 0.2493 0.0541 0.2569 0.0540 131 Tucker,Trent 0.2792 0.0777 0.2817 0.0783 0.2967 0.0790 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 42 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 31 Turkoglu,Hidayet 0.4841 0.0141 0.4895 0.0143 0.4784 0.0143 500 Turner,Elston 0.0285 0.0237 0.0409 0.0238 0.0334 0.0239 227 Turner,Jeff 0.1886 0.0493 0.2011 0.0497 0.2091 0.0508 938 Twyman,Jack (HOF) 0.4629 0.0618 0.4677 0.0612 0.4688 0.0622 854 Tyler,Terry 0.1935 0.0294 0.1722 0.0294 0.1951 0.0295 24 Unseld,Wes (HOF) 0.5081 0.0369 0.5210 0.0371 0.5090 0.0370 259 Valentine,Darnell 0.1692 0.0237 0.1825 0.0238 0.1644 0.0239 516 Van Arsdale,Dick 0.0185 0.0286 0.0049 0.0288 0.0195 0.0288 461 Van Arsdale,Tom 0.0523 0.0208 0.0807 0.0206 0.0512 0.0209 489 Van Exel,Nick 0.0369 0.0209 0.0397 0.0210 0.0466 0.0212 764 Vanbredakolff,Jan 0.1240 0.1376 0.1059 0.1380 0.1176 0.1384 726 Vandeweghe,Kiki 0.0987 0.0417 0.1092 0.0421 0.0971 0.0420 586 Vanhorn,Keith 0.0168 0.0131 0.0184 0.0132 0.0222 0.0132 562 Vanlier,Norm 0.0020 0.0270 0.0564 0.0262 0.0027 0.0272 466 Vaughn,Jacque 0.0504 0.0075 0.0470 0.0076 0.0477 0.0076 793 Vaught,Loy 0.1465 0.0297 0.1463 0.0300 0.1314 0.0305 377 Vincent,Jay 0.0944 0.0176 0.0987 0.0177 0.1014 0.0178 947 Voskuhl,Jake 0.7531 0.2084 0.7475 0.2102 0.7833 0.2121 676 Vranes,Danny 0.0676 0.0471 0.0452 0.0474 0.0658 0.0474 814 Walk,Neal 0.1573 0.0255 0.1334 0.0251 0.1638 0.0257 858 Walker,Antoine 0.1960 0.0135 0.1935 0.0136 0.1593 0.0175 80 Walker,Chet 0.3407 0.0448 0.2815 0.0423 0.3351 0.0451 655 Walker,Darrell 0.0526 0.0185 0.0524 0.0186 0.0508 0.0186 264 Walker,Foots 0.1637 0.0488 0.1243 0.0482 0.1686 0.0491 433 Walker,Jimmy 0.0636 0.0135 0.0472 0.0133 0.0630 0.0136 839 Walker,Kenny 0.1804 0.0600 0.1746 0.0605 0.1962 0.0610 616 Walker,Samaki 0.0334 0.0135 0.0303 0.0136 0.0372 0.0136 336 Walker,Wally 0.1195 0.0492 0.1134 0.0496 0.1238 0.0495 299 Wallace,Ben 0.1420 0.0232 0.1432 0.0233 0.1345 0.0234 216 Wallace,Rasheed 0.1996 0.0473 0.2068 0.0477 0.2061 0.0476 880 Walton,Bill (HOF) 0.2290 0.0868 0.2343 0.0865 0.2352 0.0874 386 Wanzer,Bobby (HOF) 0.0872 2.8034 0.1940 2.8229 0.0595 2.8197 896 Ward,Charlie 0.2522 0.0518 0.2542 0.0522 0.2573 0.0521 790 Warner,Cornell 0.1445 0.0193 0.1424 0.0193 0.1471 0.0194 403 Washington,Jim 0.0792 0.0213 0.0125 0.0196 0.0764 0.0214 919 Washington,Kermit 0.3314 0.0409 0.3276 0.0413 0.3407 0.0414 510 Watson,Earl 0.0225 0.0130 0.0234 0.0131 0.0361 0.0136 76 Watts,Slick 0.3706 0.0242 0.3708 0.0244 0.3734 0.0244 435 Weatherspoon,Clarence 0.0619 0.0146 0.0609 0.0147 0.0620 0.0147 67 Weatherspoon,Nick 0.3937 0.0238 0.3882 0.0237 0.3936 0.0239 780 Webb,Spud 0.1361 0.0302 0.1286 0.0305 0.1227 0.0309 812 Webber,Chris 0.1564 0.0269 0.1562 0.0271 0.1568 0.0270 619 Webster,Marvin 0.0355 0.0138 0.0186 0.0136 0.0378 0.0138 127 Wedman,Scott 0.2830 0.0262 0.2952 0.0263 0.2839 0.0264 490 Weiss,Bob 0.0369 0.0386 0.0070 0.0367 0.0390 0.0388 704 Wells,Bonzi 0.0858 0.0328 0.0899 0.0330 0.0930 0.0331 173 Wennington,Bill 0.2459 0.0363 0.2461 0.0366 0.2419 0.0365 339 Wesley,David 0.1180 0.0362 0.1038 0.0363 0.1316 0.0369 881 Wesley,Walt 0.2311 0.0171 0.2439 0.0163 0.2293 0.0172 82 West,Doug 0.3335 0.0591 0.3275 0.0596 0.3472 0.0600 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
Table 11: Results 43 cut 3.1 cut 3.0 cut 3.3 Rank Name β St.Err. β St. Err. β St. Err. 362 West,Jerry (HOF) 0.1056 0.0487 0.0769 0.0487 0.1026 0.0490 639 West,Mark 0.0463 0.0567 0.0563 0.0571 0.0710 0.0587 431 Westphal,Paul 0.0650 0.0193 0.0866 0.0193 0.0619 0.0194 213 White,Jojo 0.2011 0.0666 0.1192 0.0648 0.1928 0.0671 837 Whitehead,Jerome 0.1786 0.0210 0.1760 0.0211 0.1795 0.0211 162 Whitney,Chris 0.2546 0.0469 0.2594 0.0473 0.2344 0.0483 107 Wicks,Sidney 0.2982 0.0219 0.2789 0.0219 0.2990 0.0220 699 Wilkens,Lenny (HOF) 0.0814 0.0311 0.0662 0.0313 0.0810 0.0313 542 Wilkerson,Bob 0.0045 0.0136 0.0005 0.0136 0.0045 0.0136 795 Wilkes,Jamaal 0.1480 0.0438 0.1358 0.0434 0.1519 0.0441 908 Wilkins,Dominique (HOF) 0.2771 0.0821 0.2933 0.0825 0.2738 0.0825 396 Wilkins,Gerald 0.0817 0.0249 0.0752 0.0251 0.0824 0.0250 667 Wilkins,Jeff 0.0633 0.1054 0.0327 0.1055 0.0459 0.1068 591 Williams,Aaron 0.0187 0.0183 0.0172 0.0185 0.0277 0.0187 337 Williams,Alvin 0.1183 0.0557 0.1143 0.0561 0.0955 0.0574 220 Williams,Buck 0.1942 0.0495 0.1968 0.0499 0.1808 0.0503 739 Williams,Eric 0.1055 0.0391 0.0986 0.0394 0.1393 0.0426 248 Williams,Gus 0.1751 0.0222 0.1442 0.0216 0.1742 0.0223 496 Williams,Herb 0.0294 0.0367 0.0403 0.0370 0.0274 0.0369 289 Williams,Hotrod 0.1487 0.1107 0.1644 0.1114 0.1530 0.1113 44 Williams,Jason 0.4404 0.0273 0.4405 0.0276 0.4159 0.0292 271 Williams,Jayson 0.1598 0.0546 0.1467 0.0550 0.1448 0.0555 883 Williams,Jerome 0.2367 0.0269 0.2370 0.0271 0.2271 0.0273 825 Williams,John 0.1693 0.0335 0.1720 0.0337 0.1652 0.0337 375 Williams,Michael 0.0958 0.0156 0.1004 0.0157 0.0953 0.0157 694 Williams,Monty 0.0786 0.0343 0.0786 0.0346 0.0814 0.0345 505 Williams,Nate 0.0274 0.0121 0.0204 0.0122 0.0224 0.0123 483 Williams,Ray 0.0402 0.0216 0.0266 0.0218 0.0387 0.0217 849 Williams,Reggie 0.1896 0.0622 0.1701 0.0626 0.1887 0.0625 459 Williams,Ron 0.0524 0.0357 0.0368 0.0355 0.0539 0.0359 716 Williams,Scott 0.0906 0.0183 0.0944 0.0185 0.0979 0.0186 85 Williams,Walt 0.3295 0.0180 0.3298 0.0181 0.3190 0.0184 714 Williamson,Corliss 0.0892 0.0125 0.0865 0.0126 0.0858 0.0126 533 Willis,Kevin 0.0081 0.0167 0.0059 0.0168 0.0045 0.0168 548 Willoughby,Bill 0.0012 0.0318 0.0074 0.0320 0.0047 0.0320 622 Wilson,George 0.0370 0.0243 0.0255 0.0236 0.0399 0.0244 285 Winfield,Lee 0.1505 0.0237 0.1516 0.0239 0.1554 0.0239 750 Wingate,David 0.1127 0.0206 0.1122 0.0208 0.1065 0.0208 620 Winters,Brian 0.0358 0.0547 0.0486 0.0551 0.0347 0.0550 737 Wittman,Randy 0.1048 0.0450 0.0930 0.0452 0.1064 0.0452 610 Wolf,Joe 0.0297 0.0144 0.0343 0.0145 0.0254 0.0145 614 Wood,Al 0.0328 0.0202 0.0248 0.0203 0.0316 0.0203 440 Wood,David 0.0605 0.0200 0.0547 0.0201 0.0666 0.0202 744 Woodson,Mike 0.1090 0.0351 0.1211 0.0354 0.1102 0.0353 792 Woolridge,Orlando 0.1459 0.0124 0.1487 0.0125 0.1498 0.0125 262 Worthy,James (HOF) 0.1674 0.0405 0.1630 0.0408 0.1623 0.0407 756 Wright,Lorenzen 0.1159 0.0252 0.1204 0.0254 0.1245 0.0256 198 Yardley,George (HOF) 0.2097 0.0515 0.1999 0.0518 0.2097 0.0518 674 Young,Danny 0.0667 0.0141 0.0656 0.0143 0.0608 0.0143 C 3.6232 6.7136 3.3707 0.9360 0.9392 0.2885 *** : significant at 1 percent level ** : significant at 5 percent level * : significant at 10 percent level
HHL-Arbeitspapiere / HHL Working Papers 102 Scherzer, Falk (2010) On the Value of Individual Athletes in Team Sports 101 Wulf, Torsten; Brands, Christian; Meißner, Philip (2010) A Scenario-based Approach to Strategic Planning: Tool Description 360 Stakeholder Feedback 100 Viellechner, Oliver; Wulf, Torsten (2010) Incumbent Inertia upon Disruptive Change in the Airline Industry: Causal Factors for Routine Rigidity and Top Management Moderators 99 Wulf, Torsten; Meißner, Philip; Bernewitz, Friedrich Frhr. von (2010) Future Scenarios for German Photovoltaic Industry 98 Wulf, Torsten; Meißner, Philip; Stubner, Stephan (2010) A Scenario-based Approach to Strategic Planning Integrating Planning and Process Perspective of Strategy 97 Wulf, Torsten; Stubner, Stephan; Blarr, W. Henning; Lindow, Corinna (2010) Erfolgreich bleiben in der Krise 96 Wulf, Torsten; Stubner, Stephan (2010) Unternehmernachfolge in Familienunternehmen Ein Untersuchungsmodell zur Analyse von Problemfeldern bei der Übergabe der Führungsrolle 95 Zülch, Henning; Pronobis, Paul (2010) The Predictive Power of Comprehensive Income and Its Individual Components under IFRS 94 Zülch, Henning; Hoffmann, Sebastian (2010) Lobbying on Accounting Standard Setting in a Parliamentary Environment A Qualitative Approach 93 Hausladen, Iris; Porzig, Nicole; Reichert, Melanie (2010) Nachhaltige Handels- und Logistikstrukturen für die Bereitstellung regionaler Produkte: Situation und Perspektiven 92 La Mura, Pierfrancesco; Rapp, Marc Steffen; Schwetzler, Bernard; Wilms, Andreas (2009) The Certification Hypothesis of Fairness Opinions 91 La Mura, Pierfrancesco (2009) Expected Utility of Final Wealth and the Rabin Anomaly 90 Thürbach, Kai (2009) Fallstudie sekretaria - Vom New Economy-Internet-Startup zum Old Economy-Verlagsunternehmen
89 Wulf, Torsten; Stubner, Stephan; Blarr, W. Henning (2010) Ambidexterity and the Concept of Fit in Strategic Management Which Better Predicts Success? 88 Wulf, Torsten; Stubner, Stephan; Miksche, Jutta; Roleder, Kati (2010) Performance over the CEO Lifecycle A Differentiated Analysis of Short and Long Tenured CEOs 87 Wulf, Torsten; Stubner, Stephan; Landau, Christian; Gietl, Robert (2010) Private Equity and Family Business Can Private Equity Investors Add to the Success of Formerly Owned Family Firms? 86 Wulf, Torsten; Stubner, Stephan (2008) Executive Succession and Firm Performance the Role of Position-specific Skills 85 Wulf, Torsten; Stubner, Stephan (2008) Unternehmernachfolge in Familienunternehmen Untersuchungsmodell zur Analyse von Problemfeldern bei der Übergabe der Führungsrolle 84 Wulf, Torsten; Stubner, Stephan (2008) Executive Departure Following Acquisitions in Germany an Empirical Analysis of Its Antecedents and Consequences 83 Zülch, Henning; Gebhardt, Ronny (2008) Politische Ökonomie der Rechnungslegung - Empirische Ergebnisse und kritische Würdigung des Forschungsansatzes 82 Zülch, Henning; Löw, Edgar; Burghardt, Stephan (2008) Zur Bedeutung von IFRS-Abschlüssen bei der Kreditvergabe von Banken an mittelständische Unternehmen 81 Suchanek, Andreas (2007) Die Relevanz der Unternehmensethik im Rahmen der Betriebswirtschaftslehre 80 Kirchgeorg, Manfred; Jung, Kathrin (2007) User Behavior in Second Life: an Empirical Study Analysis and Its Implications for Marketing Practice 79 Freundt, Tjark (2007) Neurobiologische Erklärungsbeiträge zur Struktur und Dynamik des Markenwissens 78 Wuttke, Martina (2007) Analyse der Markteintrittsstrategien chinesischer Unternehmen in Mitteldeutschland am Beispiel von chinesischen Unternehmen im MaxicoM in Leipzig 77 La Mura, Pierfrancesco; Swiatczak, Lukasz (2007) Markovian Entanglement Networks 76 Suchanek, Andreas (2007) Corporate Responsibility in der pharmazeutischen Industrie 75 Möslein, Kathrin; Huff, Anne Sigismund (2006) Management Education and Research in Germany
74 Kirchgeorg, Manfred; Günther, Elmar (2006) Employer Brands zur Unternehmensprofilierung im Personalmarkt : eine Analyse der Wahrnehmung von Unternehmensmarken auf der Grundlage einer deutschlandweiten Befragung von High Potentials 73 Vilks, Arnis (2006) Logic, Game Theory, and the Real World 72 La Mura, Pierfrancesco; Olschewski, Guido (2006) Non-Dictatorial Social Choice through Delegation 71 Kirchgeorg, Manfred; Springer, Christiane (2006) UNIPLAN Live Trends 2006 : Steuerung des Kommunikationsmix im Kundenbeziehungszyklus ; eine branchenübergreifende Befragung von Marketingentscheidern unter besonderer Berücksichtigung der Live Communication. 2., erw. Aufl. 70 Reichwald, Ralf; Möslein, Kathrin (2005) Führung und Führungssysteme 69 Suchanek, Andreas (2005) Is Profit Maximization the Social Responsibility of Business? Milton Friedman and Business Ethics 68 La Mura, Pierfrancesco (2005) Decision Theory in the Presence of Uncertainty and Risk 67 Kirchgeorg, Manfred; Springer, Christiane (2005), UNIPLAN LiveTrends 2004/2005 : Effizienz und Effektivität in der Live Communication ; eine Analyse auf Grundlage einer branchen-übergreifenden Befragung von Marketingentscheidern in Deutschland 66 Kirchgeorg, Manfred; Fiedler, Lars (2004) Clustermonitoring als Kontroll- und Steuerungsinstrument für Clusterentwicklungsprozesse - empirische Analysen von Industrieclustern in Ostdeutschland 65 Schwetzler, Bernhard (2004) Mittelverwendungsannahme, Bewertungsmodell und Unternehmensbewertung bei Rückstellungen 64 La Mura, Pierfrancesco; Herfert, Matthias (2004) Estimation of Consumer Preferences via Ordinal Decision-Theoretic Entropy 63 Wriggers, Stefan (2004) Kritische Würdigung der Means-End-Theorie im Rahmen einer Anwendung auf M-Commerce-Dienste 62 Kirchgeorg, Manfred (2003) Markenpolitik für Natur- und Umweltschutzorganisationen 61 La Mura, Pierfrancesco (2003) Correlated Equilibria of Classical Strategic Games with Quantum Signals 60 Schwetzler, Bernhard; Reimund, Carsten (2003) Conglomerate Discount and Cash Distortion: New Evidence from Germany
59 Winkler, Karsten (2003) Wettbewerbsinformationssysteme: Begriff, Anforderungen, Herausforderungen 58 Winkler, Karsten (2003) Getting Started with DIAsDEM Workbench 2.0: A Case-Based Tutorial 57 Lindstädt, Hagen (2002) Das modifizierte Hurwicz-Kriterium für untere und obere Wahrscheinlichkeiten - ein Spezialfall des Choquet-Erwartungsnutzens 56 Schwetzler, Bernhard; Piehler, Maik (2002) Unternehmensbewertung bei Wachstum, Risiko und Besteuerung Anmerkungen zum Steuerparadoxon 55 Althammer, Wilhelm; Dröge, Susanne (2002) International Trade and the Environment: The Real Conflicts 54 Kesting, Peter (2002) Ansätze zur Erklärung des Prozesses der Formulierung von Entscheidungsproblemen 53 Reimund, Carsten (2002) Internal Capital Markets, Bank Borrowing and Investment: Evidence from German Corporate Groups 52 Fischer, Thomas M.; Vielmeyer, Uwe (2002) Vom Shareholder Value zum Stakeholder Value? Möglichkeiten und Grenzen der Messung von stakeholderbezogenen Wertbeiträgen 51 Fischer, Thomas M.; Schmöller, Petra; Vielmeyer, Uwe (2002) Customer Options Möglichkeiten und Grenzen der Bewertung von kundenbezogenen Erfolgspotenzialen mit Realoptionen 50 Grobe, Eva (2003) Corporate Attractiveness : eine Analyse der Wahrnehmung von Unternehmensmarken aus der Sicht von High Potentials 49 Kirchgeorg, Manfred; Lorbeer, Alexander (2002) Anforderungen von High Potentials an Unternehmen eine Analyse auf der Grundlage einer bundesweiten Befragung von High Potentials und Personalentscheidern 48 Kirchgeorg, Manfred; Grobe, Eva; Lorbeer, Alexander (2003) Einstellung von Talenten gegenüber Arbeitgebern und regionalen Standorten : eine Analyse auf der Grundlage einer Befragung von Talenten aus der Region Mitteldeutschland (not published) 47 Fischer, Thomas M.; Schmöller, Petra (2001) Kunden-Controlling Management Summary einer empirischen Untersuchung in der Elektroindustrie 46 Althammer, Wilhelm; Rafflenbeul, Christian (2001) Kommunale Beschäftigungspolitik: das Beispiel des Leipziger Betriebs für Beschäftigungsförderung
45 Hutzschenreuter, Thomas (2001) Managementkapazitäten und Unternehmensentwicklung 44 Lindstädt, Hagen (2001) On the Shape of Information Processing Functions 43 Hutzschenreuter, Thomas; Wulf,Torsten (2001) Ansatzpunkte einer situativen Theorie der Unternehmensentwicklung 42 Lindstädt, Hagen (2001) Die Versteigerung der deutschen UMTS-Lizenzen eine ökonomische Analyse des Bietverhaltens 41 Lindstädt, Hagen (2001) Decisions of the Board 40 Kesting, Peter (2001) Entscheidung und Handlung 39 Kesting, Peter (2001) Was sind Handlungsmöglichkeiten? Fundierung eines ökonomischen Grundbegriffs 38 Kirchgeorg, Manfred; Kreller, Peggy (2000) Etablierung von Marken im Regionenmarketing eine vergleichende Analyse der Regionennamen "Mitteldeutschland" und "Ruhrgebiet" auf der Grundlage einer repräsentativen Studie 37 Kesting, Peter (2000) Lehren aus dem deutschen Konvergenzprozess eine Kritik des Eisernen Gesetzes der Konvergenz und seines theoretischen Fundaments 36 Hutzschenreuter, Thomas; Enders, Albrecht (2000) Möglichkeiten zur Gestaltung internet-basierter Studienangebote im Markt für Managementbildung 35 Schwetzler, Bernhard (2000) Der Einfluss von Wachstum, Risiko und Risikoauflösung auf den Unternehmenswert 34 No longer available. There will be no reissue. 33 Löhnig, Claudia (1999) Wirtschaftliche Integration im Ostseeraum vor dem Hintergrund der Osterweiterung der Europäischen Union: eine Potentialanalyse 32 Fischer, Thomas M. (1999) Die Anwendung von Balanced Scorecards in Handelsunternehmen 31 Schwetzler, Bernhard; Darijtschuk, Niklas (1999) Unternehmensbewertung, Finanzierungspolitiken und optimale Kapitalstruktur 30 Meffert, Heribert (1999) Marketingwissenschaft im Wandel Anmerkungen zur Paradigmendiskussion
29 Schwetzler, Bernhard (1999) Stochastische Verknüpfung und implizite bzw. maximal zulässige Risikozuschläge bei der Unternehmensbewertung 28 Fischer, Thomas M.; Decken, Tim von der (1999) Kundenprofitabilitätsrechnung in Dienstleistungsgeschäften Konzeption und Umsetzung am Beispiel des Car Rental Business 27 Fischer, Thomas M. (2000) Economic Value Added (EVA ) - Informationen aus der externen Rechnungslegung zur internen Unternehmenssteuerung? (rev. edition, July 2000) 26 Hungenberg, Harald; Wulf, Torsten (1999) The Transition Process in East Germany 25 Vilks, Arnis (1999) Knowledge of the Game, Relative Rationality, and Backwards Induction without Counterfactuals 24 Darijtschuk, Niklas (1998) Dividendenpolitik 23 Kreller, Peggy (1998) Empirische Untersuchung zur Einkaufsstättenwahl von Konsumenten am Beispiel der Stadt Leipzig 22 Löhnig, Claudia (1998) Industrial Production Structures and Convergence: Some Findings from European Integration 21 Schwetzler, Bernhard (1998) Unternehmensbewertung unter Unsicherheit Sicherheitsäquivalentoder Risikozuschlagsmethode 20 Fischer, Thomas M.; Schmitz, Jochen A. (1998) Kapitalmarktorientierte Steuerung von Projekten im Zielkostenmanagement 19 Fischer, Thomas M.; Schmitz, Jochen A. (1998) Control Measures for Kaizen Costing - Formulation and Practical Use of the Half-Life Model 18 Schwetzler, Bernhard; Ragotzky, Serge (1998) Preisfindung und Vertragsbindungen bei MBO-Privatisierungen in Sachsen 17 Schwetzler, Bernhard (1998) Shareholder-Value-Konzept, Managementanreize und Stock Option Plans 16 Fischer, Thomas M. (1998) Prozeßkostencontrolling Gestaltungsoptionen in der öffentlichen Verwaltung 15 Hungenberg, Harald (1998) Kooperation und Konflikt aus Sicht der Unternehmensverfassung
14 Schwetzler, Bernhard; Darijtschuk, Niklas (1998) Unternehmensbewertung mit Hilfe der DCF-Methode eine Anmerkung zum Zirkularitätsproblem 13 Hutzschenreuter, Thomas; Sonntag, Alexander (1998) Erklärungsansätze der Diversifikation von Unternehmen 12 Fischer, Thomas M. (1997) Koordination im Qualitätsmanagement Analyse und Evaluation im Kontext der Transaktionskostentheorie 11 Schwetzler, Bernhard; Mahn, Stephan (1997) IPO s: Optimale Preisstrategien für Emissionsbanken mit Hilfe von Anbot-Modellen 10 Hungenberg, Harald; Hutzschenreuter, Thomas; Wulf, Torsten (1997) Ressourcenorientierung und Organisation 9 Vilks, Arnis (1997) Knowledge of the Game, Rationality and Backwards Induction (Revised edition HHL Working Paper No. 25) 8 Kesting, Peter (1997) Visionen, Revolutionen und klassische Situationen Schumpeters Theorie der wissenschaftlichen Entwicklung 7 Hungenberg, Harald; Hutzschenreuter, Thomas; Wulf, Torsten (1997) Investitionsmanagement in internationalen Konzernen - Lösungsansätze vor dem Hintergrund der Agency-Theorie 6 Hungenberg, Harald; Hutzschenreuter, Thomas (1997) Postreform - Umgestaltung des Post- und Telekommunikationssektors in Deutschland 5 Schwetzler, Bernhard (1996) Die Kapitalkosten von Rückstellungen zur Anwendung des Shareholder- Value-Konzeptes in Deutschland 4 Hungenberg, Harald (1996) Strategische Allianzen im Telekommunikationsmarkt 3 Vilks, Arnis (1996) Rationality of Choice and Rationality of Reasoning (rev. Edition, September 1996) 2 Schwetzler, Bernhard (1996) Verluste trotz steigender Kurse? - Probleme der Performancemessung bei Zinsänderungen 1 Meffert, Heribert (1996) Stand und Perspektiven des Umweltmanagement in der betriebswirtschaftlichen Forschung und Lehre