University of Nevada, Reno. The Effects of Changes in Major League Baseball Playoff Format: End of Season Attendance

Transcription

1 University of Nevada, Reno The Effects of Changes in Major League Baseball Playoff Format: End of Season Attendance A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Economics by Alexis Irion Dr. Mark Nichols/Thesis Advisor May, 2015

2 THE GRADUATE SCHOOL We recommend that the thesis prepared under our supervision by ALEXIS LOUISE IRION Entitled The Effects Of Changes In Major League Baseball Playoff Format: End Of Season Attendance be accepted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Mark Nichols, Advisor Sankar Mukhopadhyay, Committee Member Rahul Bhargava, Graduate School Representative David W. Zeh, Ph.D., Dean, Graduate School May, 2015

3 i Abstract This paper examines the effect on attendance of Major League Baseball (MLB) games as a result of the additional playoff round added by the MLB in Adding another round to the playoffs increases the number of teams qualifying for the playoffs from eight teams to ten teams. More teams towards the end of the season will be in the playoff race than prior to the 2012 season. It is hypothesized that with more teams having a playoff chance, an increase in attendance will result. Home game attendance is a major contributor to team revenue, thus the implications of an increase in attendance would positively impact many teams financially across the league.

4 ii Table of Contents List of Tables... iii List of Figures... iv Introduction... 1 Literature Review... 2 Data and Methodology... 6 Conclusions Bibliography... 23

5 iii List of Tables Page Table 1. All Teams 10 Table 2. 5 th through 8 th Place 13 Table 3. Logged Outcome Variable 15 Table 4. Different Treatment Groups 17 Table 5. Game Day Analysis 19

6 iv List of Figures Page Figure 1. Average Attendance by Team 7 Figure 2. Attendance Comparison within Year 9

7 1 Introduction The goal of this paper is to determine the effect on Major League Baseball game attendance due to the additional playoff round added in Adding another round to the playoffs after the 2011 season advances ten teams to the playoffs compared to the previous eight teams. This results in more teams competing for the added playoff spots at the end of each regular season. Rottenberg s Uncertainty of Outcome Hypothesis (UOH) explains that the more evenly matched a game is between two teams or the more competitive a game is expected to be, the more interested the fan base will be (Rottenberg, 1956). This idea favors playoff expansion as it increases uncertainty for each team making the playoffs and performing well in the playoffs. Teams in the top ranking positions that would have made the eight team playoffs prior to 2012 would not expect any additional change in attendance. The middle ranked teams, say 5 th through 8 th place, would be expected to be the benefactors of this additional round. Therefore, with the additional playoff round placing more teams in the playoff race, an increase in attendance would be expected for these middle ranked teams. Fan attendance at games and ticket sales are a major source of revenue for professional sports teams. Therefore, an increase in home game attendance means a direct increase in revenue for each team. The MLB regular season consists of 162 games, which span from April to September each year. The postseason begins in early October, and crowns the best of the best as the World Series Champion. Although the championship title is referred to as the World

8 2 Series Champion, MLB has teams only in North America. There are 29 teams in the United States and one team in Toronto, Canada. MLB consists of two leagues, the National League and the American League. Each league is composed of three divisions, the East, Central and West. The division winners in both leagues are each awarded a playoff berth. Six teams advance to the playoffs as divisional champions. The remaining teams to make the playoffs come from the Wild Card rankings. Wild Card rankings exist for the National League and the American League. The Wild Card ranks the teams in each league excluding the divisional winners (three teams) by their win-loss record. Prior to 2012, only eight teams made the playoffs. The seventh and eighth teams to make the playoffs are the Wild Card winners for each league. Beginning in 2012, ten teams were able to reach the playoffs. Instead of only one Wild Card team from each league, the top two teams in the Wild Card rankings for each league earn a playoff spot. The first round of the playoffs is a single game playoff between the Wild Card teams in each League. The winner of this Wild Card game then advances to the divisional round. As this additional playoff round is a fairly recent change, the effect of this change on attendance has yet to be examined in other literature. Literature Review The two most recent playoff expansions in the MLB occurred in 1994 and Prior to 1994, there were only two divisions for each league. In 1994 a third division was added to each league. Previously, only division winners made the post season. In order to create an even number of teams in the playoffs, a Wild Card format was instituted.

9 3 Each divisional leader advances to the playoffs, and bypasses the Wild Card rankings. The Wild Card spot in the postseason is awarded to the best of the 2 nd place teams within each league. In the 2012 season, a second Wild Card game was added, which matches the top two teams in the Wild Card race in a single game playoff. The winner then advances to the divisional series. This is the playoff expansion to be analyzed in this paper. With the addition of the second Wild Card being so recent, very little has been studied to analyze its effects. It seems that this addition would keep more teams in the postseason race, especially as the regular season winds down in the month of September. Based on the UOH, an additional amount of uncertainty about reaching the playoffs for each team is created from the wild card single elimination playoff game, creating additional attendance demand. One would expect this to be most prevalent in the month of September as the divisional rankings start to take shape as the regular season comes to a close. There is a point in every season when teams at the bottom of the rankings have lost all chances of making it to the playoffs. However, as teams drop out of the playoff race, there are still more teams remaining in the playoff race than before 2012, thus there are more games at the end of each season with playoff excitement and implications. Before testing the hypothesis that this playoff expansion impacts attendance, I expand on general playoff knowledge to help describe the MLB playoff structure. There are four matchups in each division series. The division series is a best-of-five game series. The

10 4 two teams that advance from the divisional playoffs meet in the League Championship series. The League Championship series is a best-of-seven game series. The league champion is then awarded the title of winner of the National League Championship Series and the winner of the American League Championship Series. Each are crowned and play each other in the World Series for the title. The World Series is a best-of-seven game series. It is important to note the number of games for each series because although an additional playoff round was added, it only consists of one game. It is of interest why MLB has decided that for two teams that do indeed make the playoffs, the regular 162 game season comes down to a single game. Since the other playoff series are five and seven game series, it seems that MLB considers multiple game matches essential to determining the better of the two wild card teams. Given this, it is unclear why only a single game was added to the playoffs rather than a series of games to determine the best of the two Wild Card teams within each League. From 2002 to 2014, eight teams in the MLB have built new stadiums, all of which have decreased the total stadium capacity by an average of 9000 seats. MLB is fighting to stay relevant in today s fast-paced society by making the stadiums smaller to create a better game experience for the fans. This supports adding a single game Wild Card playoff rather than a multiple game series. In addition, MLB has been making significant efforts to make the game of baseball more fan friendly, creating a Pace of Game and Replay Committee which has implemented new rules for the upcoming 2015 season in an attempt to have better flow-of-game with less stoppage time (Starke, Crasnick 2015).

11 5 The uncertainty of outcome hypothesis is an essential idea in sports economics, as leagues can aim for competitive likeness among teams to increase attendance demand and thus boost revenues (Rottenberg, 1956). Evidence was found in the 1988 season to support Rottenberg s outcome uncertainty as a significant factor of attendance (Knowles, Sherony and Haupert, 1992). There are varying types of outcome uncertainty that exist including individual game uncertainty, seasonal uncertainty and playoff uncertainty. It has been established that playoff uncertainty is what truly effects game attendance over a panel series of data from 1901 to 2003 (Lee and Fort, 2008). The changes made to post season play in 1969 and 1994 were specifically analyzed and found to have a substantial increase in postseason uncertainty, similar to the intentions of this paper with the most recent changes to MLB playoffs (Lee, 2009). This paper will not test whether playoff uncertainty increased as a result of the 2012 changes. Rather, based on Lee s 2009 paper I assume playoff uncertainty increased and test what this increase in playoff uncertainty has done to the demand for attendance. Furthermore, it was found that playoff uncertainty does in fact increase attendance, particularly during the closing months of the regular season, leading this analysis to focus on the month of September (Krautmann, Lee, Quinn, 2011). However, it has also been found that although a relationship between outcome and uncertainty exists, over the years this relationship is lessening (Beckman, Cai, Esrock, Lemke, 2012). This can be explained in part since in recent years there are more factors that contribute to attendance demand than in previous years, including playing style and stadium quality (Ahn, Lee 2014). New stadiums are designed to improve the fan experience which can also increase

12 6 attendance. It is clear that the 2012 playoff expansion increases uncertainty for teams to make the playoffs, and it makes sense that an increase in attendance would likely be the result. Data and Methodology Data are collected for all 30 teams in Major League Baseball spanning the 2002 to 2014 seasons. The new playoff format began in 2012, so there are three years of data after the change, from 2012 to 2014, and ten years of data before the change, from 2002 to With the additional round, each team that wins their division receives a playoff berth in addition to the top two ranked teams in each league s Wild Card race. The two Wild Card teams play a single elimination game and the winner advances to the second round of the playoffs, the divisional series. The added playoff game is defined as the treatment. A simple difference-in-differences model is used to estimate this treatment effect. Control variables are included to capture each team s Metropolitan Statistical Area s (MSA) characteristics. The MSA is appropriate because a team s fan base expands beyond city and county lines. A control variable for a new stadium is used to account for new stadiums that were built during the time period of interest. Team fixed effects and a time trend variable are included. As the attendance increase is expected to be seen for the last month of the season, ranking statistics are included as of September 1 each year, including Division place, Division games back, Wild Card place and Wild Card games back for each team. For

13 7 Division and Wild Card rankings, games back for both rankings are presented. Games Back is the number of games a team sits in the standings behind the next highest ranked team. Each teams win/loss record as of September 1 st each year is included in the model. The variable of interest is average attendance per game in the final month of the season. The final month begins September 1 st of each year, however some years the regular season extends to the first few days in October. These October games are included in the average attendance calculated for the final month of the season. Figure 1 plots the average attendance per game in the month of September for each team from 2002 to Looking at Figure 1, there does not appear to be a general flow of attendance over time for all of teams in Major League Baseball. The attendance

14 8 for many teams has stayed relatively flat over the 2002 to 2014 time period such as the entire bottom row of teams in Figure 1. Visually it appears that most teams hit a locally low attendance value around , if not an all-time low. This could explain why MLB looked to expand the playoffs in an attempt to combat this decline in attendance. Teams like Houston (HOU), Arizona (ARZ), New York Mets (NYM), Chicago White Sox (CHW), and Cleveland (CLE) show all time low attendance average for games in the month of September in This may be due to a delayed reaction time, as these teams have yet to experience any treatment effect from the 2012 playoff expansion. Additionally, from the years 2012 to 2014, these teams have been so uncompetitive within the league that any playoff changes would not affect them as they have had little or no hope in recent years of making the playoffs. Data was collected for each team s home game attendance along with each team s home stadium s total capacity (ESPN). The average per game home attendance was divided into two parts of the regular season. The average per game attendance for the regular season after September 1 st and the average per game attendance for the regular season prior to September 1 st. What we are interested in is the per game attendance average during the month of September, comparing this attendance with the rest of the season. Figure 2 plots each team s average attendance for the month of September with the average game attendance for the rest of the year. This figure shows that September average game attendance often follows the trend for the season relative to

15 9 other years. If attendance is down from April to August, it is likely to be down in September as well. As expected, the total capacity for each team varies, thus the outcome variable is calculated as Y dt = average game attendance in sept total stadium capacity. I estimate the following model, Y dt = α 0 + α 1 A d + α 2 trend t + α 3 X dt + α 4 post t + α 5 treated dt + β(post treated) dt + ε dt, where the outcome variable Y dt is the percentage of per game attendance for the final month of the season for team d at time t. A d is team fixed effects and trend t is the included time trend. X dt are the descriptive covariates, per capita income, and unemployment of the MSA for each team. The variable post t is an

16 10 indicator variable for years that are after the treatment, thus 2012 to The variable treated dt is an indicator variable for those teams in the treatment group. In this paper, different places for teams are used to define the treatment group, such as 4 th through 8 th place or 5 th through 7 th place. The idea is that this group of teams are more likely to have a chance in the playoffs now that an additional team gets into the single Wild Card playoff game. Prior to this additional round, these teams were more than likely out of the playoff race. The variable of interest is β on the interacted (post treated) dt term, which gives the treatment effect. Table 1. All Teams ATT Percent VARIABLES (1) (2) post *** (0.0175) *** (0.0160) trend.0052 (.0051).0036 (.0068) AL (.0277).0152 (.0250) EAST (.0339) (.0820) WEST ** (.0276) (.0093) New Stadium.0300 (.0307).0396 (.0286) Wins on 9/1.0042*** (.0008).0035*** (.0005) Constant ** (.1182) ** (.1355) Sample Size R-squared Team Fixed Effects No Yes *** p<0.01, ** p<0.05, * p<0.1

17 11 The first regression (1) displayed in Table 1 shows the overall change in attendance. The additional Wild Card game added in 2012 effects all the teams as it modifies the entire playoff structure and the specific teams that make the playoffs will vary from year to year. The variable of interest is attendance percentage, which is the average attendance percentage of the team s stadium s total capacity for the final month of the season. The final month of the season was chosen because as the season winds down and the playoff race takes shape, the playoff format changes should have the greatest effect. A statistically significant overall decrease in attendance of 5.8% for all teams between the years 2012 to 2014 was found. The standard errors are clustered at the team level. A time trend is included in the model, however it is not estimated to be significant. There is no significant relationship found for teams relative to being in the American or National League. A 5% decrease is found for teams in the Eastern Division, although not significant, however interestingly enough, a statistically significant 6.1% decrease in average game attendance in the final month of the season for being a member of the Western Division. This implies there is some advantage to being in the Central division but this anomaly could be explained by the Central division being stronger than the others in most recent years. A new stadium estimates an insignificant 3% increase in attendance percentage, which matches intuition that as teams are downsizing their stadium size when building new stadiums, an increase in attendance percentage would occur. This could also be capturing the benefits of improving the fan experience when new stadiums are built.

18 12 The number of wins a team has as of September 1 st leads to a statistically significant estimated 4.2% increase in average per game attendance for the month of September. On average each team plays 13 home games in the final month of the season, sometimes as few as nine games to as many as 17. On average for all the teams, a single game has approximately 30,000 people in attendance. If a team has one more win on September first, this can lead to an average additional 1,440 people in attendance for each game in the month of September. For an average of 13 home games in September, this means on average an 18,720 increase in attendance for each additional win a team has as of September 1. The second regression (2) displayed in Table 1 adds team fixed effects to regression (1), still considering all 30 teams in the treatment group. This model estimates a significant but smaller decrease of 5.1% in attendance in the final month of the season for all teams between the years 2012 to As was done in model (1) the standard errors are clustered for teams and a time trend variable is included. There is no significant relationship found for teams relative to being in the American or National League. The estimate for the Western division effect on end of season attendance is no longer significant in model (2). The new stadium estimate is again insignificant. The number of wins a team has as of September 1 st estimates a lower statistically significant 3.5% increase in average per game attendance for the month of September. Table 2 looks at the treatment group as teams in 5 th through 8 th place in the Wild Card Standings. Prior to the 2012 playoff expansion, only the winner of the Wild Card

19 13 received a playoff berth. Now the top two teams move onto the playoffs. It is theorized that teams in teams in 3 rd and 4 th in the Wild Card standings were likely in the playoff race prior to 2012, but now teams in 5 th through 8 th will benefit from the expansion. Both regressions in Table 2 cluster standard errors at the team level. Neither regression (3) or (4) displayed in Table 2 estimate a statistically significant treatment effect. Table 2. 5 th through 8 th Place VARIABLES (3) (4) treated*post (.0258).0094 (.0173) treated.0022 (.0159) (.0125) post *** (.0155) *** (.0134) trend.0055 (.0050).0031 (.0068) AL.0090 (.0259) (.0311) EAST (.0333) (.0759) WEST ** (.0275).0280 (.0178) New Stadium.0219 (.0293).0309 (.0285) Win Percentage.1243 (.2641).1416 (.2337) WC GB 9/ ** (.2641) (.0017) Constant.0011*** (.1751) (.1787) Sample Size R-squared Team Fixed Effects No Yes *** p<0.01, ** p<0.05, * p<0.1

20 14 There is no significant relationship found for teams relative to being in the American or National League or in the Eastern Division. Model (3) estimates that for the years after the playoff expansion, a statistically significant 5.1% decrease was seen in average attendance for the last month of the season. A statistically significant estimate of a 6.1% decrease in average attendance for the last month of season for teams in the Western Division, which is close to what was estimated in model (1) and (2). The estimated effect of a new stadium is insignificant. Rather than the number of wins as of September 1 st which was used in the regressions in Table 1, here the actual win percentage was used. This is calculated as percentage = wins as of 9/1 wins +loses as of 9/1. The estimated win percentage coefficient of 12% was not statistically significant. The number of games back in the Wild Card race as of September 1 st (WC GB 9/1) is included in model (3), and is estimated as a 0.4% decrease in attendance per game in the month September for each additional game back in the Wild Card race. Model (4) adds team fixed effects to model (3) and the estimated coefficients on the Western division, Wild Card Games Back as of Sept. 1 and the constant becomes insignificant. The estimated effect for the years after the playoff expansion, remains significant but becomes more negative at a 5.5% decrease in average attendance for the last month of the season. This shows a larger decrease in end of season attendance from 2002 to 2014 than from 2012 to 2014, which supports the notion that baseball is losing its popularity. However, due to better television and technology it may be that fans enjoy watching baseball

21 15 more at home than actually attending the games. The decline in attendance does not imply a decline in fan base. Table 3. Logged Outcome Variable VARIABLES (5) (6) (7) treated*post * (.0246) (.0297) (.0287) treated.0049 (.0185) (.0207) (.0287) post *** (.0247) *** (.0253) *** (.0250) trend.0157*** (.0056).0057 (.0120).0055 (.0119) AL (.0156) (.0423) (.0423) EAST.0197 (.0211) (.1072) (.1083) WEST.0403** (.0219).1438*** (.0355).1383*** (.0361) New Stadium (.0183).0003 (.0273).0066 (.0295) Win Percentage (.2974).1459 (.3689).1399 (.3711) WC GB 9/ ** (.0023) * (.0027) * (.0027) constant *** (.1882) *** (.3465) *** (.3489) Sample size R-squared Team Fixed No yes yes effects Total Capacity No No Yes *** p<0.01, ** p<0.05, * p<0.1 Up to this point the dependent variable has been attendance percentage. Instead, Table 3 looks at a log transformation of attendance as the outcome variable. Model (6) adds team fixed effects to model (5). The treatment group remains as teams in 5 th

22 16 through 8 th places. The estimated treatment effect in model (5) is a statistically significant additional 4.4% decrease in the attendance average per game in the month of September. While counterintuitive, this treatment effect is only significant at 10% level and it should be recognized that we do not know what attendance for this treatment group would have been had the playoff change not been implemented. The time trend estimate is positive and significant only in model (5) and much smaller in magnitude than the post estimate, 1.6% and -7.2% respectively. Similar to the previous models, the estimates on AL, East, New Stadium and Win Percentage are not significant. The number of games back in the Wild Card race as of September 1 st (WC GB 9/1) is estimated as a statistically significant 0.6% decrease in attendance per game in the month September for each additional game back in the Wild Card race. The model estimates a 4% increase in average September attendance for teams in the Western division. It is interesting that in this model the sign on this estimate has become positive, and remained significant. Model (6) adds team fixed effects to model (5). The estimated treatment effect in model (6) is an additional 0.2% decrease in the attendance average per game in the month of September. This is not significant. Just as in model (5), the estimates on AL, East, New Stadium and Win Percentage are not significant. In addition, the time trend estimate becomes insignificant. The number of games back in the Wild Card race as of September 1 st (WC GB 9/1) is again estimated as a 0.5% decrease in attendance per game in the month September for each additional game back in the Wild Card race and

23 17 is statistically significant. As in model (5), it is a positive and significant estimate for teams in the Western division, estimated as a 14.4% increase in average September attendance for teams in the Western division, a large increase from the previous models. Table 4. Different Treatment Groups VARIABLES (8) 4 th 8 th (9) 5 th 7 th Place Place treated*post (.0272) * (.0269) treated.0133 (.0173).0142 (.0194) post *** (.0249) *** (.0251) trend.0158*** (.0057).0158*** (.0057) AL (.0155) (.0158) EAST.0195 (.0206).0188 (.0210) WEST.0402* (.0221).0402* (.0219) New Stadium (.0181) (.0187) Win Percentage.0091 (.2876).0024 (.2881) WC GB 9/ ** (.0022) ** (.0022) constant *** (.1848) *** (.1834) Sample size R-squared Team Fixed Effects No No *** p<0.01, ** p<0.05, * p<0.1

24 18 Model (7) adds a control variable for total stadium capacity to model (6) to account for teams having different stadium sizes, which surprisingly does not make much of a difference, particularly when compared to model (6). A significant treatment effect in model (6) is not found. Similar to models (5) and (6) the estimates on AL, East, New Stadium and Win Percentage remain insignificant. The number of games back in the Wild Card race as of September 1 st (WC GB 9/1) is again estimated as a 0.5% decrease in attendance per game in the month September for each additional game back in the Wild Card race and is statistically significant as in model (6). As in model (5) and (6) it is again a positive and significant estimate for teams in the Western division, but decreases to a 13.% increase in average September attendance for teams in the Western division. This is a higher estimate than found in model (5) but lower than in model (6). In Table 4, the logged outcome variable is still being used, however the definition of the treatment group changes. In both models the standard errors are clustered at the team level. In Model (8) the treatment group is defined as teams in 4 th through 8 th place in the Wild Card race as of September 1 st of each season. A significant treatment effect is not found. A positive and significant estimate for teams in the Western division is estimated as a 4% increase in average September attendance for teams in the Western division. The number of games back in the Wild Card race as of September 1 st (WC GB 9/1) is again estimated as a 0.6% decrease in attendance per game in the month September for each additional game back in the Wild Card race and is statistically

25 19 significant. Time trend and post are significant estimates in model (8), -7.4% and 1.6% respectively. This is similar to the significant estimates found in model (5). Late season attendance is down since 2002, but it has been increasing since the playoff expansion of Table 5. Game Day Analysis VARIABLES (10) 5 th 8 th (11) 5 th 7 th Place (12) 4 th - 8 th place Place Treated*post (.0408) (.0314) (.0333) treated.0070 (.0237) (.0221).0213 (.0211) post (.0231) (.0214) (.0236) trend (.0063) (.0063) (.0061) AL (.0351) (.0348) (.0349) EAST ** (.0415) ** (.0410) ** (.0417) WEST (.0392) (.0392) (.0391) New Stadium.1408*** (.0326).1382*** (.0058).1439*** (.0322) Win Percentage.6774** (.2960).6583** (.3046).7160** (.3030) WC GB 9/ (.0326) (.0020) (.0020) Constant.0760 (.2114).0919 (.2171).0516 (.2139) Sample size R-squared Team fixed effects No No No *** p<0.01, ** p<0.05, * p<0.1

26 20 In Model (9) the treatment group is defined as teams in 5 th through 7 th place in the Wild Card race as of September 1 st of each season. A significant treatment effect is found to be a 4.7% additional decrease in average attendance per game in the month of September for teams in 5 th through 7 th place in the Wild Card rankings. Again, however, this treatment effect is only significant at the 10% level. The same positive and significant estimate for teams in the Western division as found in Model (7) is estimated as a 4% increase in average September attendance for teams in the Western division. The number of games back in the Wild Card race as of September 1 st (WC GB 9/1) is again estimated as a 0.6% decrease in attendance per game in the month September for each additional game back in the Wild Card race and is statistically significant. Post and time trend estimates in model (9) are the same as in model (8) and remain significant. An analysis of the results of Models (8) and (9) indicates that teams in 4 th place in the Wild Card rankings do not receive any treatment effect one would expect. A 4 th place team would not see any effects from the playoffs moving from an eight team format to a ten team format, as they are in the playoff hunt in both the eight and 10 team playoff formats. Up to this point all of the analysis has been at the month level. The average attendance from each individual game averaged for the month for each season for every team. It is of interest to note the results and if any differences exist looking at the game day level rather than the month level. In model (10) at the day level, the treatment group is defined as teams in place 5 th through 8 th in the Wild Card standings as of September 1 st.

27 21 A significant treatment effect at the day level is not found for any of the defined treatment groups. A team s win percentage as of September 1 st is estimated as a 67.7% increase in attendance per game in September. This is an extremely large estimate, especially compared to the previously estimated monthly effects, but is consistent across treatment groups and statistically significant at the day level. In model (11) the treatment group is teams in 5 th through 7 th place in the Wild Card standings as of September 1 st and model (12) looks at teams in 4 th through 8 th place. At the day level, the estimates for the Eastern division are negative and significant, compared to the month analyses where the Eastern division coefficient was insignificant and the Western division estimate was significant. New stadium and win percentage are positive and significant at the day level. The significant estimates at the day level are very close for the different treatment groups. Greater fluctuation exists at the game day level compared to the month averages analyses. Conclusions As end of season attendance has been decreasing for Major League Baseball, the treated teams in 5 th through 8 th place in the Wild Card standings as of September 1 st saw little or no change in attendance from the 2012 playoff expansion. This playoff format change did not make any teams better off as hypothesized. As attendance throughout the league is declining and stadiums are being downsized, it is likely MLB made the change in 2012 to the playoff format to try and counteract the attendance decline. These efforts combined with the new rules to increase speed of play appear to all be

28 22 steps in the right direction and should be explored further by Major League Baseball. Although this did not find playoff expansion to be an effective tool boost attendance, maybe a delayed effect will be seen in the future. Playoff expansion remains a tool that professional sports leagues should consider in an effort to successfully increase fan attendance. It is recommended that this analysis be performed again when more years of data are available. This paper assumed that the 2012 playoff expansion increased playoff uncertainty which has been shown to increase attendance, but it would be useful to test whether or not playoff uncertainty did, in fact, increase. This analysis looks at home game attendance, but does not consider who the opponent is. For visiting teams who have all-star players on their rosters, the star power often brings a boost in attendance for the home team regardless of playoff position. This would be important to factor into this analysis. In addition, it would be good to look at the impact of Legacy teams, such as the New York Yankees and the Boston Red Sox, who have such a devoted and massive fan base that attendance does not seem to vary much relative to seasonal success. How these teams affect attendance at other stadiums is an additional aspect to explore. It is also of interest to analyze the difference between multi-game series versus a one game playoff. For instance, if each series was actually cut back to a one game series, how often is the winner of the first game the winner of the series and what is the benefit of a seven game series compared to a five game series.

29 23 Bibliography Ahn, S. C., & Lee, Y. H. (2014). Major league baseball attendance: Long-term analysis using factor models. Journal of Sports Economics, 15(5), doi: / Beckman, E. M., Cai, W., Esrock, R. M., & Lemke, R. J. (2012). Explaining game-to-game ticket sales for major league baseball games over time. Journal of Sports Economics, 13(5), doi: dx.doi.org.innopac.library.unr.edu/ / Databases, Tables & Calculators by Subject. Retrieved November 16, 2014, from ESPN MLB Major League Baseball. Retrieved November 16, 2014, from Knowles, G., Sherony, K., & Haupert, M. (1992). The demand for major league baseball: A test of the uncertainty of outcome hypothesis. American Economist, 36(2), Retrieved from search.proquest.com.innopac.library.unr.edu/docview/ ?accountid=452 Krautmann, A. C., Lee, Y. H., & Quinn, K. (2011). Playoff uncertainty and pennant races. Journal of Sports Economics, 12(5), Retrieved from search.proquest.com.innopac.library.unr.edu/docview/ ?accountid=452y

30 24 oung H. Lee. The impact of postseason restructuring on the competitive balance and fan demand in major league baseball. Journal of Sports Economics, 10, Lee, Y. H. (2009). The impact of postseason restructuring on the competitive balance and fan demand in major league baseball.journal of Sports Economics, 10(3), doi: Lee, Y. H., & Fort, R. (2008). Attendance and the uncertainty-of-outcome hypothesis in baseball. Review of Industrial Organization, 33(4), doi: dx.doi.org.innopac.library.unr.edu/ /s MLB Major League Baseball. Retrieved November 16, 2014, from Rottenberg, S. (1956). The Baseball Players' Labor Market. Journal of Political Statistics Canada. Retrieved November 16, 2014, from Economy,64(3), Retrieved November 16, 2014, from Stark, J., & Crasnick, J. (2015, February 20). MLB adds pace-of-play rules for '15. Retrieved February 26, 2015, from U.S. Economic Accounts. Retrieved November 16, 2014, from