Complete Analysis of Difficulty of Schedule

$21 95 The 2016-17 KillerSports.com NBA Schedule/Log Featuring the SDQL! Complete Annotated 2016 17 Team Schedules Back-to-Back Road Games Opponents on Long Road Trips Days Rest Combinations 4th Game in Five Days 420 Perfect Team Trends! Fourteen for Each Team Complete Analysis of Difficulty of Schedule Back-to-Back Road Games Rest vs No Rest Combinations Opponents on Long Road Trips Missing Games in the Schedule 1

CONTENTS 3 Quick SDQL Overview 4 Back-to-Back Road Games 8 Rest vs No Rest and No Rest vs Rest 9 Missing Games in the 10 Opponents on Long Road Trips 11 SportsBook Breakers NBA Study: Fourth Quarter Carryover 13 Team Trends Section 45 Team Schedule Section 2 www.sportsdatabase.com

QUICK SDQL OVERVIEW SDQL stands for Sports Data Query Language. It is a new language that allows the investigation of past sports results over the internet using your home computer. It is easy, it is fast and it is free. If you can perform a search on Google, you can query the past results of professional sports games. Like the Google search, there is a text query box in which you enter what you would like to search. Unlike Google, the search has to be specific and you must use the Sports Data Query Language. The advantage of the SDQL is that you get one hit, which is exactly what you asked for not a billion hits, most of which are not what you are looking for. For example, if you want to see the results for all road favorites in the NBA since 1995-96 (the start of the database), simply enter: AF query into the query text box and then click on the query button. It is as simple as that! There are SDQL query text boxes at many internet sites. The most developed is currently at: killersports.com/nba.py/query To see all the NBA games in which a team shot less than 40% from the field and won the game, enter FGP<40 and W query That s it! The SDQL allows access to billions of situations that are of interest to sports historians, the sports media, fantasy league participants and serious sports bettors. The ability to quickly and efficiently interrogate historical data in the NBA (as well as the NFL, NHL, MLB and NCAA football and basketball) will provide the SDQL user a terrific advantage over those that just pore over box scores and read other people s interpretations of the results. Perhaps the best way to grasp the SDQL is to simply try the hundreds of examples in the trends section of book using query page. Basically, there are only a couple of key ideas that will get you well on your way to becoming an SDQL master. The first is that a query consists of a number of conditions separated by the word and. The second is grasping the difference between the team and the opponent. In sports, there are two combatants. To distinguish between them, SDQL calls one of these the team and the other the opponent. This allows access to results based on both the performance of the team and the performance of their opponent. For example, we can see how a team performs when they score at least 100 points and we can see how a team performs when their opponent scores at least 100 points. For example, to see how the Heat perform in games in which they scored at least 100 points, use: team = Heat and points>=100 query When this query is run, the computer responds with a records summary and a game listing of all the games since 1995 in which the Heat scored at least 100 points. To see how the Heat perform in games in which they allowed at least 100 points, use: team = Heat and o:points>=100 query The o: prefix on the points parameter directs it to the opponent rather than the team. To see how the Heat perform in games AFTER they scored at least 100 points, use: team = Heat and p:points>=100 query Here, the p: prefix on the points directs the parameter to the team s previous game. Each one of these queries has two SDQL phrases. The first defines the team and the second gives a condition. There is no limit to the number of SDQL phrases that can be strung together with the word and. That s it. This is the basic structure of the SDQL. This structure will allow the thorough interrogation and investigation of historical sports data. Understanding this structure is the key to understanding the SDQL. Once you have a grasp of this structure, you will be able to perform your own investigations. Start by trying the many examples in this book. If you have any questions about the SDQL, address them to the sportsdatabase. com discussion group at: http://groups.google.com/group/sportsdatabase This group is monitored by numerous SDQL masters who will be able to be able to address all your well-posed questions. Happy Hunting! killersports.com/nba.py/query 2016 17 NBA Schedule Log 3

BACK-TO-BACK ROAD GAMES In all the major professional sports, the back-to-back road game in the NBA might be the most physically grueling. In the NFL, there are different players for offense and defense and the NFL plays sixteen regular season games a year. In the NBA, there are usually 82 regular season games and the players must play both defense and offense. Unlike other sports, the line for the side on the game is adjusted when one team in unrested and the other is not. That is, the NBA is the only major sport that adjusts the lines for a fatigue factor. Let s investigate this further. To start, we present the following three query results with their associated Sports Data Query Language (SDQL) text: SDQL: A SU: 10338-15598 (-3.18, 39.9%) ATS: 12845-12589-502 (0.10, 50.5%) avg line: +3.3 SDQL: rest > 0 and A SU: 7110-10258 (-2.76, 40.9%) ATS: 8667-8366-335 (0.21, 50.9%) avg line: +3.0 SDQL: A and p:a and rest=0 SU: 1716-2744 (-3.74, 38.5%) ATS: 2218-2148-94 (0.13, 50.8%) avg line: +3.9 The first query, which is simply the capital letter A (A means the away team), gives the results of all road games since 1995-96. Here we see that the road team has a record of 10338-15598, which is 39.9% winners. We also see that they have been a 3.3 point underdog on the average and we see that they have lost by an average of 3.18 ppg. The second query, A and rest>0, gives the results of all road teams since 1995-96 in which they did not play the day before. Here we see that the rested road team is 7110-10258 straight up, which is 40.9% winners. We also see that they have been a 3.0 point underdog on the average and we see that they have lost by an average of only 2.76 ppg. Finally, the third query, A and rest=0 and p:a, gives the results of all road teams since 1995-96 in which they played on the road the day before. Here we see that the unrested road team is 1716-2744, which is 38.5% winners. Also, we see that they have been a 3.9 point underdog on the average and we see that they have lost by an average of 3.74 ppg. So, unless the schedule-makers assign more back-to-back games to teams that are expected to be poor, the results indicate that NBA teams are negatively affected when playing their second road game in two days. Specifically, since the start of the 1995-96 NBA season, road teams with rest have lost by an average of 2.76 ppg and road teams playing their second road game in two days have lost by an average of 3.74 ppg. It is clear that the linesmakers have corrected for this, as teams playing their second road game in two days have been getting an average of 3.9 points whereas rested road teams have only been given an average of 3.0 points. This season there are 174 back-to-back road games that are distributed among the 30 NBA teams, down from 207 in 2015-16. Some teams have been saddled with a large number of back-toback road games and others have only a few. It is useful to look at the number of times a team is hosting an opponent that is playing in the second of B2B road games. Clearly, if a particular team hosts a large number of opponents coming in off another road game the previous night that team has an advantage. The number of times a team plays and hosts the second of back-to-back road games are important factors in determining the difficulty of a team s schedule and thus an important factor in estimating the number of wins they will have over the season. To aid in this investigation, we present a table on the next page that gives the number of B2B occurrences for each team for the upcoming 2016-17 season for two situations; one is when the team is playing its second road game in two days and the other is when the team is hosting an opponent that is playing its second road game in two days. Chicago Bulls Finishing Up a Road Trip The Bulls are 18-0 ATS (+8.00 ppg) since 2001 in the last game of at least a four-game road trip vs a Western conference opponent. The SDQL text is: team = Bulls and not C and A and p:a and pp:a and ppp:a and n:h and season >= 2001 Check out the complete game listing for this trend by running the SDQL at: http://killersports.com/nba.py/query 4 www.sportsdatabase.com

2016 2017 BACK-TO-BACK ROAD GAMES # of Back-to-Back Road Games 2016-17 Team Playing Hosting Differential ATL 4 5 +1 BKN 5 4-1 BOS 2 9 +7 CHA 4 5 +1 CHI 3 7 +4 CLE 6 5-1 DAL 3 4 +1 DEN 6 6 0 DET 5 3-2 GSW 11 12 +1 HOU 5 6 +1 IND 5 3-2 LAC 8 8 0 LAL 8 4-4 MEM 7 4-3 MIA 7 10 +3 MIL 7 4-3 MIN 5 8 +3 NOP 9 4-5 NYK 6 3-3 OKC 7 6-1 ORL 8 2-6 PHI 3 6 +3 PHX 3 6 +3 POR 7 8 +1 SAC 8 5-3 SAS 5 6 +1 TOR 6 5-1 UTA 7 11 +4 WAS 4 5 +1 TOTAL 174 174 0 Looking down the first column we see that there is only one team that has to play double-digit road games this season is the Golden St Warriors, with eleven. On the other end of the spectrum, we find that the Boston Celtics only have to play two back-to-back road games this season and the Bulls, Mavericks, 76ers and Suns only have to play three and the Hawks, Hornets and Wizards only have to play four. Moving to the next column, we find the number of times each team hosts an opponent that has no rest and played on the road last night. In this column we have a larger range of numbers than in the previous. The Orlando Magic host only two opponents playing the second of back-to-back road games all season and the Pistons, Pacers and Knicks only get three such opponents. There are three teams with double-digit opponents that are playing their second road game in as many nights. The Warriors get twelve, the Jazz get eleven and the Heat get ten. It might appear that the Warriors have good back-to-back scheduling situation because they host one more bakc-to-back road game than they play, but the Warriors are very unlikely to be able to win more home games because their opponent is playing the second of back-to-back road games because they are already likely to win their home games. However, on the road the fact that they are playing the second of back-to-back road games might give their opponent the advantage they need. Other teams that host a lot of opponents playing the second of back-to-back road games include the Celtics with nine, the Blazers, Timberwovles, and Clippers with eight and the Bulls with seven. The final, right-most column in the table gives the difference between the number of times a team hosts the second of B2B road games and the number of times a team plays B2B road games. A high positive number has a scheduling advantage and a team with a high negative number has a scheduling disadvantage. The team with the most favorable differential is the Celtics at plus seven. Next is the Jazz and Bulls at plus four. The team that has the most unfavorable differential is the Magic at minus six, the Pelicans at minus five and the Lakers at minus four. The article on the next two pages gives a complete listing of all the back-to-back road games that each NBA team both plays and hosts for the upcoming 2016-17 NBA season. Play Smart. Play Informed. Investigate Back-to-Back road games at KillerSports.com using the SDQL. Clippers in Second of Back-to-Back The Clippers are 9-0 ATS (+9.50 ppg) as a favorite when playing the second of back-to-back road games after winning the first as a dog. The SDQL text is: team=clippers and AF and p:wad and rest=0 2016 17 NBA Schedule Log 5

BACK-TO-BACK ROAD GAMES PLAYING The table below gives a complete listing of all the dates when a team is playing the second of Back-to-Back road games over the entire 2016-17 NBA season. The team in the left-most column is the team playing the Back-to- Back road game. The entries in the table give the date and opponent. For example, on 11/28 the Hawks face the Warriors in Oakland having played on the road the previous night. The level of opponent is important when determining the advantage of hosting a Back-to-Back road game. For example, on 11/19 the Bucks are playing the second of back-to-back road games at Golden St. This is a game that the Warriors were very likely to win anyway. The situations where hosting a back-toback road game is helpful is when the scheduling advantage is likely to be enough to turn a loss into a win. For example, on 11/15 the Nets host the Lakers when LA played on the road the night before. This might give the Nets the edge they need to win a game they otherwise might have lost. Team 1 2 3 4 5 6 7 8 9 10 11 ATL 11/28 GSW 01/05 NOP 02/02 HOU 04/02 BKN BKN 11/15 LAL 01/21 CHA 01/28 MIN 02/25 GSW 03/04 POR BOS 02/09 POR 03/06 LAC CHA 12/17 ATL 02/01 GSW 02/26 LAC 04/11 ATL CHI 11/10 MIA 11/20 LAL 03/13 CHA CLE 01/11 POR 02/09 OKC 03/04 MIA 03/12 HOU 03/19 LAL 04/10 MIA DAL 11/09 GSW 12/30 GSW 04/05 LAC DEN 11/06 BOS 12/08 WAS 02/11 CLE 03/01 MIL 04/05 HOU 04/12 OKC DET 11/12 DEN 11/30 BOS 01/13 UTA 02/13 MIL 03/22 CHI GSW 11/19 MIL 12/08 UTA 12/11 MIN 12/23 DET 01/23 MIA 02/11 OKC 02/28 WAS 03/06 ATL 03/11 SAS 03/21 DAL 03/29 SAS HOU 11/02 NYK 12/02 DEN 03/18 DEN 03/31 GSW 04/10 LAC IND 10/29 CHI 12/05 GSW 12/15 NOP 01/21 UTA 03/06 CHA LAC 11/05 SAS 11/12 MIN 12/02 NOP 12/31 OKC 01/24 PHI 02/06 TOR 03/04 CHI 03/09 MEM LAL 11/02 ATL 11/13 MIN 11/30 CHI 12/03 MEM 12/17 CLE 12/23 ORL 01/26 UTA 02/03 BOS MEM 12/27 BOS 01/04 LAC 01/28 UTA 02/04 MIN 03/04 HOU 03/16 ATL 03/27 SAC MIA 12/01 UTA 12/10 CHI 12/30 BOS 01/04 SAC 02/11 PHI 03/29 NYK 04/08 WAS MIL 11/17 MIA 12/31 CHI 01/21 MIA 02/04 PHX 03/18 GSW 03/22 SAC 03/29 BOS MIN 11/09 ORL 11/26 GSW 12/03 CHA 03/25 POR 04/07 UTA NOP 11/08 SAC 12/11 PHX 02/01 DET 02/13 PHX 02/26 OKC 03/06 UTA 03/27 UTA 04/08 GSW 04/12 POR NYK 11/12 TOR 12/31 HOU 01/07 IND 02/01 BKN 03/12 BKN 03/23 POR OKC 11/03 GSW 11/23 SAC 12/14 UTA 01/05 HOU 01/16 LAC 03/03 PHX 03/27 DAL ORL 10/29 CLE 11/14 IND 12/02 PHI 01/02 NYK 01/14 UTA 01/30 MIN 03/17 PHX 04/01 BKN PHI 12/30 DEN 02/02 SAS 03/12 LAL PHX 11/19 PHI 01/22 TOR 03/24 BOS POR 11/18 NOP 11/23 CLE 12/08 MEM 01/21 BOS 03/07 OKC 03/15 SAS 03/19 MIA SAC 11/01 MIA 11/06 TOR 11/28 WAS 01/21 CHI 01/28 CHA 02/15 GSW 03/19 SAS 04/01 MIN SAS 11/26 WAS 12/06 MIN 12/23 POR 01/24 TOR 02/13 IND TOR 11/21 LAC 12/29 PHX 01/18 PHI 03/04 MIL 03/11 MIA 04/05 DET UTA 11/07 PHI 11/12 MIA 11/20 DEN 01/03 BOS 01/08 MEM 02/09 DAL 03/16 CLE By scanning each team s back-to-back road games this season both quantity and opponent the astute handicapper can estimate the deleterious effect the back-to-back road games might have on their win-loss record for the season. To query on historical results when a team is playing the second of back-toback road games, use, for example: A and p:a and rest =0 and team=hawks The table on the next page gives the games in which each team is hosting an opponent that is playing the second of Backto-Back road games. 6 www.sportsdatabase.com

BACK-TO-BACK ROAD GAMES HOSTING The table below gives a complete listing of all the dates when a team is hosting the second of Back-to-Back road games over the entire 2016-17 NBA season. This information is exactly the same that is in the previous table but it is organized differently. Here it is advantageous to have a large number of games. The team in the left-most column is the team hosting the Back-to-Back road game. The entries in the table give the date and opponent. For example, on 11/02 the Hawks host the Lakers and the LA played on the road the previous day. Note that the Warriors host twelve back-to-back road games this season; tops in the league while the Orlando Magic have only TWO such opponents. These numbers or more good information to assist in the forecasting of a team record for the upcoming 2016-17 regular season. As before, it is not just the quantity of games that matters, it is the level of the opponent as well. Team 1 2 3 4 5 6 7 8 9 10 11 12 ATL 11/02 LAL 12/17 CHA 03/06 GSW 03/16 MEM 04/11 CHA BKN 02/01 NYK 03/12 NYK 04/01 ORL 04/02 ATL BOS 11/06 DEN 11/30 DET 12/27 MEM 12/30 MIA 01/03 UTA 01/21 POR 02/03 LAL 03/24 PHX 03/29 MIL CHA 12/03 MIN 01/21 BKN 01/28 SAC 03/06 IND 03/13 CHI CHI 10/29 IND 11/30 LAL 12/10 MIA 12/31 MIL 01/21 SAC 03/04 LAC 03/22 DET CLE 10/29 ORL 11/23 POR 12/17 LAL 02/11 DEN 03/16 UTA DAL 01/03 WAS 02/09 UTA 03/21 GSW 03/27 OKC DEN 11/12 DET 11/20 UTA 12/02 HOU 12/30 PHI 03/08 WAS 03/18 HOU DET 12/23 GSW 02/01 NOP 04/05 TOR GSW 11/03 OKC 11/09 DAL 11/26 MIN 11/28 ATL 12/05 IND 12/30 DAL 02/01 CHA 02/15 SAC 02/25 BKN 03/18 MIL 03/31 HOU 04/08 NOP HOU 12/31 NYK 01/05 OKC 02/02 ATL 03/04 MEM 03/12 CLE 04/05 DEN IND 11/14 ORL 01/07 NYK 02/13 SAS LAC 11/21 TOR 01/04 MEM 01/16 OKC 02/26 CHA 03/06 BOS 03/29 WAS 04/05 DAL 04/10 HOU LAL 11/15 BKN 11/20 CHI 03/12 PHI 03/19 CLE MEM 12/03 LAL 12/08 POR 01/08 UTA 03/09 LAC MIA 11/01 SAC 11/10 CHI 11/12 UTA 11/17 MIL 01/21 MIL 01/23 GSW 03/04 CLE 03/11 TOR 03/19 POR 04/10 CLE MIL 11/19 GSW 02/13 DET 03/01 DEN 03/04 TOR MIN 11/12 LAC 11/13 LAL 12/06 SAS 12/11 GSW 01/28 BKN 01/30 ORL 02/04 MEM 04/01 SAC NOP 11/18 POR 12/02 LAC 12/15 IND 01/05 ATL NYK 11/02 HOU 01/02 ORL 03/29 MIA OKC 12/31 LAC 02/09 CLE 02/11 GSW 02/26 NOP 03/07 POR 04/12 DEN ORL 11/09 MIN 12/23 LAL PHI 11/07 UTA 11/19 PHX 12/02 ORL 01/18 TOR 01/24 LAC 02/11 MIA PHX 12/11 NOP 12/29 TOR 02/04 MIL 02/13 NOP 03/03 OKC 03/17 ORL POR 12/23 SAS 01/11 CLE 02/09 BOS 03/04 BKN 03/11 WAS 03/23 NYK 03/25 MIN 04/12 NOP SAC 11/08 NOP 11/23 OKC 01/04 MIA 03/22 MIL 03/27 MEM SAS 11/05 LAC 02/02 PHI 03/11 GSW 03/15 POR 03/19 SAC 03/29 GSW TOR 11/06 SAC 11/12 NYK 01/22 PHX 01/24 SAS 02/06 LAC UTA 12/01 MIA 12/08 GSW 12/14 OKC 01/13 DET 01/14 ORL 01/21 IND 01/26 LAL 01/28 MEM 03/06 NOP 03/27 NOP 04/07 MIN WAS 11/26 SAS 11/28 SAC 12/08 DEN 02/28 GSW 04/08 MIA Note: To query the situation where a team is hosting a second of back-to-back road games, and see past results in this situation, for the Nets, for example, use the following SDQL text: H and op:a and o:rest=0 and team = Nets 2016 17 NBA Schedule Log 7

REST vs NO REST and No REST vs REST Of the 1230 NBA games this regular season, 345 feature a rested team vs an unrested team. This makes the rest combination an important factor when handicapping NBA basketball. A team with at least one days rest has a definite advantage over a team that played the previous night. Young, well-disciplined teams often can perform well even though they played the previous night whereas older teams tend to struggle when playing their second game in two days especially if a long trip is involved. Of course, the number of these no rest vs rest games is determined when the schedule is finalized. The table to the right gives the number of occurrences of the rest vs no rest (R v NR) and no rest vs rest (NR v R) for each of the 30 NBA teams over the 2016-17 NBA regular season. The +/- R vs NR column on the far right gives the difference between the R v NR and NR v R columns. A high positive number indicates a favorable schedule and a high negative number indicates an unfavorable schedule. First, let s look at the Rest vs No Rest numbers. The Golden St Warriors have the greatest number of Rest vs No Rest games this season with seventeen. Next we have the Pistons, Heat and Jazz with sixteen each. On the unfortunate end of the spectrum with find the Brooklyn Nets with only five games all season in which they are rested and their opponent is not. The Knicks have only six and the Kings and Raptors have only seven. In the No Rest vs Rest column we find that the Denver Nuggets have to play fifteen games this season with no rest vs an unrested foe the most in the league. Also getting unfortunate schedules are the Lakers, Clippers, Warriors and Pelicans, each with fourteen games in which they played the previous day and their opponent did not. Now let s check out the difference column. Here the number of times a team is playing a no rest vs rest game is subtracted from the number of times a team is playing a rest vs no rest game. The higher the number, the more favorable the schedule. The Miami Heat have the highest positive differential at plus six -- playing sixteen rest vs no rest games and only ten no rest vs rest games. The Brooklyn Nets got the unluckiest schedule with regard to rest-vs-no-rest games, as they have a differential of minus seven. Clearly, these are important factors when forecasting regular season win totals. However, other factors such as personnel changes can be more important than scheduling. Also, some teams can handle the no rest vs rest combination whereas other struggle. To investigate past records in rest-vs-no-rest games, use the NBA query page at KillerSports.com. Play Smart. Play Informed. Watch the rest combinations. # of Rest Combos 2016-17 Team R vs NR NR vs R +/- R vs NR ATL 12 11 +1 BKN 5 12-7 BOS 15 10 +5 CHA 9 10-1 CHI 12 13-1 CLE 13 10 +3 DAL 10 11-1 DEN 15 15 0 DET 16 13 +3 GSW 17 14 +3 HOU 15 11 +4 IND 14 12 +2 LAC 13 14-1 LAL 10 14-4 MEM 13 9 +4 MIA 16 10 +6 MIL 8 10-2 MIN 14 10 +4 NOP 10 14-4 NYK 6 7-1 OKC 9 10-1 ORL 9 11-2 PHI 8 13-5 PHX 11 9 +2 POR 14 13 +1 SAC 7 11-4 SAS 8 12-4 TOR 7 12-5 UTA 16 13 +3 WAS 13 11 +2 TOTAL 345 345 0 NBA 1995-96 Through 2015-16: Rest vs No Rest, Overall, Home, Away W/L record SU % Avg SUm ATS Rec Avg ATSm ATS % Avg Line Overall 4657-3161 59.6% (+3.11 pts) 3929-3744-145 (+0.30 pts) 51.2% -2.8 pts Home 3865-2205 63.7% (+4.40 pts) 3016-2935-119 (+0.18 pts) 50.7% -4.2 pts Away 792-956 45.3% (-1.35 pts) 913-809-26 (+0.72 pts) 53.0% +2.1 pts 8 www.sportsdatabase.com

2016-17 Missing Match-ups There are thirty teams in the NBA, 15 in the Eastern Conference and 15 in the Western Conference. The standard scheduling for the NBA is a home-and-home series with each team in the other conference and two home-and-home series with each team in their conference. So, thirty (15 x 2) interconference matchups and 56 (14 x 4) intraconerence match-ups. This, however, adds to 86 regular season games. To eliminate four games, the schedule-makers cut four intraconference match-ups and retain all thirty interconference match-ups. Of course, the level of difficulty of a team s schedule is a strong function of which matchups are eliminated. The table below reveals the missing match-ups for each team - two home and two away. Team HOME AWAY ATL IND TOR DET BOS BKN ORL CLE DET MIA BOS IND ATL ORL MIL CHA MIL NYK PHI CHI CHI NYK CHA MIA TOR CLE PHI WAS ORL BKN DAL GSW MIN SAC OKC DEN SAS LAL MEM GSW DET BKN ATL PHI WAS GSW SAN DEN DAL UTH HOU POR LAC LAL UTH IND MIA TOR BOS ATL LAC MIN NOP POR HOU LAL HOU OKC MEM DEN MEM DEN LAL POR PHX MIA CHI BKN NYK IND MIL ORL BOS CHA NYK MIN NOP PHX LAC DAL NOP SAC UTH MIN LAC NYK MIA MIL CHI CHA OKC SAC DAL LAL SAS ORL CLE BOS MIL BRK PHI CHA DET CLE WAS PHX UTA MEM MIN SAS POR LAC MEM SAC HOU SAC POR DAL NOP OKC SAS PHX OKC GSW DEN TOR WAS CHI ATL TOR UTA GSW HOU NOP PHX WAS PHI DET TOR CLE From this table we can see, for example, that the Atlanta Hawks are missing a home games vs the Pacers and Raptors and rod games vs the Pistons and Celtics. So, over the 2016-17 season, the Pacers will host the Pacers and Raptors only once and visit the Pistons and Celtics only once. All these teams are fairly tough, so this is an advantage for the Hawks. As a comparison, the Cavs are missing four games against weak Conference opponents. They only host the 76ers once and the Wizards only visit Cleveland once. The Cavaliers also only visit the Magic and Brooklyn once, So if you live in Orlando, you will only get one chance to see Lebron at the Amway Center. next season. This is a distinct disadvantage for the Cavs. It is also worth noting that the Magic only host the Celtics once in 2016-17 and this makes their home schedule significantly easier as a result. The Pistons, like the Cavs, are also missing some easy opponents. Detroit only has one home game vs the Nets and Hawks next season and they only visit the 76ers and Wizards once in 2016-17. In the West, the obvious team to avoid is the Golden State Warriors. The Spurs have this advantage, as they have to visit the Warriors only once this season during the regular season. The Nuggets are the other team making only one trip to oracle Arena for the upcoming season. Avoiding a home game vs the Warriors are the Mavericks and Jazz. The Western Conference team with the worst home draw in this spot is the Grizzlies, as they miss out on home games vs the Nuggets and the Lakers. Become a certified SDQL Master! Email masters@sdql.com and apply now. 2016 17 NBA Schedule Log 9

OpponentS on Long Road Trips Of the 1230 NBA games this regular season, the road team is playing in at least their third straight road game in 232 of them. Continuing, we find that the road team is playing in their fourth straight road game in 166 of the 1230 NBA games this season. Finally, we see that the road team is playing in their fifth straight road game in 79 games this season. On the average, an NBA team plays 10.77 games in which they are playing in at least their third straight road game. This is slightly more than one-fourth of their road games. Similarly, an NBA team plays about 5.53 games in which they are playing in at least their fourth straight road game and about 2.63 games in which they are playing in at least their fifth straight road game. There are some interesting differences worth noting. The Hawks have only eight games all season in which they are playing in at least their third straight road game whereas the Blazers have sixteen such games. Theses are both league highs in 2016-17. The Timberwolves are the only team in the league with as few as two games in which they are playing in at least their fourth straight road game. The Kings, on the other hand have nine games this season in which they are playing in at least their fourth straight game away from home. Again, both of these are tops in the league. Finally, we see that the Timberwolves are the only team in the league with NO five game road trips all season. While these numbers are important, the real disparities come in the opponent s trips. These data are shown in the table in the next column. The Warriors get nineteen opponents playing in at least their third straight road game this season. This is not only tops in the league, it is nearly half their home games. On the other end, we find the Thunder, who only have five games this season in which their opponent is playing in at least their third straight road game. The Warriors also lead in number of opponents playing in at least their fourth road game with fourteen. This must seem unfair to the Raptors, which only get one opponent all season that is playing in at least their fourth straight road game. In the 5th+A column we note that the Denver Nuggets have the most opponents playing in at least their fifth straight road game this season with six. In the rarefied air of Denver, this could actually be a significant advantage. Finally, the Chicago Bulls are the only team in league to get NO opponents playing in at least their third straight road game. These are important factors to consider when forecasting regular season win totals. # of Opponents on Road Trips Team 3rd+A 4th+A 5th+A ATL 10 9 4 BKN 16 6 1 BOS 9 7 1 CHA 10 7 4 CHI 7 2 0 CLE 8 4 2 DAL 10 6 4 DEN 13 9 6 DET 12 4 1 GSW 19 13 3 HOU 7 3 2 IND 14 8 4 LAC 16 5 3 LAL 12 7 4 MEM 10 6 3 MIA 10 5 4 MIL 9 4 3 MIN 9 6 3 NOP 9 7 4 NYK 10 5 1 OKC 5 3 2 ORL 10 5 4 PHI 15 5 1 PHX 12 6 4 POR 11 5 2 SAC 9 4 2 SAS 9 4 2 TOR 7 1 1 UTA 16 6 2 WAS 9 4 2 To check how a team performs when their opponent is playing in at least their third road game, set the team s site to home, the opponent s previous site to away and the opponent s second previous site to away. The SDQL text is: H and op:a and opp:a The H sets the team s site to home, the op:a sets the opponent s previous site to away and the opp:a sets the opponent s second previous site to away. In the prefix op, the o represents opponent and the p represents previous. To learn more about the SDQL, check out the team trends section in this publication. 10 www.sportsdatabase.com

NBA STUDY: fourth Quarter Carryover SportsBook Breakers While momentum during a game can often be overstated, particularly in basketball where runs are a natural tendency, there are times where a performance from a single game carries over to the next game. The NBA actually is more aligned for this than the other two major sports, as there is less time to regroup between games than there is in football, and the same players are back out their from one game to the next unlike baseball where the starting pitcher makes a large difference. With the power of the Sports Data Query Language, we can take things even a step further, isolating a team s performance from a just a portion of the game. And if we are looking at momentum going into the next game, that portion we want to look at here is the fourth quarter. Our hypothesis is that a teams fourth quarter scoring performance could effect the outcome of their next game. The idea being a extremely low scoring fourth quarter might have a negative impact next game and/or that a high-scoring quarter could buoy the next game s scoring effort. This is an easy subject to investigate with the power of the Sports Data Query Language (SDQL). To explore the subject, we need to use just one parameter, p:p4, an easy shortcut for the points scored in a given quarter, in this case the fourth quarter. For an easy and quick way to explore the subject, we will look at how teams perform in this spot using the SDQL grouping feature. We defined the line with open ended text using the following two SDQLs. p:p4<=9, 11, 13, 15, and p:p4>=33, 36, 39, 42 produces the following result NOTE: Results date back to the beginning of the NFL database in 1989. With the powerful SDQL, we can easily determine the impact of going to the free throw line the previous game has on a team in their next game. To do this we use the p: prefix to signify a team s game and the shortcut FTA to designate free throw attempts. By leaving this query open ended, we can look at all results based on the previous free throw attempts. We list here all performances coming off a game with 12 free throw attempts or fewer: Previous 4Q Scoring ATS # of Games p:p4 <= 9 73-85-2 (-0.33, 46.2%) 160 p:p4 <= 11 266-277-11 (-0.04, 49.0%) 554 p:p4 <= 13 677-731-23 (-0.20, 48.1%) 1431 p:p4 <= 15 1530-1642-59 (-0.12, 48.2%) 3231 p:p4 >= 33 1810-1765-76 (-0.00, 50.6%) 3651 p:p4 >= 36 647-602-32 (0.21, 51.8%) 1281 p:p4 >= 39 207-165-11 (0.74, 55.6%) 383 p:p4 >= 42 52-43-4 (-0.37, 54.7%) 99 These grouped results do bare out our hypothesis. The low scoring fourth quarters lead to underperforming the next game, but only slightly. As the previous fourth quarter scoring reaches the high end of the spectrum, ATS performance improves, and to the point where it does become an interesting betting opportunity. By looking at the individual previous fourth quarter scoring results, we ve determined that the optimal time to start playing on in this situation is when teams have scored at least 40 points in the fourth quarter last game. Teams are 140-107-6 (0.70, 56.7%) in this spot. This is just one of over 150 systems SportsBook Breakers looks at as part of its daily handicapping. And now, with the new Killersports.com Trend Mart, you can receive daily access to active, must-have systems such as this. Visit Killersports.com/ trend_mart to learn more! is an expert at system handicapping in college and pro sports including the NBA. Using 100s of systems such as this as well as dozens of playoff systems and 1000s of team trends, SBB has established itself as a leading handicapper and is poised for a huge 2016-17 with new systems added to its database. SportsBook Breakers picks can be found at Killercappers.com. 2016 17 NBA Schedule Log 11

12 www.sportsdatabase.com

The 2016-17 KillerSports.com NBA Schedule/Log The TEAM Trends There are 420 team trends in the next section fourteen for each of the thirty NBA teams. Each trend is perfect and ten are of the ATS variety and four are OU trends. The first five trends for each team are Play-ON trends and the second grouping of five trends are Play-AGAINST trends, the next two trends are Play-OVER and the final two are Play-UNDER. The trends are presented in three columns. The first is the trend ID. This allows the trend to be referenced. For example, ATL005 in Atlanta s trend number five. The second column gives the English text of the trend. For example, The Hawks are 14-0 ATS (+8.73 ppg) with at most one day of rest after a road game in which they shot at least 50% from the arc. Note that the number in parentheses immediately following the record is the average margin by which a team has covered or failed to cover the spread. Here, the Hawks are 0-11 ATS, covering by an average of 4.18 points per game. The last column contains the Sports Data Query Language (SDQL) text that can be used to see the updated results for the trend anytime, Simply cut the SDQL text from this document and paste it into the query box on-line and click the query button run the query. SDQL text boxes are available and SportsDataBase.com, KillerSports.com. No membership or registration is needed and there is no charge to run a query. It s similar to Google. If you can Google, you can SDQL. The trends presented here and not recommended plays. In the NBA, teams often undergo significant changes in personnel and coaching over the off season. The obvious example this season is the departure of Kevin Durant from Oklahoma City. the Thunder. This should make the Thunder s trends in PAST performance less likely to predict future results. To use trends in past performance successfully a handicapper must ask two important questions: 1. Does this trend make handicapping sense? 2. Do the reasons for this past performance still exist? If the answer to both these questions is yes, further investigation is warranted. For example, checking out the average margin and the game listing to see how the trend has done THIS season. With a cursory knowledge of the Sports Data Query Language (SDQL), you will soon be researching situations of your own choosing and hence make the transition from a typical gambler to winning sports investor. 2016 17 NBA Schedule Log 13

AtlantA HAWks PLAY ON ATL001 ATL002 ATL003 ATL004 The Hawks are 14-0 ATS (+8.73 ppg) with at most one day of rest after a road game in which they shot at least 50% from the arc. The Hawks are 14-0 ATS (+10.29 ppg) with less than two days rest off a loss as a favorite in which they scored at least ten points more in the first quarter than in the fourth quarter. The Hawks are 13-0 ATS (+11.12 ppg) with less than two days rest off a road win in which they allowed at least 15+ points fewer than Vegas projected. The Hawks are 11-0 ATS (+8.59 ppg) off a double-digit win when they are facing a team that is averaging more than 15 turnovers per game. ATL005 The Hawks are 11-0 ATS (10.09 ppg) with no rest after they shot worse than 25% from beyond the arc with at least 20 attempts. team=hawks and rest<2 and p:a and p:tpp>=50 and date>=20111228 team = Hawks and rest < 2 and p:lf and p:p1 - p:p4 >= 10 and date >= 20090113 team = Hawks and rest < 2 and p:aw and p:dpa <= -15 and date >= 20081107 team = Hawks and 10 <= p:margin and oa(to) >= 15 and date >= 20131223 team = Hawks and rest = 0 and 20 <= p:tpa and p:tpp < 25 and date >= 20091205 ATL006 The Hawks are 0-14 ATS (-9.18 ppg) on the road after a game as a home dog in which they scored less than 15% of their points from free throws. team = Hawks and A and p:hd and p:pft < 15 and date >= 20050420 PLAY AGAINST ATL007 ATL008 ATL009 The Hawks are 0-14 ATS (-9.57 ppg) as a dog off a double-digit loss as a home dog in which they were outshot by at least ten percent. The Hawks are 0-13 ATS (-10.04 ppg) as a dog after a loss in which they had at least ten more turnovers than their opponent. The Hawks are 0-12 ATS (-7.08 ppg) on the road off a win when the total is at least 15 points more than their season-to-date average. team = Hawks and D and p:margin <= -10 and p:hd and p:fgp + 10 <= po:fgp and date >= 20000401 team = Hawks and D and p:l and po:to + 10 <= p:to and date >= 20040109 team = Hawks and A and p:w and ta(p:total) + 15 <= total and date >= 20020219 ATL010 The Hawks are 0-12 ATS (-10.04 ppg) as a dog off a double-digit road loss in which they had at least twice as many assists as turnovers. team = Hawks and D and p:margin <= -10 and p:a and 2 <= p:atr and date >= 20041109 PLAY OVER ATL011 ATL012 The Hawks are 14-0 OU (+12.50 ppg) as a dog with no rest off a road win in which they had at least twice as many assists as turnovers. The Hawks are 12-0 OU (+14.17 ppg) as a dog with less than two days rest off a double-digit win in which they scored at least 15 points more than Vegas projected. team = Hawks and D and rest = 0 and p:w and p:a and 2 <= p:atr and date >= 20020105 team = Hawks and D and rest < 2 and 10 <= p:margin and 15 <= p:dps and date >= 20030125 PLAY UNDER ATL013 ATL014 The Hawks are 0-15 OU (-13.37 ppg) as a home dog off a home win when they are facing a team that is getting less than 25 percent of their rebounds on the offensive end. The Hawks are 0-14 OU (-8.64 ppg) at home after a game in which they scored fewer than 25 points in the paint. team = Hawks and H and D and p:w and p:h and os(orb) / os(rebounds) < 0.25 and date >= 20070321 team = Hawks and H and p:pip < 25 and date >= 20081121 14 www.sportsdatabase.com

BOSTON CELTICS BOS001 The Celtics are 14-0 ATS (+12.32 ppg) with no rest off a win as a dog when they are facing a team with an assist-to-turnover ratio less than 1.50. team = Celtics and rest = 0 and p:w and p:d and os(assists) < 1.5 * os(to) and date >= 20031208 PLAY ON BOS002 BOS003 The Celtics are 13-0 ATS (+9.73 ppg) with rest off a double-digit loss as a dog when they are facing a team that is averaging more than 62 ppg from 2-point range. The Celtics are 13-0 ATS (+7.81 ppg) with rest off a loss as a home dog in which they shot under 60% from the free throw line. team = Celtics and 0 < rest and p:margin <= -10 and p:d and oa(points-3*tpm-ftm) > 62 and date >= 20070211 team = Celtics and 0 < rest and p:lhd and p:ftp < 60 and date >= 19951122 BOS004 The Celtics are 12-0 ATS (+5.33 ppg) as a dog off a win as a favorite when they are facing a team that is averaging more than 45 rebounds per game. team = Celtics and D and p:w and p:f and oa(rebounds) > 45 and date >= 20120311 BOS005 The Celtics are 11-0 ATS (+6.95 ppg) as a home favorite off a win when they are facing a team that is making less than 16 free throws per game. team = Celtics and HF and p:w and oa(ftm) < 16 and date >= 20130201 BOS006 The Celtics are 0-16 ATS (-9.97 ppg) as a road favorite off a loss as a road dog when they are facing a team that is averaging more than 12 offensive rebounds per game. team = Celtics and AF and p:lad and oa(orb) > 12 and date >= 19951230 PLAY AGAINST BOS007 BOS008 BOS009 The Celtics are 0-16 ATS (-9.50 ppg) as a road favorite with less than two days rest off a win that was tied five-plus times. The Celtics are 0-14 ATS (-6.71 ppg) off a home loss in which they scored at least ten points more in the first quarter than they did in the fourth quarter. The Celtics are 0-13 ATS (-8.65 ppg) as a favorite off a road win when they are facing a team that is that is getting more than 30 percent of their rebounds on the offensive end. team = Celtics and AF and p:lad and oa(orb) > 12 and date >= 19951230 team = Celtics and p:lh and p:p1 - p:p4 >= 10 and date >= 20100227 team = Celtics and F and p:w and p:a and os(orb) / os(rebounds) > 0.30 and date >= 20080408 BOS010 The Celtics are 0-13 ATS (-8.85 ppg) after a game as a road favorite in which their turnovers increased by at least ten from the game before. team = Celtics and p:af and pp:to + 10 <= p:to and date >= 20050316 PLAY OVER BOS011 BOS012 The Celtics are 14-0 OU (+18.96 ppg) as a home favorite off a loss as a favorite in which they led by double-digits. The Celtics are 13-0 OU (+16.27 ppg) with less than two days rest off a road win when they are facing a team that is averaging more than 24 assists per game. team = Celtics and H and F and p:f and p:l and 10 <= p:bl and date >= 20090102 team = Celtics and rest < 2 and p:w and p:a and oa(assists) >= 24 and date >= 20061215 PLAY UNDER BOS013 BOS014 The Celtics are 0-16 OU (-15.50 ppg) as a favorite with less than two days rest off a game as a favorite in which they committed at least 30 fouls. The Celtics are 0-16 OU (-19.16 ppg) with less than two days rest off a double-digit win as a favorite in which they had three or fewer double-digit scorers. team = Celtics and F and rest < 2 and p:f and 30 <= p:fouls and date >= 19991210 team = Celtics and rest < 2 and 10 <= p:margin and p:f and p:dds <= 3 and date >= 20030117 2016 17 NBA Schedule Log 15

Brooklyn NETS BKN001 The Nets are 14-0 ATS (+9.82 ppg) on the road with more than two days of rest off a road game. team = Nets and A and 2 < rest and p:a and date >= 20060221 PLAY ON BKN002 BKN003 BKN004 The Nets are 12-0 ATS (+7.71 ppg) on the road with rest off a loss in which they scored more than 50 points in the paint. The Nets are 12-0 ATS (+8.62 ppg) as a dog with more than one day of rest off a road loss. The Nets are 12-0 ATS (+8.08 ppg) as a dog with no rest off a loss as a dog in which they led by double-digits. team = Nets and A and 0 < rest and p:l and p:pip > 50 and date >= 20110413 team = Nets and D and 1 < rest and p:l and p:a and date >= 20140419 team = Nets and D and rest = 0 and p:dl and 10 <= p:bl and date >= 20070125 BKN005 The Nets are 11-0 ATS (+8.82 ppg) on the road with more than one day of rest off a game as a dog in which they had three or fewer double-digit scorers. team = Nets and A and 1 < rest and p:d and p:dds <= 3 and date >= 20090325 BKN006 The Nets are 0-14 ATS (-10.25 ppg) as a home dog after a game as a road dog in which they had 20+ turnovers. team = Nets and HD and p:ad and 20 <= p:to and date >= 19951212 PLAY AGAINST BKN007 BKN008 BKN009 The Nets are 0-13 ATS (-12.04 ppg) with rest off a double-digit home loss in which they had fewer than 10 turnovers. The Nets are 0-12 ATS (-7.38 ppg) off a home game in which they had six-plus double-digit scorers. The Nets are 0-12 ATS (-5.54 ppg) with no rest off a double-digit win when they are facing a team that is averaging more than five blocks per game. team = Nets and 0 < rest and p:margin <= -10 and p:h and p:to < 10 and date >= 20031114 team = Nets and p:h and p:dds >= 6 and date >= 20150429 team = Nets and rest = 0 and 10 <= p:margin and oa(blocks) > 5 and date >= 20081220 BKN010 The Nets are 0-12 ATS (-12.83 ppg) on the road with less than two days rest after they shot over 50% from the field. team = Nets and A and rest < 2 and 50 < p:fgp and date >= 20140402 PLAY OVER BKN011 BKN012 The Nets are 13-0 OU (+12.92 ppg) as a favorite off a double-digit win as a favorite when they are facing a team that is averaging less than six referreed turnovers per game. The Nets are 12-0 OU (+17.04 ppg) as a home dog after a game as a home dog in which they had a baskets assisted percentage at least ten points better than their season-to-date average. team = Nets and F and 10 <= p:margin and p:f and oa(to-o:steals) < 6 and date >= 20040206 team = Nets and H and D and p:h and p:d and ta(p:bap) + 10 <= p:bap and date >= 20100403 PLAY UNDER BKN013 BKN014 The Nets are 0-15 OU (-16.60 ppg) on the road with less than two days rest off a game as a favorite when the total is at least 15 points more than their last game. The Nets are 0-14 OU (-10.86 ppg) as a eight-plus point dog off a loss in which they had at least 15 more shots than their opponent. team = Nets and A and rest < 2 and p:f and p:total + 15 <= total and date >= 19960204 team = Nets and 8 <= line and p:l and po:fga + 15 <= p:fga and date >= 19961218 16 www.sportsdatabase.com

Charlotte hornets CHA001 The Hornets are 18-0 ATS (+12.72 ppg) when the line is within three of pick and they are off a home game in which they held their opponent to fewer than 85 points. team = Hornets and -3 <= line <= 3 and p:h and po:points<90 and po:fgp<41.5 and season >=2007 CHA002 The Hornets are 14-0 ATS (+5.64 ppg) with less than two days rest off a loss as a home favorite in which they has at least twice as many assists as turnovers. team = Hornets and rest < 2 and p:l and p:h and p:f and 2 <= p:atr and date >= 20080128 PLAY ON CHA003 The Hornets are 12-0 ATS (+10.00 ppg) at home when the line is within 3.5 of pick with less than two days rest off a loss in a road game when they are facing a team that is making more than 20 free throws per game team = Hornets and H and -3.5 <= line <= 3.5 and rest < 2 and p:l and p:a and oa(ftm) >= 20 and date >= 20050321 CHA004 The Hornets are 11-0 ATS (+9.14 ppg) with less than two days rest off a doubledigit win as a dog in which they had six-plus double-digit scorers. team = Hornets and rest < 2 and 10 <= p:margin and p:d and p:dds >= 6 and date >= 20051105 CHA005 The Hornets are 11-0 ATS (+12.64 ppg) as a dog off a home win in which they scored at least ten points more in the fourth quarter than they did in the first quarter. team = Hornets and D and p:hw and p:p1 - p:p4 <= -10 and date >= 20080308 CHA006 The Hornets are 0-13 ATS (-8.23 ppg) as a dog off a road win when they allowed 100+ points in each of their last two games. team = Hornets and D and p:w and p:a and 100 <= ppo:points and 100 <= po:points and date >= 20050204 PLAY AGAINST CHA007 CHA008 CHA009 The Hornets are 0-12 ATS (-14.12 ppg) as a eight-plus point dog off a game as a dog in which their opponent shot under 40% from the field. The Hornets are 0-12 ATS (-11.92 ppg) at home with no rest off a loss as a dog when they are facing a team that is averaging less than 20 points per game from threes. The Hornets are 0-11 ATS (-10.09 ppg) as a favorite with less than two days rest when they are off two games in which more than 65 percent of their field goals were assisted. team = Hornets and 8 <= line and p:d and po:fgp < 40 and date >= 20110305 team = Hornets and H and rest = 0 and p:l and p:d and oa(3*tpm) < 20 and date >= 20100410 team = Hornets and F and rest < 2 and 65 < p:bap and 65 < pp:bap and date >= 20090403 CHA010 The Hornets are 0-11 ATS (-8.23 ppg) with rest when they are off two consecutive games in which they had six-plus double-digit scorers. team = Hornets and 0 < rest and p:dds >= 6 and pp:dds >= 6 and pp:season = season and date >= 20050416 PLAY OVER CHA011 The Hornets are 13-0 OU (+11.96 ppg) as a road dog with rest when they are facing a team that is averaging less than four blocks per game. CHA012 The Hornets are 11-0 OU (+21.77 ppg) off a home loss in which they had at least 15 more shots than their opponent. team = Hornets and A and D and 0 < rest and oa(blocks) < 4 and date >= 20130206 team = Hornets and p:l and p:h and po:fga + 15 <= p:fga and date >= 20060203 PLAY UNDER CHA013 CHA014 The Hornets are 0-15 OU (-14.53 ppg) at home when the line is within three of pick with less than two days rest after a game as a road dog that was tied five-plus times. The Hornets are 0-12 OU (-9.08 ppg) with more than one day of rest off a loss as a road dog when they are facing a team that is averaging more than 23 fouls per game. team = Hornets and H and -3 <= line <= 3 and rest < 2 and p:a and p:d and p:tt >= 5 and date >= 20110115 team = Hornets and 1 < rest and p:l and p:a and p:d and oa(fouls) > 23 and date >= 20060409 2016 17 NBA Schedule Log 17

CHICAGO BULLS CHI001 The Bulls are 18-0 ATS (+8.97 ppg) at home with no rest off a game as a favorite when when they are facing a team that is making more than 20 free throws per game. team = Bulls and H and rest = 0 and p:f and oa(ftm) >= 20 and date >= 19960302 PLAY ON CHI002 CHI003 CHI004 The Bulls are 15-0 ATS (+9.83 ppg) as a dog off a home game in which they scored at least 30% of their points from threes. The Bulls are 14-0 ATS (+12.82 ppg) as a road dog after a game in which they had three or fewer double-digit scorers. The Bulls are 14-0 ATS (+10.11 ppg) when the line is within three of pick with rest off a home win in which at least 70 percent of their field goals were assisted. team = Bulls and D and p:h and 30 <= p:ptp and date >= 20050319 team = Bulls and AD and p:dds <= 3 and date >= 20120510 team = Bulls and -3 <= line <= 3 and 0 < rest and p:w and p:h and 70 <= p:bap and date >= 20040217 CHI005 The Bulls are 13-0 ATS (+11.85 ppg) as a road favorite with less than two days rest off a win in which they scored a least 18 fast break points. team = Bulls and AF and rest < 2 and p:w and p:fbp >= 18 and date >= 20110226 CHI006 The Bulls are 0-14 ATS (-13.00 ppg) as a home favorite with more than one day of rest when they are facing a team that is averaging fewer than 20 fouls per game. team = Bulls and H and F and 1 < rest and oa(fouls) < 20 and date >= 20101201 PLAY AGAINST CHI007 CHI008 CHI009 The Bulls are 0-14 ATS (-9.68 ppg) as a dog with rest off a road game when they are facing a team that is averaging more than seven referreed turnovers per game. The Bulls are 0-12 ATS (-8.83 ppg) at home off a win as a dog in which there were eight-plus lead changes. The Bulls are 0-11 ATS (-13.64 ppg) as a rested dog off a road win when facing a team that is getting less than 25 percent of their rebounds on the offensive end. team = Bulls and D and 0 < rest and p:a and oa(to-o:steals) > 7 and date >= 20091101 team = Bulls and H and p:w and p:d and p:lc >= 8 and date >= 20121126 team = Bulls and D and 0 < rest and p:w and p:a and os(orb) / os(rebounds) < 0.25 and date >= 20130508 CHI010 The Bulls are 0-11 ATS (-7.82 ppg) as a dog with less than two days rest off a win when they are facing a team that is averaging fewer than ten offensive rebounds per game. team = Bulls and D and rest < 2 and p:w and oa(orb) < 10 and date >= 20140303 PLAY OVER CHI011 CHI012 The Bulls are 16-0 OU (+11.47 ppg) as a dog with less than two days rest after they committed at least 30 fouls. The Bulls are 15-0 OU (+12.67 ppg) as a road dog with rest off a home loss in which they had more than eight times as many field goal attempts as turnovers. team = Bulls and D and rest < 2 and 30 <= p:fouls and date >= 20050122 team = Bulls and AD and 0 < rest and p:hl and 8 * p:to < p:fga and date >= 20010114 PLAY UNDER CHI013 CHI014 The Bulls are 0-17 OU (-13.91 ppg) as a favorite with rest off a game as a dog in which they scored at least ten points more in the first quarter than they did in the fourth quarter. The Bulls are 0-15 OU (-12.90 ppg) as a favorite with rest off a double-digit road loss when they are facing a team that is getting more than 20 percent of their points at the free throw line. team = Bulls and F and 0 < rest and p:d and p:p1 - p:p4 >= 10 and date >= 20010226 team = Bulls and F and 0 < rest and p:margin <= -10 and p:a and os(ftm) / os(points) >= 0.2 and date >= 20050415 18 www.sportsdatabase.com