NBA Schedule/Log

More documents

Recommendations

Info

OPPONENTS ON LONG ROAD TRIPS When the league made the schedule in December, it had to arrange 33 home games and 33 road games for each team. The result is 66 regular season games that contain numerous homestands and road trips. The number of consecutive road games a team must play over the entire season does not vary greatly from team to team because of the constraint that each team must have 33 home games and 33 road games. There are no such restrictions, however, on the number of times a team hosts an opponent that is playing in at least their third straight away game. Theoretically, a team can face an opponent that is playing in at least their third straight road game in all 33 of their home games. This season, the average number of times a team will face an opponent that is playing in at least their third straight road game in 2011-12 is 8.5. Continuing, the average number of times a team will face an opponent that is playing in at least their fourth straight road game is 4.4 and the average number of times a team will face an opponent that is playing in at least their fifth straight road game is 2.2. Of course, due to the vagaries of the schedule, some teams get a lot more than average and other a lot fewer than the league average. The interesting feature to NBA futures bettors is how many times each team hosts an opponent that is playing in at least their third straight road game. The accompanying table shows just that. The first column gives the name of the team, the second column gives the number of times each team is hosting an opponent that is playing in AT LEAST their third straight road game. The third column gives the number of times each team is hosting an opponent that is playing in AT LEAST their fourth straight road game. And, finally, the last column gives the number of times each team is hosting an opponent that is playing in AT LEAST their fifth straight road game. The range in the second column is significant. The New Jersey host thirteen opponents that are playing in at least their third straight road game – highest in the league. They are followed by the Knicks and Nuggets each with twelve. On the unlucky end of the scheduling spectrum, we find the Miami Heat, with only four games this season in which they opponent is playing in at least their third straight road game. They are followed by the Grizzlies, Spurs and Wizards, each with only five opponents that will be playing in at least their third straight road game. In the “Opp 4+A” column we see the discrepancies increase. The New York Knicks get eight opponents playing in at least their fourth straight away game. The Rockets and Magic have only ONE such opponent. Note that a complete listing of games where their opponent is playing in at least their third straight away game appears on the SDQL Hint 16 | KillerSports.com team’s schedule pages, in section two of this book. Continuing, we see that the Nuggets and Raptors have five opponents this season that are playing in at least their fifth straight road game, whereas the Houston Rockets have NONE. Number of Opp’s in 3+ Away; 2011-12 Team Opp 3+ A Opp 4+ A Opp 5+ A ATL 10 4 1 BOS 8 5 1 CBC 10 6 4 CHI 8 5 3 CLE 11 6 3 DAL 6 4 2 DEN 12 6 5 DET 7 4 2 GSW 8 3 2 HOU 7 1 0 IND 6 3 1 LAC 10 7 2 LAL 11 4 2 MEM 5 2 2 MIA 4 2 1 MIL 7 6 2 MIN 8 3 1 NJN 13 6 4 NOR 9 5 3 NYK 12 8 4 OKC 10 4 3 ORL 7 1 1 PHI 8 4 1 PHO 10 6 4 POR 9 4 1 SAC 11 6 1 SAN 5 3 2 TOR 7 6 5 UTH 11 6 2 WAS 5 3 3 AVG 8.5 4.4 2.3 The number of times a team hosts an opponent that is playing a long road trip is yet another factor that should be considered when playing NBA Futures. Play Smart. Play Informed. Get on KillerSports.com and find out just how each team performs vs an opponent that is on a long road trip. To see a team’s results, in this case the Thunder’s, when facing an opponent who is playing in at least their third straight road game, use the SDQL text: site=home and op:site=away and opp:site=away and team=Thunder
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/nfl.py/query To see all the NBA games in which a team committed at least twenty-five turnovers and won the game, enter TO>=25 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” directs the “points” parameter to the opponent. 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 2011–2012 NBA Schedule Log | 17
Page 1 and 2: The 2011-12 KillerSports.com NBA Sc
Page 3 and 4: 2011-2012 NBA SCHEDULE OVERVIEW The
Page 5 and 6: 2011-2012 NBA OPPONENT BREAKDOWN CO
Page 7 and 8: 2011-2012 BACK-TO-BACK ROAD GAmES (
Page 9 and 10: BACK-TO-BACK ROAD GAmES - HOSTING T
Page 11 and 12: 2011-2012 DAYS REST DISTRIBUTION A
Page 13 and 14: PLAYING FOUR GAmES IN FIVE DAYS (CO
Page 15: THIRD GAmE IN THREE DAYS 2011-2012
Page 19 and 20: The 2011-12 KillerSports.com NBA Sc
Page 21 and 22: ATLANTA HAWKS 2011-12 Schedule DATE
Page 23 and 24: BOSTON CELTICS 2011-12 Schedule DAT
Page 25 and 26: CHARLOTTE BOBCATS 2011-12 Schedule
Page 27 and 28: CHICAGO BULLS 2011-12 Schedule DATE
Page 29 and 30: CLEVELAND CAVALIERS 2011-12 Schedul
Page 31 and 32: DALLAS mAVERICKS 2011-12 Schedule D
Page 33 and 34: DENVER NUGGETS 2011-12 Schedule DAT
Page 35 and 36: DETROIT PISTONS 2011-12 Schedule DA
Page 37 and 38: GOLDEN STATE WARRIORS 2011-12 Sched
Page 39 and 40: HOUSTON ROCKETS 2011-12 Schedule DA
Page 41 and 42: INDIANA PACERS 2011-12 Schedule DAT
Page 43 and 44: LA CLIPPERS 2011-12 Schedule DATE D
Page 45 and 46: LA LAKERS 2011-12 Schedule DATE DAY
Page 47 and 48: mEmPHIS GRIZZLIES 2011-12 Schedule
Page 49 and 50: mIAmI HEAT 2011-12 Schedule DATE DA
Page 51 and 52: mILWAUKEE BUCKS 2011-12 Schedule DA
Page 53 and 54: mINNESOTA TImBERWOLVES 2011-12 Sche
Page 55 and 56: NEW JERSEY NETS 2011-12 Schedule DA
Page 57 and 58: NEW ORLEANS HORNETS 2011-12 Schedul
Page 59 and 60: NEW YORK KNICKS 2011-12 Schedule DA
Page 61 and 62: OKLAHOmA CITY THUNDER 2011-12 Sched
Page 63 and 64: ORLANDO mAGIC 2011-12 Schedule DATE
Page 65 and 66: PHILADELPHIA 76ERS 2011-12 Schedule
Page 67 and 68:
PHOENIX SUNS 2011-12 Schedule DATE
Page 69 and 70:
PORTLAND TRAILBLAZERS 2011-12 Sched
Page 71 and 72:
SACRAmENTO KINGS 2011-12 Schedule D
Page 73 and 74:
SAN ANTONIO SPURS 2011-12 Schedule
Page 75 and 76:
TORONTO RAPTORS 2011-12 Schedule DA
Page 77 and 78:
UTAH JAZZ 2011-12 Schedule DATE DAY
Page 79 and 80:
WASHINGTON WIZARDS 2011-12 Schedule
Page 81 and 82:
The 2011-12 KillerSports.com NBA Sc
Page 83 and 84:
BOSTON CELTICS PLAY ON TREND ID DES
Page 85 and 86:
CHICAGO BULLS PLAY ON TREND ID DESC
Page 87 and 88:
DALLAS mAVERICKS PLAY ON TREND ID D
Page 89 and 90:
DETROIT PISTONS PLAY ON TREND ID DE
Page 91 and 92:
HOUSTON ROCKETS PLAY ON TREND ID DE
Page 93 and 94:
LA CLIPPERS PLAY ON TREND ID DESCRI
Page 95 and 96:
mEmPHIS GRIZZLIES PLAY ON TREND ID
Page 97 and 98:
mILWAUKEE BUCKS PLAY ON TREND ID DE
Page 99 and 100:
NEW JERSEY NETS PLAY ON TREND ID DE
Page 101 and 102:
NEW YORK KNICKS PLAY ON TREND ID DE
Page 103 and 104:
ORLANDO mAGIC PLAY ON TREND ID DESC
Page 105 and 106:
PHOENIX SUNS PLAY ON TREND ID DESCR
Page 107 and 108:
SACRAmENTO KINGS PLAY ON TREND ID D
Page 109 and 110:
TORONTO RAPTORS PLAY ON TREND ID DE
Page 111 and 112:
WASHINGTON WIZARDS PLAY ON TREND ID
show all

NBA Schedule/Log

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?