Analysis of basketball through objective evidence
http://www.apbr.org/metrics/
Well, I had the Spurs with +5.5 going into the finals. Using the minute distribution and the updated values after those 5 games, it becomes +6.0. Though, the difference was even bigger than that. If you need some sort of "proof" for that, please click: http://sportforen.de/showthread.php?590 ... st50557370 (at the end I wrote: Im bisherigen Verlauf der Playoffs spielten die Heat im Schnitt wie ein +8 Team, die Spurs wie ein +13.5 Team, das ist schon ein erheblicher Unterschied. Rough translation: Heat played like +8, Spurs like +13.5.)colts18 wrote:So far the first 4 games seem like vindication for xRPM predicting that the Spurs would dominate the Heat. I don't think any other system had the Spurs as a 80% favorite.
I also did a quick finals prediction recap based on my regular season player ratings. The general regular season team rating had the Spurs +2.8, after seeing how playing time was allotted for the finals, +3.6. I didn't use any playoff data, which obviously would have made the Spurs an even bigger favorite - I was just trying to show some of the validity of the regular season player ratings. I talk about Kawhi Leonard some too:mystic wrote:Well, I had the Spurs with +5.5 going into the finals. Using the minute distribution and the updated values after those 5 games, it becomes +6.0. Though, the difference was even bigger than that. If you need some sort of "proof" for that, please click: http://sportforen.de/showthread.php?590 ... st50557370 (at the end I wrote: Im bisherigen Verlauf der Playoffs spielten die Heat im Schnitt wie ein +8 Team, die Spurs wie ein +13.5 Team, das ist schon ein erheblicher Unterschied. Rough translation: Heat played like +8, Spurs like +13.5.)colts18 wrote:So far the first 4 games seem like vindication for xRPM predicting that the Spurs would dominate the Heat. I don't think any other system had the Spurs as a 80% favorite.
Against Vegas I was 4-1, with the lines:
G1: -8.5 vs. -4.5
G2: -8.5 vs. -4
G3: +2.5 vs. -4
G4: +2.6 vs. -5
G5: -8.8 vs. -5.5
Not a particular great RMSE (was better last season), but still clearly better than Vegas. The interesting thing for me was the pretty obvious gambler's fallacy in G4, when the Heat all of the sudden were thought to be more likely to win that game after the game 3 loss. I used a -3 HCA, if we apply that to Vegas, they actually had the Heat in average for the first 4 games as +0.5 over the Spurs on neutral court.
As point of comparison: Last season's finals I had the Spurs with +1.8, they ended up being +1.2, I went 4-3 against Vegas, two times lost due to last minute actions, where luck was a big factor for the Heat. Vegas had the Heat in average at +2.9.
I admit to being somewhat mystified.mystic wrote:... I used a minute and pace prediction, got the Heat with +8 per 100 poss, the Bobcats with -4 per 100 poss with about 87 pace for +10.5...SRS differential is meaningless given the severe differences in terms of minute distribution. Gary Neal is a -4 player in my metric, for example, I expected him to get 24 mpg ... I had the Heat clearly better than their RS SRS, the Bobcats being worse. Again, look at the minute distribution, then use a reliable player metric and you get a MUCH better impression about the strength of the teams.Mike G wrote:The SRS differential for Mia-Cha is about 5 ppg. You give Mia another expected 6 ppg, based on ... ?
- Jefferson averaging 8 fewer mpg, picked up by McRoberts? Everyone else within 3 mpg of RS for Cha
- Wade was full-time, Ray played less, Battier not at all; Haslem and Jones played more than usual.
My lines I played in reality for the Heat vs Bobcats series:Mike G wrote:After the fact "predictions" are something else. Postdictions, perhaps.
I predicted player minutes based on a model which took RS minutes and the development in average for PS minutes of the past into account. That wasn't just "guessing". I also didn't guess at player values, but I use a model based on my own boxscore-based SPM model and RAPM (combined via OLS) for those values. That model and my minute prediction combined gave me about 60% wins against Vegas over the past 3 seasons (only played this season, just tested it for 2012 and 2013 with PREDICTIONS based on the model)! Matter of fact is: RS SRS is a worse predictor than that.Mike G wrote: Guessing at player minutes, and then guessing at player values -- while dismissing SRS as "meaningless" -- I don't see how you'd get improved predictions.
Jefferson averaging 8 fewer mpg, picked up by McRoberts.. Everyone else within 3 mpg of RS for Cha
See, it starts with your assumption that a team would be a +2 team based on a smaller sample. Maybe the Bobcats weren't a +2 team to begin with? Because, quite frankly, they weren't. That's why I pointed out before that runs in smaller samples happen, but I would never base a prediction on such thing. But I think we will run in circles here, because you will stick with your belief that the Bobcats were much better than I saw them (or Colts18 prediction in this thread using RPM as the player metric), and I will not go further into details, because, tbh, I don't see how that would be beneficial for me.Mike G wrote:So, how does a +2 team become a -4 team with your predicted minutes redistribution?
This is way off the main topic, but it sounded weird to me too, so I went back and checked what we had. I agree that CHA was projected to be a bit worse than in the regular season (and the Heat way better), due in large part to Gary Neal presumably getting mucho minutes, and Al probably getting less than normal minutes. But that makes them maybe a -1.5 or -2 or something (CHA's SRS was -1). I don't see that -4 there anywhere. Al was crippled in that series which isn't accounted for in that -2ish estimate. But I don't see a -4 for that Bobcats team, if you ignore the crippled issue.Mike G wrote:So, how does a +2 team become a -4 team?
From my prediction model for the playoffs (before the 1st game was played):talkingpractice wrote: But I don't see a -4 for that Bobcats team, if you ignore the crippled issue.
Code: Select all
Name min v
Kemba Walker 38 1.02
Josh McRoberts 36 0.08
Al Jefferson 35 0.82
Gary Neal 30 -4.21
Gerald Henderson 30 -1.58
Michael Kidd-Gilchri 24 0.02
Bismack Biyombo 13 -2.46
Anthony Tolliver 12 0.45
Chris Douglas-Robert 12 -1.33
Luke Ridnour 10 -2.73