Talisman Red's NBA Computer Ratings
Presented here are computer ratings and rankings for NBA and, hopefully, a system that can come somewhat close to predicting final game scores. The Predictions tab includes games scheduled for the next few days.
To calculate a hypothetical margin of victory for any other matchup, just use the "Points" column. The home advantage fluctuates based on games played, but is consistently about 2.5 to 3 points.
For the last couple of years, all overtime games are recorded as "ties" because this helps the score predictions be slightly more accurate. 20 Jan 2026 update: The performance this year has been, well, woof. I noticed an error that was keeping way too many old games in the predictions file. Hopefully things will improve from here forward.
If you need original text files for anything below, check the Description tab. Let me know if you see any issues. Thanks and glad you're here!
Everything is now in one scrollable page, instead of the tabs which required Javascript. Easier for phone users, I hope. Scrapers should not be impacted.
Ratings
NBA Computer Ratings Last updated 10-Mar-2026 08 AM ET Rank Team W L OT Rating Points BCS 1 Oklahoma City 47 15 4 3.22 59.27 2 2 San Antonio 46 17 1 3.10 57.82 1 3 Detroit 43 17 3 2.40 56.61 3 4 Boston 41 21 2 2.38 56.56 4 5 New York 39 24 3 1.91 55.79 7 6 Cleveland 40 22 3 1.90 54.73 6 7 Houston 38 18 7 1.82 54.03 5 8 Minnesota 39 22 3 1.25 52.95 8 9 Denver 36 23 6 1.06 53.04 10 10 Charlotte 30 32 3 0.99 54.52 17 Rank Team W L OT Rating Points BCS 11 Orlando 33 26 4 0.98 52.19 9 12 Miami 35 29 1 0.88 53.29 14 13 Toronto 34 25 4 0.72 51.71 13 14 Phoenix 36 26 2 0.62 50.83 11 15 LA Clippers 30 32 2 0.53 51.57 15 16 LA Lakers 39 25 0 0.49 50.27 12 17 Atlanta 32 31 1 0.28 50.56 16 18 Golden State 30 31 3 0.13 51.10 19 19 Philadelphia 30 27 7 -0.17 48.69 18 20 Portland 30 33 2 -0.57 47.62 20 Rank Team W L OT Rating Points BCS 21 Milwaukee 25 34 4 -1.18 45.73 21 22 Chicago 26 37 1 -1.49 45.67 22 23 New Orleans 20 41 5 -1.60 46.30 23 24 Memphis 21 39 3 -1.90 46.32 25 25 Dallas 19 40 5 -1.92 45.93 24 26 Brooklyn 17 44 3 -2.64 42.93 26 27 Utah 17 43 5 -2.73 42.76 27 28 Indiana 14 48 2 -3.29 41.60 29 29 Washington 16 45 2 -3.54 39.53 28 30 Sacramento 13 49 3 -3.63 40.11 30
Ratings by Division
Teams are sorted by computer ranking (in parentheses), not necessarily by win-loss percentage. As on the front page, overtime games get recorded as ties to make the predictions hopefully more accurate. Playoff games between division teams end up getting counted here, too.
NBA Computer Ratings (Last updated 10-Mar-2026 08 AM ET) --- Atlantic CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Boston 7 5 2 41 21 2 2.38 ( 4) 56.56 34 16 0 -0.28 ( 28) 2 New York 11 3 0 39 24 3 1.91 ( 5) 55.79 28 21 3 0.04 ( 14) 3 Toronto 3 10 1 34 25 4 0.72 ( 13) 51.71 31 15 3 -0.16 ( 25) 4 Philadelphia 8 6 1 30 27 7 -0.17 ( 19) 48.69 22 21 6 -0.18 ( 27) 5 Brooklyn 3 8 2 17 44 3 -2.64 ( 26) 42.93 14 36 1 -0.04 ( 18) --- Central CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Detroit 9 4 1 43 17 3 2.40 ( 3) 56.61 34 13 2 0.12 ( 8) 2 Cleveland 8 4 1 40 22 3 1.90 ( 6) 54.73 32 18 2 0.25 ( 2) 3 Milwaukee 8 5 0 25 34 4 -1.18 ( 21) 45.73 17 29 4 0.09 ( 11) 4 Chicago 4 10 0 26 37 1 -1.49 ( 22) 45.67 22 27 1 0.10 ( 10) 5 Indiana 3 9 0 14 48 2 -3.29 ( 28) 41.60 11 39 2 0.03 ( 15) --- Southeast CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Charlotte 9 5 0 30 32 3 0.99 ( 10) 54.52 21 27 3 -0.00 ( 16) 2 Orlando 7 5 0 33 26 4 0.98 ( 11) 52.19 26 21 4 0.11 ( 9) 3 Miami 6 5 0 35 29 1 0.88 ( 12) 53.29 29 24 1 -0.03 ( 17) 4 Atlanta 7 6 0 32 31 1 0.28 ( 17) 50.56 25 25 1 0.14 ( 6) 5 Washington 2 10 0 16 45 2 -3.54 ( 29) 39.53 14 35 2 -0.15 ( 24) --- Northwest CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Oklahoma City 8 3 2 47 15 4 3.22 ( 1) 59.27 39 12 2 -0.06 ( 19) 2 Minnesota 8 4 1 39 22 3 1.25 ( 8) 52.95 31 18 2 -0.45 ( 30) 3 Denver 5 4 2 36 23 6 1.06 ( 9) 53.04 31 19 4 -0.30 ( 29) 4 Portland 5 7 0 30 33 2 -0.57 ( 20) 47.62 25 26 2 0.08 ( 12) 5 Utah 1 9 1 17 43 5 -2.73 ( 27) 42.76 16 34 4 -0.13 ( 21) --- Pacific CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Phoenix 10 6 0 36 26 2 0.62 ( 14) 50.83 26 20 2 0.26 ( 1) 2 LA Clippers 8 5 0 30 32 2 0.53 ( 15) 51.57 22 27 2 0.13 ( 7) 3 LA Lakers 8 7 0 39 25 0 0.49 ( 16) 50.27 31 18 0 0.05 ( 13) 4 Golden State 6 6 0 30 31 3 0.13 ( 18) 51.10 24 25 3 0.15 ( 5) 5 Sacramento 2 10 0 13 49 3 -3.63 ( 30) 40.11 11 39 3 0.21 ( 4) --- Southeast CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 San Antonio 10 3 1 46 17 1 3.10 ( 2) 57.82 36 14 0 0.22 ( 3) 2 Houston 6 5 1 38 18 7 1.82 ( 7) 54.03 32 13 6 -0.13 ( 22) 3 New Orleans 5 5 3 20 41 5 -1.60 ( 23) 46.30 15 36 2 -0.08 ( 20) 4 Memphis 4 6 2 21 39 3 -1.90 ( 24) 46.32 17 33 1 -0.18 ( 26) 5 Dallas 3 9 1 19 40 5 -1.92 ( 25) 45.93 16 31 4 -0.15 ( 23)
Division Rankings
The average computer rating of all teams in a division is shown here.
Rank Conference Mean Rating ---- ------------------------- ----------- 1 Northwest 0.45 2 Atlantic 0.44 3 Southeast -0.08 4 Southeast -0.10 5 Central -0.33 6 Pacific -0.37
Game Predictions
These predictions already include home advantage, if necessary.
PREDICTIONS FOR UPCOMING GAMES Date Away Team Home Team Total Prediction ----------- -------------------- -------------------- ----- -------------- 10-Mar-2026 Memphis Philadelphia 227 HOME by 3.50 10-Mar-2026 Detroit Brooklyn 223 AWAY by -12.55 10-Mar-2026 Washington Miami 244 HOME by 14.88 10-Mar-2026 Dallas Atlanta 231 HOME by 5.75 10-Mar-2026 Toronto Houston 218 HOME by 3.45 10-Mar-2026 Phoenix Milwaukee 218 AWAY by -3.97 10-Mar-2026 Boston San Antonio 223 HOME by 2.39 10-Mar-2026 Chicago Golden State 242 HOME by 6.55 10-Mar-2026 Charlotte Portland 238 AWAY by -5.76 10-Mar-2026 Indiana Sacramento 232 AWAY by -0.36 10-Mar-2026 Minnesota LA Lakers 238 AWAY by -1.55 11-Mar-2026 Cleveland Orlando 230 AWAY by -1.41 11-Mar-2026 Toronto New Orleans 234 AWAY by -4.29 11-Mar-2026 New York Utah 237 AWAY by -11.90 11-Mar-2026 Houston Denver 227 HOME by 0.13 11-Mar-2026 Charlotte Sacramento 232 AWAY by -13.28 11-Mar-2026 Minnesota LA Clippers 231 AWAY by -0.25 12-Mar-2026 Philadelphia Detroit 219 HOME by 9.05 12-Mar-2026 Phoenix Indiana 227 AWAY by -8.10 12-Mar-2026 Washington Orlando 236 HOME by 13.79 12-Mar-2026 Brooklyn Atlanta 218 HOME by 8.75 12-Mar-2026 Milwaukee Miami 231 HOME by 8.68 12-Mar-2026 Denver San Antonio 233 HOME by 5.90 12-Mar-2026 Boston Oklahoma City 207 HOME by 3.83 12-Mar-2026 Chicago LA Lakers 242 HOME by 5.72 12-Mar-2026 Dallas Memphis 233 HOME by 1.51 13-Mar-2026 Memphis Detroit 214 HOME by 11.42 13-Mar-2026 New York Indiana 223 AWAY by -13.07 13-Mar-2026 Phoenix Toronto 221 HOME by 2.02 13-Mar-2026 New Orleans Houston 225 HOME by 8.86 13-Mar-2026 Cleveland Dallas 223 AWAY by -7.67 13-Mar-2026 Minnesota Golden State 238 AWAY by -0.72 13-Mar-2026 Utah Portland 245 HOME by 5.99 13-Mar-2026 Chicago LA Clippers 235 HOME by 7.02 14-Mar-2026 Brooklyn Philadelphia 215 HOME by 6.88 14-Mar-2026 Milwaukee Atlanta 225 HOME by 5.96 14-Mar-2026 Washington Boston 221 HOME by 18.15 14-Mar-2026 Orlando Miami 236 HOME by 2.22 14-Mar-2026 Charlotte San Antonio 234 HOME by 4.43 14-Mar-2026 Denver LA Lakers 233 AWAY by -1.65 14-Mar-2026 Sacramento LA Clippers 227 HOME by 12.59 15-Mar-2026 Minnesota Oklahoma City 222 HOME by 7.45 15-Mar-2026 Dallas Cleveland 230 HOME by 9.92 15-Mar-2026 Detroit Toronto 224 AWAY by -3.77 15-Mar-2026 Indiana Milwaukee 224 HOME by 5.26 15-Mar-2026 Portland Philadelphia 230 HOME by 2.19 15-Mar-2026 Golden State New York 219 HOME by 5.82 15-Mar-2026 Utah Sacramento 238 AWAY by -1.53
Description
Original Text Files
Feel free to download these; if you use them elsewhere, give credit to talismanred.com.
- Rankings
- Division Standings (but sorted by computer rating)
- Game Predictions
What is this about?
Computer ratings are the starting point for Vegas oddsmakers, and have traditionally done reasonably well at predicting game winners. On this page, I share my own formula, which I've been producing for one sport or another for about 20 years. If you're familiar with ratings you've probably heard of the others: Sagarin, Massey, and more.
So it's just a math formula?
Yep, that's all that computer ratings are. You can do it this way, or you can do like they do for college sports and do a human "poll" (coaches, writers, whoever).
The formula here is one that I developed quite a few years ago to try and "compete" with all the other folks who are doing it. That's where the predictions come from -- incorporating historical games and trying to use those to figure out what will happen next. It includes scores, dates, and locations, but no other information. No information about injuries, pace or speed of the game, shooting percentages, etc. Those things *do* matter, but they aren't factored in here.
Are the predictions any good?
In 2023-24, my NBA ratings predicted 64.2% of the correct game winners. By comparison, Jeff Sagarin's method got 65.8% correct. Over a season of about 850 games, that is a 10-15 game difference. I'll let you decide how much difference there is for 10-15 games out of 850. (I suspect that most of that was early in the season, when it's more difficult to know what a team's true strength is going to be. Jeff's preseason algorithm is probably more sophisticated than mine.)
That said, the Vegas line got 68.0% of winners. You just cannot beat a human touch!
In 2025-26, about mid-January I noticed that this year's predictions were doing terribly (61%, compared to most of the other computers at 65-66%). So I did what any self-respecting programmer would do, I adjusted the formula in hopes of improving accuracy. I'll report back with the results. One of the big factors is how much recent information do you keep when trying to predict a team's performance. A couple weeks? A month? The whole season?
Ratings Description
This rating system uses a formula developed by the owners of talismanred.com. It is explained in more detail over on the college football page, but the bottom line is that it can be used both for ranking teams as well as predicting future scores. In some circles, you'll see that referred to as both "retrodictive" and "predictive."
About the Author
I am a faculty member at Indiana University in Bloomington, with a Ph.D. in Atmospheric Science from the University of Alabama in Huntsville. For my day job, in addition to teaching lots of courses I have research interests in the broad areas of thunderstorms and numerical weather prediction (forecasting the weather using computers). Contact me using this email form if you have questions or non-hateful comments.