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 25-Mar-2026 08 AM ET Rank Team W L OT Rating Points BCS 1 Oklahoma City 53 15 4 3.37 59.90 2 2 San Antonio 53 18 1 3.17 58.39 1 3 Detroit 50 18 3 2.49 57.14 3 4 Boston 45 24 2 2.06 56.11 5 5 New York 46 25 3 1.89 55.58 6 6 Cleveland 45 24 3 1.80 54.58 4 7 Denver 42 23 7 1.68 54.72 8 8 Charlotte 36 33 3 1.45 55.86 12 9 Houston 42 22 7 1.42 53.12 7 10 Minnesota 43 26 3 1.14 53.04 10 Rank Team W L OT Rating Points BCS 11 LA Lakers 45 26 1 1.02 51.67 9 12 Atlanta 39 32 1 0.82 52.03 11 13 Toronto 38 29 4 0.66 51.80 13 14 Phoenix 39 32 2 0.45 51.30 14 15 LA Clippers 33 36 3 0.38 51.65 17 16 Orlando 35 32 5 0.37 51.17 15 17 Miami 37 34 1 0.35 51.93 18 18 Philadelphia 35 30 7 -0.15 48.34 16 19 Portland 35 36 2 -0.24 48.68 19 20 Golden State 31 36 5 -0.26 50.13 20 Rank Team W L OT Rating Points BCS 21 New Orleans 24 44 5 -1.03 47.80 22 22 Chicago 28 41 2 -1.40 45.84 23 23 Milwaukee 27 40 4 -1.57 44.32 21 24 Dallas 21 44 7 -1.81 45.56 24 25 Memphis 22 46 3 -2.19 44.96 25 26 Utah 18 49 5 -2.79 42.33 26 27 Brooklyn 17 52 3 -3.09 41.35 28 28 Sacramento 17 53 3 -3.22 39.91 27 29 Indiana 15 55 2 -3.24 41.38 30 30 Washington 16 52 3 -3.52 39.42 29
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 25-Mar-2026 08 AM ET) --- Atlantic CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Boston 7 5 2 45 24 2 2.06 ( 4) 56.11 38 19 0 -0.21 ( 28) 2 New York 12 3 0 46 25 3 1.89 ( 5) 55.58 34 22 3 -0.25 ( 29) 3 Toronto 3 10 1 38 29 4 0.66 ( 13) 51.80 35 19 3 -0.09 ( 20) 4 Philadelphia 9 6 1 35 30 7 -0.15 ( 18) 48.34 26 24 6 -0.16 ( 25) 5 Brooklyn 3 10 2 17 52 3 -3.09 ( 27) 41.35 14 42 1 -0.00 ( 15) --- Central CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Detroit 9 4 1 50 18 3 2.49 ( 3) 57.14 41 14 2 -0.12 ( 22) 2 Cleveland 10 4 1 45 24 3 1.80 ( 6) 54.58 35 20 2 0.16 ( 5) 3 Chicago 4 11 0 28 41 2 -1.40 ( 22) 45.84 24 30 2 0.12 ( 8) 4 Milwaukee 9 6 0 27 40 4 -1.57 ( 23) 44.32 18 34 4 0.10 ( 10) 5 Indiana 3 10 0 15 55 2 -3.24 ( 29) 41.38 12 45 2 0.10 ( 9) --- Southeast CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Charlotte 11 5 0 36 33 3 1.45 ( 8) 55.86 25 28 3 -0.12 ( 23) 2 Atlanta 8 6 0 39 32 1 0.82 ( 12) 52.03 31 26 1 -0.03 ( 19) 3 Orlando 8 7 1 35 32 5 0.37 ( 16) 51.17 27 25 4 0.14 ( 6) 4 Miami 7 7 0 37 34 1 0.35 ( 17) 51.93 30 27 1 0.03 ( 14) 5 Washington 2 11 1 16 52 3 -3.52 ( 30) 39.42 14 41 2 0.06 ( 11) --- Northwest CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Oklahoma City 9 3 2 53 15 4 3.37 ( 1) 59.90 44 12 2 -0.14 ( 24) 2 Denver 6 4 2 42 23 7 1.68 ( 7) 54.72 36 19 5 -0.19 ( 26) 3 Minnesota 9 6 1 43 26 3 1.14 ( 10) 53.04 34 20 2 -0.36 ( 30) 4 Portland 7 8 0 35 36 2 -0.24 ( 19) 48.68 28 28 2 -0.10 ( 21) 5 Utah 1 11 1 18 49 5 -2.79 ( 26) 42.33 17 38 4 -0.19 ( 27) --- Pacific CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 LA Lakers 8 7 0 45 26 1 1.02 ( 11) 51.67 37 19 1 0.22 ( 2) 2 Phoenix 10 6 0 39 32 2 0.45 ( 14) 51.30 29 26 2 0.31 ( 1) 3 LA Clippers 8 6 0 33 36 3 0.38 ( 15) 51.65 25 30 3 0.05 ( 13) 4 Golden State 6 6 0 31 36 5 -0.26 ( 20) 50.13 25 30 5 0.18 ( 4) 5 Sacramento 3 10 0 17 53 3 -3.22 ( 28) 39.91 14 43 3 0.13 ( 7) --- Southeast CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 San Antonio 10 3 1 53 18 1 3.17 ( 2) 58.39 43 15 0 0.21 ( 3) 2 Houston 7 5 1 42 22 7 1.42 ( 9) 53.12 35 17 6 -0.02 ( 18) 3 New Orleans 6 6 3 24 44 5 -1.03 ( 21) 47.80 18 38 2 0.06 ( 12) 4 Dallas 4 10 1 21 44 7 -1.81 ( 24) 45.56 17 34 6 -0.02 ( 16) 5 Memphis 4 7 2 22 46 3 -2.19 ( 25) 44.96 18 39 1 -0.02 ( 17)
Division Rankings
The average computer rating of all teams in a division is shown here.
Rank Conference Mean Rating ---- ------------------------- ----------- 1 Northwest 0.63 2 Atlantic 0.27 3 Southeast -0.09 4 Southeast -0.11 5 Pacific -0.33 6 Central -0.38
Game Predictions
These predictions already include home advantage, if necessary.
PREDICTIONS FOR UPCOMING GAMES Date Away Team Home Team Total Prediction ----------- -------------------- -------------------- ----- -------------- 25-Mar-2026 Atlanta Detroit 225 HOME by 6.70 25-Mar-2026 LA Lakers Indiana 230 AWAY by -8.70 25-Mar-2026 Chicago Philadelphia 239 HOME by 4.09 25-Mar-2026 Oklahoma City Boston 210 AWAY by -2.20 25-Mar-2026 Miami Cleveland 239 HOME by 4.23 25-Mar-2026 San Antonio Memphis 236 AWAY by -11.84 25-Mar-2026 Washington Utah 253 HOME by 4.50 25-Mar-2026 Houston Minnesota 223 HOME by 1.51 25-Mar-2026 Dallas Denver 230 HOME by 10.75 25-Mar-2026 Brooklyn Golden State 218 HOME by 10.37 25-Mar-2026 Milwaukee Portland 227 HOME by 5.95 25-Mar-2026 Toronto LA Clippers 224 HOME by 1.44 26-Mar-2026 New York Charlotte 217 HOME by 1.87 26-Mar-2026 New Orleans Detroit 221 HOME by 10.93 26-Mar-2026 Sacramento Orlando 233 HOME by 12.84 27-Mar-2026 LA Clippers Indiana 224 AWAY by -8.68 27-Mar-2026 Atlanta Boston 221 HOME by 5.68 27-Mar-2026 Miami Cleveland 239 HOME by 4.23 27-Mar-2026 Houston Memphis 231 AWAY by -6.57 27-Mar-2026 Chicago Oklahoma City 226 HOME by 15.65 27-Mar-2026 New Orleans Toronto 228 HOME by 5.59 27-Mar-2026 Utah Denver 239 HOME by 13.99 27-Mar-2026 Washington Golden State 239 HOME by 12.30 27-Mar-2026 Dallas Portland 235 HOME by 4.71 27-Mar-2026 Brooklyn LA Lakers 218 HOME by 11.91 28-Mar-2026 San Antonio Milwaukee 225 AWAY by -12.48 28-Mar-2026 Philadelphia Charlotte 229 HOME by 9.12 28-Mar-2026 Sacramento Atlanta 235 HOME by 13.70 28-Mar-2026 Chicago Memphis 245 HOME by 0.71 28-Mar-2026 Detroit Minnesota 226 AWAY by -2.50 28-Mar-2026 Utah Phoenix 229 HOME by 10.57 29-Mar-2026 LA Clippers Milwaukee 218 AWAY by -5.73 29-Mar-2026 Miami Indiana 237 AWAY by -8.96 29-Mar-2026 Sacramento Brooklyn 225 HOME by 3.03 29-Mar-2026 Boston Charlotte 217 HOME by 1.34 29-Mar-2026 Orlando Toronto 224 HOME by 2.22 29-Mar-2026 Washington Portland 243 HOME by 10.85 29-Mar-2026 Houston New Orleans 232 AWAY by -3.73 29-Mar-2026 New York Oklahoma City 206 HOME by 5.91 29-Mar-2026 Golden State Denver 227 HOME by 6.19 30-Mar-2026 Philadelphia Miami 242 HOME by 5.19 30-Mar-2026 Boston Atlanta 223 AWAY by -2.50 30-Mar-2026 Phoenix Memphis 231 AWAY by -4.75 30-Mar-2026 Chicago San Antonio 243 HOME by 14.14 30-Mar-2026 Minnesota Dallas 231 AWAY by -5.89 30-Mar-2026 Cleveland Utah 247 AWAY by -10.66 30-Mar-2026 Detroit Oklahoma City 215 HOME by 4.35 30-Mar-2026 Washington LA Lakers 240 HOME by 13.84
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.