Talisman Red's NHL Computer Ratings
Welcome! This is my rough attempt at a computer rating that can, among other things, come somewhat close to predicting final game scores.
The actual computer rating, which describes team performance based on games played to date, is found under the "Rating" column. To determine a hypothetical margin of victory, use the "Points" column (just subtract the teams in question) and add the home advantage, which is shown below and is usually about 0.25 to 0.5 goals.
On the Predictions tab, all those games already have home advantage added in, and also show a predicted total.
Shootouts and overtimes make predicting scores tricky, and to deal with that all games that go to a shootout will be recorded as ties. This will, hopefully, improve the accuracy of the predictions.
(Everything is here on a single, scrollable page now. This reduces the need for the Javascript tabs, which were nice but unneeded. Scrapers should not be impacted.)
Ratings
Ratings last updated 20-Apr-2026 08 AM ET Rank Team W L OT Rating Points BCS 1 Colorado 52 21 10 3.95 51.04 1 2 Carolina 49 25 9 3.02 50.72 2 3 Buffalo 46 31 6 2.70 50.68 3 4 Tampa Bay 46 31 6 2.32 50.63 5 5 Montreal 45 29 9 2.18 50.47 4 6 Dallas 44 29 10 2.08 50.52 6 7 Minnesota 43 31 9 1.62 50.42 7 8 Washington 41 33 8 1.38 50.33 8 9 Ottawa 41 38 4 1.38 50.42 9 10 Pittsburgh 38 32 13 1.33 50.43 11 Rank Team W L OT Rating Points BCS 11 Boston 41 35 7 1.24 50.37 10 12 Las Vegas 39 35 9 0.65 50.20 12 13 Utah 43 40 0 0.44 50.19 16 14 Edmonton 41 37 4 0.40 50.15 15 15 Philadelphia 34 35 14 0.37 50.12 14 16 St Louis 36 41 5 -0.16 49.95 19 17 NY Islanders 39 34 9 -0.21 49.82 13 18 Detroit 39 37 6 -0.34 49.85 18 19 New Jersey 38 39 5 -0.34 49.79 17 20 Columbus 33 40 10 -0.43 50.01 22 Rank Team W L OT Rating Points BCS 21 Nashville 33 42 7 -0.77 49.82 21 22 Florida 35 40 7 -0.84 49.72 20 23 Los Angeles 30 39 15 -1.05 49.75 25 24 NY Rangers 31 47 4 -1.12 49.93 27 25 Anaheim 35 39 8 -1.19 49.63 24 26 San Jose 37 41 4 -1.55 49.43 23 27 Winnipeg 33 43 6 -1.65 49.56 26 28 Seattle 32 42 8 -2.13 49.46 28 29 Toronto 31 46 5 -2.36 49.41 30 30 Calgary 30 45 7 -2.44 49.33 29 31 Chicago 26 48 8 -3.44 49.15 31 32 Vancouver 19 55 8 -5.06 48.70 32
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.
NHL Computer Ratings (Last updated 20-Apr-2026 08 AM ET) --- East CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Buffalo 16 10 1 46 31 6 2.70 ( 3) 50.68 30 21 5 -0.15 ( 18) 2 Tampa Bay 14 11 2 46 31 6 2.32 ( 4) 50.63 32 20 4 -0.15 ( 21) 3 Montreal 15 9 3 45 29 9 2.18 ( 5) 50.47 30 20 6 -0.15 ( 23) 4 Ottawa 12 14 0 41 38 4 1.38 ( 9) 50.42 29 24 4 -0.10 ( 17) 5 Boston 10 14 3 41 35 7 1.24 ( 11) 50.37 31 21 4 -0.15 ( 22) 6 Detroit 13 12 1 39 37 6 -0.34 ( 18) 49.85 26 25 5 -0.15 ( 24) 7 Florida 12 12 2 35 40 7 -0.84 ( 22) 49.72 23 28 5 -0.15 ( 20) 8 Toronto 7 17 2 31 46 5 -2.36 ( 29) 49.41 24 29 3 -0.15 ( 19) --- North CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Carolina 16 5 5 49 25 9 3.02 ( 2) 50.72 33 20 4 -0.01 ( 9) 2 Washington 17 7 2 41 33 8 1.38 ( 8) 50.33 24 26 6 -0.03 ( 12) 3 Pittsburgh 13 7 7 38 32 13 1.33 ( 10) 50.43 25 25 6 -0.03 ( 15) 4 Philadelphia 8 10 9 34 35 14 0.37 ( 15) 50.12 26 25 5 -0.03 ( 11) 5 NY Islanders 14 10 2 39 34 9 -0.21 ( 17) 49.82 25 24 7 -0.03 ( 13) 6 New Jersey 5 19 2 38 39 5 -0.34 ( 19) 49.79 33 20 3 -0.03 ( 10) 7 Columbus 8 14 4 33 40 10 -0.43 ( 20) 50.01 25 26 6 -0.05 ( 16) 8 NY Rangers 7 16 3 31 47 4 -1.12 ( 24) 49.93 24 31 1 -0.03 ( 14) --- Central CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Colorado 14 6 6 52 21 10 3.95 ( 1) 51.04 38 15 4 -0.31 ( 32) 2 Dallas 15 8 4 44 29 10 2.08 ( 6) 50.52 29 21 6 -0.29 ( 29) 3 Minnesota 12 12 3 43 31 9 1.62 ( 7) 50.42 31 19 6 -0.29 ( 27) 4 Utah 13 13 0 43 40 0 0.44 ( 13) 50.19 30 27 0 -0.28 ( 25) 5 St Louis 10 16 0 36 41 5 -0.16 ( 16) 49.95 26 25 5 -0.29 ( 26) 6 Nashville 10 14 2 33 42 7 -0.77 ( 21) 49.82 23 28 5 -0.29 ( 31) 7 Winnipeg 12 13 1 33 43 6 -1.65 ( 27) 49.56 21 30 5 -0.29 ( 28) 8 Chicago 10 14 2 26 48 8 -3.44 ( 31) 49.15 16 34 6 -0.29 ( 30) --- West CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Las Vegas 15 9 2 39 35 9 0.65 ( 12) 50.20 24 26 7 0.48 ( 8) 2 Edmonton 16 8 2 41 37 4 0.40 ( 14) 50.15 25 29 2 0.48 ( 5) 3 Los Angeles 8 12 6 30 39 15 -1.05 ( 23) 49.75 22 27 9 0.52 ( 1) 4 Anaheim 12 11 3 35 39 8 -1.19 ( 25) 49.63 23 28 5 0.48 ( 7) 5 San Jose 9 15 2 37 41 4 -1.55 ( 26) 49.43 28 26 2 0.48 ( 2) 6 Seattle 14 9 3 32 42 8 -2.13 ( 28) 49.46 18 33 5 0.48 ( 6) 7 Calgary 12 11 3 30 45 7 -2.44 ( 30) 49.33 18 34 4 0.48 ( 4) 8 Vancouver 6 17 3 19 55 8 -5.06 ( 32) 48.70 13 38 5 0.48 ( 3)
Division Rankings
The average computer rating of all teams in a division is shown here.
Rank Conference Mean Rating ---- ------------------------- ----------- 1 East 0.79 2 North 0.50 3 Central 0.26 4 West -1.55
Predictions
PREDICTIONS FOR UPCOMING GAMES Date Away Team Home Team Total Prediction ----------- -------------------- -------------------- ----- -------------- 20-Apr-2026 Philadelphia Pittsburgh 7.0 HOME by 0.45 20-Apr-2026 Ottawa Carolina 7.1 HOME by 0.43 20-Apr-2026 Minnesota Dallas 6.2 HOME by 0.23 20-Apr-2026 Anaheim Edmonton 7.3 HOME by 0.66 21-Apr-2026 Montreal Tampa Bay 6.5 HOME by 0.29 21-Apr-2026 Boston Buffalo 6.9 HOME by 0.45 21-Apr-2026 Utah Las Vegas 6.2 HOME by 0.15 21-Apr-2026 Los Angeles Colorado 5.3 HOME by 1.43 22-Apr-2026 Pittsburgh Philadelphia 5.5 AWAY by -0.17 22-Apr-2026 Dallas Minnesota 5.9 HOME by 0.04 22-Apr-2026 Anaheim Edmonton 7.3 HOME by 0.66 23-Apr-2026 Buffalo Boston 6.2 AWAY by -0.18 23-Apr-2026 Carolina Ottawa 5.8 AWAY by -0.15 23-Apr-2026 Colorado Los Angeles 5.2 AWAY by -1.16 24-Apr-2026 Tampa Bay Montreal 6.4 AWAY by -0.01 24-Apr-2026 Las Vegas Utah 6.0 HOME by 0.12 24-Apr-2026 Edmonton Anaheim 7.2 AWAY by -0.38
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, penalties, etc. Those things *do* matter, but they aren't factored in here.
Are the predictions any good?
Great question, and the answer depends on the sport:
- In the NBA: in 2023-24 my system predicted 64.2% of game winners correctly
- In college football in 2023, 71.5% correct
- In college basketball in 2023-24, 70.4% correct
My suspicion is that in the NHL, since won-lost records are not nearly as spread out as in football, that the predictions are in the 65 percent range. And that, while comparable to other systems, it's probably less accurate than the Vegas oddsmakers. But you would expect that -- you can't beat an added human touch!
Where I've seen value is in the over-under predictions. When those deviate far away from Vegas (which is usually 5.5, but sometimes 5 or 6), that's often a sign that something is worth investigating. I've had mild betting success with those.
Who are you, anyway?
I have a Ph.D. in Atmospheric Science from the University of Alabama in Huntsville, and am currently a faculty member at Indiana University in Bloomington. In addition to lots of teaching, I have research interests in the broad areas of thunderstorms and numerical weather prediction (forecasting using computers).
Contact me using this email form if you have questions or non-hateful comments.