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 03-Mar-2026 07 AM ET

Rank Team                   W  L OT   Rating   Points  BCS
   1 Colorado              39 14  6     4.50    51.23    1
   2 Tampa Bay             34 18  6     3.50    50.91    2
   3 Dallas                33 20  7     2.47    50.64    3
   4 Pittsburgh            30 20  9     2.35    50.65    4
   5 Carolina              34 19  7     2.11    50.53    5
   6 Buffalo               32 25  3     2.02    50.53    6
   7 Montreal              31 22  6     1.66    50.43   10
   8 Boston                31 23  5     1.43    50.29    8
   9 Minnesota             31 23  7     1.24    50.32   11
  10 Detroit               33 23  5     1.19    50.11    7

Rank Team                   W  L OT   Rating   Points  BCS
  11 NY Islanders          31 21  9     1.06    50.11    9
  12 Washington            30 26  6     0.79    50.19   12
  13 Utah                  31 29  0     0.69    50.30   13
  14 Las Vegas             27 26  7     0.03    50.05   16
  15 Ottawa                26 30  3     0.02    50.11   19
  16 Edmonton              29 29  3    -0.05    50.12   21
  17 Columbus              25 28  7    -0.18    49.99   18
  18 Seattle               28 27  5    -0.19    49.92   15
  19 Anaheim               26 26  7    -0.41    49.77   14
  20 Florida               26 29  5    -0.63    49.79   20

Rank Team                   W  L OT   Rating   Points  BCS
  21 San Jose              27 28  3    -0.88    49.62   17
  22 Toronto               26 32  3    -1.10    49.75   24
  23 Philadelphia          22 29  9    -1.26    49.72   25
  24 Nashville             24 33  3    -1.37    49.60   23
  25 New Jersey            26 31  3    -1.38    49.50   22
  26 Los Angeles           20 30 11    -1.41    49.67   26
  27 Winnipeg              22 34  3    -2.06    49.63   30
  28 Calgary               22 32  5    -2.19    49.43   27
  29 Chicago               20 32  8    -2.33    49.44   28
  30 NY Rangers            20 37  3    -2.54    49.45   31
  31 St Louis              21 35  4    -2.61    49.32   29
  32 Vancouver             14 40  6    -4.49    48.85   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 03-Mar-2026 07 AM ET) --- East CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Tampa Bay 8 5 2 34 18 6 3.50 ( 2) 50.91 26 13 4 -0.21 ( 24) 2 Buffalo 13 7 0 32 25 3 2.02 ( 6) 50.53 19 18 3 -0.31 ( 31) 3 Montreal 9 8 2 31 22 6 1.66 ( 7) 50.43 22 14 4 -0.23 ( 27) 4 Boston 8 8 3 31 23 5 1.43 ( 8) 50.29 23 15 2 -0.43 ( 32) 5 Detroit 11 5 1 33 23 5 1.19 ( 10) 50.11 22 18 4 -0.22 ( 25) 6 Ottawa 6 11 0 26 30 3 0.02 ( 15) 50.11 20 19 3 -0.28 ( 29) 7 Florida 6 11 1 26 29 5 -0.63 ( 20) 49.79 20 18 4 -0.20 ( 23) 8 Toronto 6 12 1 26 32 3 -1.10 ( 22) 49.75 20 20 2 -0.28 ( 30) --- North CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Pittsburgh 11 2 5 30 20 9 2.35 ( 4) 50.65 19 18 4 -0.24 ( 28) 2 Carolina 9 4 3 34 19 7 2.11 ( 5) 50.53 25 15 4 0.23 ( 7) 3 NY Islanders 13 6 2 31 21 9 1.06 ( 11) 50.11 18 15 7 0.31 ( 5) 4 Washington 12 4 2 30 26 6 0.79 ( 12) 50.19 18 22 4 -0.02 ( 13) 5 Columbus 5 10 3 25 28 7 -0.18 ( 17) 49.99 20 18 4 -0.04 ( 15) 6 Philadelphia 4 7 6 22 29 9 -1.26 ( 23) 49.72 18 22 3 0.05 ( 12) 7 New Jersey 2 14 2 26 31 3 -1.38 ( 25) 49.50 24 17 1 0.10 ( 11) 8 NY Rangers 4 13 3 20 37 3 -2.54 ( 30) 49.45 16 24 0 0.19 ( 8) --- Central CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Colorado 10 3 3 39 14 6 4.50 ( 1) 51.23 29 11 3 -0.10 ( 17) 2 Dallas 12 4 2 33 20 7 2.47 ( 3) 50.64 21 16 5 -0.19 ( 22) 3 Minnesota 8 8 2 31 23 7 1.24 ( 9) 50.32 23 15 5 -0.23 ( 26) 4 Utah 10 9 0 31 29 0 0.69 ( 13) 50.30 21 20 0 -0.12 ( 19) 5 Nashville 8 13 1 24 33 3 -1.37 ( 24) 49.60 16 20 2 -0.17 ( 21) 6 Winnipeg 6 10 0 22 34 3 -2.06 ( 27) 49.63 16 24 3 -0.13 ( 20) 7 Chicago 7 7 2 20 32 8 -2.33 ( 29) 49.44 13 25 6 -0.10 ( 16) 8 St Louis 6 13 0 21 35 4 -2.61 ( 31) 49.32 15 22 4 -0.10 ( 18) --- West CW CL OT W L OT Rating Rank Points NCWNCLNCT Non-Conf Sched 1 Las Vegas 10 7 1 27 26 7 0.03 ( 14) 50.05 17 19 6 0.18 ( 10) 2 Edmonton 9 6 2 29 29 3 -0.05 ( 16) 50.12 20 23 1 0.19 ( 9) 3 Seattle 12 6 2 28 27 5 -0.19 ( 18) 49.92 16 21 3 0.27 ( 6) 4 Anaheim 9 7 3 26 26 7 -0.41 ( 19) 49.77 17 19 4 0.51 ( 3) 5 San Jose 8 12 1 27 28 3 -0.88 ( 21) 49.62 19 16 2 0.84 ( 1) 6 Los Angeles 4 10 5 20 30 11 -1.41 ( 26) 49.67 16 20 6 0.54 ( 2) 7 Calgary 9 8 2 22 32 5 -2.19 ( 28) 49.43 13 24 3 -0.02 ( 14) 8 Vancouver 4 9 2 14 40 6 -4.49 ( 32) 48.85 10 31 4 0.37 ( 4)

Division Rankings


The average computer rating of all teams in a division is shown here.


Rank Conference Mean Rating ---- ------------------------- ----------- 1 East 1.01 2 North 0.12 3 Central 0.07 4 West -1.20

Predictions

PREDICTIONS FOR UPCOMING GAMES Date Away Team Home Team Total Prediction ----------- -------------------- -------------------- ----- -------------- 03-Mar-2026 Pittsburgh Boston 5.7 AWAY by -0.23 03-Mar-2026 Las Vegas Buffalo 6.3 HOME by 0.62 03-Mar-2026 Florida New Jersey 5.8 AWAY by -0.15 03-Mar-2026 Utah Washington 5.4 HOME by 0.03 03-Mar-2026 Nashville Columbus 6.3 HOME by 0.53 03-Mar-2026 Chicago Winnipeg 5.9 HOME by 0.33 03-Mar-2026 Dallas Calgary 5.6 AWAY by -1.07 03-Mar-2026 Ottawa Edmonton 7.9 HOME by 0.15 03-Mar-2026 Tampa Bay Minnesota 6.1 AWAY by -0.46 03-Mar-2026 Colorado Anaheim 6.7 AWAY by -1.32 03-Mar-2026 Montreal San Jose 6.9 AWAY by -0.67 04-Mar-2026 Las Vegas Detroit 6.1 HOME by 0.20 04-Mar-2026 Toronto New Jersey 6.1 AWAY by -0.11 04-Mar-2026 Carolina Vancouver 5.8 AWAY by -1.54 04-Mar-2026 NY Islanders Anaheim 6.4 AWAY by -0.20 04-Mar-2026 St Louis Seattle 5.5 HOME by 0.74 05-Mar-2026 Toronto NY Rangers 6.2 AWAY by -0.16 05-Mar-2026 Utah Philadelphia 5.3 AWAY by -0.44 05-Mar-2026 Buffalo Pittsburgh 6.9 HOME by 0.25 05-Mar-2026 Florida Columbus 6.4 HOME by 0.33 05-Mar-2026 Boston Nashville 7.0 AWAY by -0.55 05-Mar-2026 Tampa Bay Winnipeg 6.2 AWAY by -1.14 05-Mar-2026 Ottawa Calgary 6.2 AWAY by -0.54 05-Mar-2026 NY Islanders Los Angeles 5.1 AWAY by -0.31 06-Mar-2026 Florida Detroit 6.6 HOME by 0.46 06-Mar-2026 Colorado Dallas 5.5 AWAY by -0.45 06-Mar-2026 Vancouver Chicago 5.6 HOME by 0.73 06-Mar-2026 Carolina Edmonton 6.7 AWAY by -0.27 06-Mar-2026 Montreal Anaheim 7.3 AWAY by -0.52 06-Mar-2026 Minnesota Las Vegas 6.5 AWAY by -0.14 06-Mar-2026 St Louis San Jose 6.4 HOME by 0.44 07-Mar-2026 Washington Boston 6.3 HOME by 0.23 07-Mar-2026 NY Rangers New Jersey 5.4 HOME by 0.19 07-Mar-2026 Nashville Buffalo 6.7 HOME by 1.07 07-Mar-2026 Philadelphia Pittsburgh 6.7 HOME by 1.07 07-Mar-2026 Tampa Bay Toronto 6.6 AWAY by -1.03 07-Mar-2026 Utah Columbus 5.6 AWAY by -0.17 07-Mar-2026 Vancouver Winnipeg 6.4 HOME by 0.92 07-Mar-2026 Montreal Los Angeles 6.0 AWAY by -0.62 07-Mar-2026 Carolina Calgary 5.1 AWAY by -0.96 07-Mar-2026 NY Islanders San Jose 6.0 AWAY by -0.35 07-Mar-2026 Ottawa Seattle 6.2 AWAY by -0.05

Description


Original Text Files

Feel free to download these; if you use them elsewhere, give credit to talismanred.com.

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.

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