2024-2025 NHL Elo Ratings & Projections

Last updated Thu, Nov 21, 2024, 1:33 AM EST.

Welcome to our 2024-25 NHL elo projections!

We're back for another season of NHL elo projections after much more interest than expected last year. If you're new here, this website is inspired by 538's NHL Elo ratings, which are sadly no longer available on their site. See below the table for more about how this works.

For those returning from last season, most everything has remained the same. However, we've added recent elo changes as a new column to help see in-season trends. We also have an API available so if you're data scraping, DM me on Twitter for an API key.

Show all columns?

							Based on 50,000 simulations

1	Carolina HurricanesCAR 14-4-0	Metro	1595	+37	+11	113	98%	67%	40%	24%	15%
2	Winnipeg JetsWPG 16-3-0	Central	1583	+53	+4	115	99%	67%	38%	24%	13%
3	Dallas StarsDAL 12-6-0	Central	1575	+12	+9	106	94%	57%	31%	19%	10%
4	New York RangersNYR 12-4-1	Metro	1573	+18	+8	108	93%	54%	28%	15%	9%
5	Florida PanthersFLA 12-6-1	Atlantic	1571	+6	-13	106	92%	57%	32%	16%	8%
6	Edmonton OilersEDM 10-8-2	Pacific	1553	-28	-0	99	81%	47%	27%	12%	6%
7	Toronto Maple LeafsTOR 12-6-2	Atlantic	1556	+5	+6	102	86%	47%	23%	11%	5%
8	Tampa Bay LightningTBL 10-6-1	Atlantic	1553	+19	+7	102	84%	46%	23%	10%	5%
9	Minnesota WildMIN 12-3-3	Central	1544	+29	+5	105	92%	42%	18%	10%	4%
10	Vegas Golden KnightsVEG 11-6-2	Pacific	1538	+5	-12	100	83%	44%	23%	10%	4%
11	New Jersey DevilsNJD 12-7-2	Metro	1549	+19	+8	101	82%	37%	17%	8%	4%
12	Washington CapitalsWSH 13-4-1	Metro	1539	+48	+27	104	88%	37%	15%	7%	4%
13	Colorado AvalancheCOL 10-9-0	Central	1534	-24	+8	94	65%	28%	13%	7%	3%
14	Vancouver CanucksVAN 9-6-3	Pacific	1524	-16	-11	95	68%	33%	16%	6%	3%
15	Los Angeles KingsLAK 10-7-3	Pacific	1523	+0	-6	95	67%	31%	15%	6%	2%
16	Boston BruinsBOS 8-9-3	Atlantic	1506	-38	-21	88	33%	12%	5%	2%	<1%
17	Buffalo SabresBUF 9-9-1	Atlantic	1498	-0	-4	87	33%	12%	5%	2%	<1%
18	Seattle KrakenSEA 10-9-1	Pacific	1490	+7	+12	88	40%	15%	6%	2%	<1%
19	Ottawa SenatorsOTT 8-9-1	Atlantic	1494	-3	-2	87	31%	11%	4%	2%	<1%
20	Calgary FlamesCGY 10-6-3	Pacific	1482	+12	+7	90	49%	17%	6%	2%	<1%
21	New York IslandersNYI 7-7-5	Metro	1493	-13	-3	87	30%	9%	4%	1%	<1%
22	Nashville PredatorsNSH 6-11-3	Central	1493	-40	-9	83	21%	7%	3%	1%	<1%
23	Detroit Red WingsDET 7-9-2	Atlantic	1477	-21	-17	83	18%	6%	2%	<1%	<1%
24	Utah Hockey ClubUTA 7-8-3	Central	1467	-16	-3	82	20%	5%	2%	<1%	<1%
25	St. Louis BluesSTL 8-11-1	Central	1466	-22	-9	80	15%	4%	2%	<1%	<1%
26	Pittsburgh PenguinsPIT 7-10-4	Metro	1469	-35	-19	80	11%	3%	1%	<1%	<1%
27	Philadelphia FlyersPHI 8-10-2	Metro	1462	-12	+5	81	12%	3%	<1%	<1%	<1%
28	Montreal CanadiensMTL 7-10-2	Atlantic	1433	-6	+15	74	4%	<1%	<1%	<1%	<1%
29	Columbus Blue JacketsCBJ 7-9-2	Metro	1426	+14	+3	74	4%	<1%	<1%	<1%	<1%
30	Anaheim DucksANA 8-8-2	Pacific	1421	+9	+21	75	6%	2%	<1%	<1%	<1%
31	Chicago BlackhawksCHI 6-12-1	Central	1412	-7	-9	68	2%	<1%	<1%	<1%	<1%
32	San Jose SharksSJS 6-11-4	Pacific	1370	-11	-3	63	<1%	<1%	<1%	—	—

As of:

Version History

v3.0 - current

Re-ran backtesting of model parameters with a bias towards the salary-cap era. This resulted in changes to several parameters, including increasing the K-factor from 6 to 8 and reducing home ice advantage from 50 to 42, which were found to improve predictive performance of the model at the game level. This in should improve the quality of the forecast, which is done via game-level monte carlo simulation.

v2.0

I added a Vegas totals bias to the teams' season starting elo. This differs from v1.0, which uses only last season's ending elo, with a small regression back to the mean. In this change, I mapped Vegas totals to elo ratings using a simple linear regression model, then I blended the v1 rating with the Vegas projected rating, at 65% Vegas-biased elo and 35% v1 elo. The most notable change is Boston going from first with a 20% cup chance, down to 4th at only 9%.

v1.0 - FiveThirtyEight's

This was an exact replica of FiveThirtyEight's NHL forecast.

What is this?

This is an elo forecast based on FiveThirtyEight's deprecated NHL Elo model and forecast. You can read about how the original version works on FiveThirtyEight's website. Model credit to @ryanabest and @neil_paine, with modifications as detailed in the version history above. This website is not affiliated with FiveThirtyEight or ABC News.

How does it work?

Each team is given an elo score, which is effectively their strength relative to other teams. At the start of the eason, this score is a blend of their previous season's ending elo, regressed to the mean, and an implied elo derived from the Vegas season point total projections. Before each game, we compute the probability of each team winning based on their elo ratings and other factors like home ice advantage. After each game is played, we update the teams' scores based based on who won, by how much, who was originally expected to win, etc.

To simulate the season, we go game by game, randomly picking a winner of each game weighted on their pre-game probabilities. We then update their elo rating as described above as if they really played the game, and continue to the next game. We do this for the whole season (including playoffs) tens of thousands of times, recording how each team did in each full season simulation.

We then average their results across simulated seasons to get the probability of making the playoffs or winning the cup, etc., which are presented in the table above. For example, if the Edmonton Oilers won the cup 6,000 times in 50,000 simulations, they would show a 12% chance of winning the cup in the table above. If the Leafs won the cup 5,000 times, the table would show 10%, but we'd all know the true probability is still 0.

Is it accurate?

These projections have been shown to be exceptionally well-calibrated over the years when 538 was doing it, and last year when I did it. So across a season, they're quite reliable. When you factor in the simplicity of the modeling, the ROI on effort to results is quite frankly astounding. (As an aside, other projections websites go to mind-bending lengths incuding things like puck locations and player tracking, and achieve only marginally better results.)

However, there are shortfalls to the system, especially at the game level. It doesn't account for day-to-day changes like injuries, trades, suspensions, coaching changes, etc. When these things happen, it can take a few games for the elo score to capture the impact, and so any given game could be poorly calibrated in the short term. One way to think about this is if the Vegas money line is significantly different from the elo projection, it's not a value find but an indication that there's a significant factor the model doesn't know about.

How do I use this to gamble?

You don't. I'm just some random guy on the internet (see below) and this could go away at any time. It's made for entertainment and hockey obsession purposes only.

Why do this?

I'm a super fan of both hockey and elo ratings. So when I learned that FiveThirtyEight wasn't doing their forecasts last season, I shed a few tears. Ironically, a hockey injury gave me some extra time back in my week, which I used to build this.

Who made this?

I'm a software engineer, machine learning practioner and beer league hockey player. My day job is building software for Coastline, a driving education startup.