2024-2025 NHL Elo Ratings & Projections

Last updated Tue, Jan 14, 2025, 11:56 PM EST.

Welcome to our 2024-25 NHL elo projections!

This website is inspired by 538's NHL Elo ratings, which are sadly no longer available on their site. We provide season-long and game-level projections, updated daily. See below the table for how it works.

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							Based on 50,000 simulations

1	Edmonton OilersEDM 27-13-3	Pacific	1588	+8	+8	108	99.1%	67%	41%	22%	13.6%
2	Dallas StarsDAL 28-14-1	Central	1585	+21	+13	108	98.8%	62%	36%	20%	12.1%
3	Winnipeg JetsWPG 30-12-3	Central	1573	+43	+3	110	99.6%	60%	31%	16%	9.4%
4	Washington CapitalsWSH 29-10-5	Metro	1561	+70	+2	111	99.8%	64%	34%	19%	8.8%
5	Carolina HurricanesCAR 26-14-3	Metro	1562	+4	-3	104	97.5%	57%	30%	17%	7.8%
6	Florida PanthersFLA 26-16-3	Atlantic	1557	-8	-3	102	95.4%	56%	31%	16%	6.9%
7	Vegas Golden KnightsVEG 29-12-3	Pacific	1559	+25	-13	108	99.0%	55%	26%	12%	6.5%
8	Colorado AvalancheCOL 27-17-1	Central	1562	+3	+3	102	93.4%	44%	22%	10%	5.7%
9	Tampa Bay LightningTBL 22-16-3	Atlantic	1551	+16	-9	98	87.4%	48%	26%	13%	5.6%
10	Los Angeles KingsLAK 24-12-5	Pacific	1552	+30	+6	104	96.1%	47%	21%	10%	5.3%
11	New Jersey DevilsNJD 26-15-5	Metro	1548	+18	-6	101	95.3%	48%	23%	12%	4.9%
12	Toronto Maple LeafsTOR 27-16-2	Atlantic	1540	-10	-15	100	92.7%	47%	23%	11%	4.3%
13	Minnesota WildMIN 27-13-4	Central	1535	+20	+2	103	95.7%	36%	15%	6%	3.0%
14	Ottawa SenatorsOTT 22-18-3	Atlantic	1510	+13	+5	92	58.8%	22%	10%	4%	1.5%
15	New York RangersNYR 20-20-3	Metro	1512	-43	+8	88	37.2%	14%	6%	3%	1.1%
16	Boston BruinsBOS 22-19-5	Atlantic	1510	-34	-3	90	44.9%	17%	7%	3%	1.1%
17	Vancouver CanucksVAN 19-14-10	Pacific	1501	-39	-6	91	46.4%	13%	5%	2%	0.7%
18	Montreal CanadiensMTL 21-18-4	Atlantic	1473	+34	+16	86	26.9%	8%	3%	<1%	0.3%
19	St. Louis BluesSTL 21-20-4	Central	1491	+3	-6	86	18.8%	5%	2%	<1%	0.3%
20	Calgary FlamesCGY 21-15-7	Pacific	1474	+3	+3	89	31.9%	7%	2%	<1%	0.2%
21	Detroit Red WingsDET 20-19-4	Atlantic	1479	-18	+10	82	13.5%	5%	2%	<1%	0.2%
22	New York IslandersNYI 17-19-7	Metro	1480	-25	+10	82	11.8%	4%	2%	<1%	0.2%
23	Columbus Blue JacketsCBJ 21-17-6	Metro	1459	+48	+23	85	22.8%	5%	2%	<1%	0.2%
24	Utah Hockey ClubUTA 18-18-7	Central	1475	-9	-16	84	13.2%	3%	<1%	<1%	0.1%
25	Philadelphia FlyersPHI 19-20-6	Metro	1460	-14	-0	81	7.8%	2%	<1%	<1%	0.1%
26	Nashville PredatorsNSH 14-22-7	Central	1486	-48	+11	79	3.6%	1%	<1%	<1%	0.1%
27	Pittsburgh PenguinsPIT 18-20-8	Metro	1457	-47	-17	80	5.4%	1%	<1%	<1%	0.1%
28	Buffalo SabresBUF 16-22-5	Atlantic	1468	-31	-1	76	2.7%	<1%	<1%	<1%	0.1%
29	Seattle KrakenSEA 19-23-3	Pacific	1467	-17	-1	78	3.4%	<1%	<1%	<1%	0.0%
30	Anaheim DucksANA 18-21-5	Pacific	1420	+8	-12	75	1.1%	<1%	<1%	<1%	—
31	San Jose SharksSJS 14-26-6	Pacific	1378	-3	+7	63	0.0%	—	—	—	—
32	Chicago BlackhawksCHI 14-28-2	Central	1398	-21	-9	62	0.0%	—	—	—	—

As of:

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 outlined below. This website is not affiliated with FiveThirtyEight or ABC News.

Current Version

The current version of the projections builds on FiveThirtyEight's model, biasing parameters to the salary-cap era. We tune home-ice advantage from 50 to 42, and increase the K-factor from 6 to 8. We also add a Vegas totals bias to the teams' season starting elo, rather than relying solely on a regressed season-ending elo, which short-cuts learning any off-season movement.

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.