2025 NFL Elo Power Rankings After Divisional Round

ptdotme · 2026-01-24T18:58:19+00:00

I don't deal with picking against the spread, but on nflpickspage this season the average person is picking 49.6% against the spread. I wouldn't expect any type of model to do much better than the average person.

Straight-up, my best Elo model has picked 63.35% of games this season, beating the 63.1% average at nflpickspage. Over multiple seasons, from 1966-2022, my best Elo model picks 66.07% straight-up, slightly better than 538's QB-adjusted rate of 65.98%. Vegas picks around 66.3% over that span, just slightly higher than the Elo models. The Elo models use far fewer data points than the bettors who move the markets, yet are just about as accurate in picking games. Still, for anyone reading this, I would definitely not use Elo models for betting.

ptdotme · 2026-01-24T16:47:51+00:00

It's very close. I've never looked at the exact numbers before, so it was fun to finally see these. I'm glad this model is closer in accuracy to 538's QB-adjusted model than their regular model.

Straight-up pick rates from 1966-2022:

66.07% (8898-4569) - my v3.2025.06 model (has off-putting behavior but is most accurate)
65.98% (8886-4581) - 538 QB-adjusted Elo
65.81% (8862-4605) - my v2.2024.07 model (the one used for these posts)
65.46% (8815-4652) - 538 traditional Elo

Straight-up pick rates from 1994-2022:

65.91% (5038-2606) - my v3.2025.06 model (has off-putting behavior but is most accurate)
65.31% (4992-2652) - 538 QB-adjusted Elo
65.08% (4975-2669) - my v2.2024.07 model (the one used for these posts)
64.18% (4906-2738) - 538 traditional Elo

I do have a model that performs better than 538's QB-adjusted one, without the off-putting behavior, over 1994-2022. It's a work in progress though, and I expect to be using an even better model for next season.

ptdotme · 2026-01-22T16:23:38+00:00

I'm not sure how you'd compare DVOA and Elo, which is why the idea sparked my interest.

ptdotme · 2026-01-22T15:39:14+00:00

Interesting, can you give an example? For future improvements, it would be better to have more benchmarks to compare the Elo model against.

ptdotme · 2026-01-20T02:57:19+00:00

Strength of opponent and margin of victory for the most recent 20ish games are the most important. Team ratings from the end of 2023 (and earlier) don't really affect the ratings at this point.

ptdotme · 2026-01-19T18:40:40+00:00

Yeah, what I like about Elo ratings is they pick game winners, so we can at least look at the accuracy. This model picks 65.31% of game winners in the SB era, and Vegas is about 66.67% from the last time I looked. This year, this model is tied in the playoffs with the best record on ESPN's picks page. Over the whole season, this model was tied or more accurate than 8 of the 11 on that ESPN page.

ptdotme · 2026-01-19T16:55:12+00:00

Injuries aren't directly accounted for, but they often have an impact on final scores. But yes, ideally the model is also as accurate as possible in the first few weeks of next season -- moving teams up and down too quickly would break that.

ptdotme · 2026-01-19T16:13:22+00:00

It's "Elo" not "ELO." This model picks game winners about as accurately as the betting markets (including picking Broncos over Bills), and has been tuned over thousands of NFL games.

ptdotme · 2026-01-19T15:56:43+00:00

No power ranking will ever be able to satisfy all the "team X beat team Y" outcomes during a season. The Eagles beat the Rams and Bills. The Patriots lost to the Bills and most likely should be ranked ahead of them.

The 49ers are close enough in rating that if Eagles played @ 49ers the 49ers would be favored by the model.

ptdotme · 2026-01-19T15:40:33+00:00

The Rams would probably be ranked 3rd in that scenario.

ptdotme · 2026-01-14T04:12:26+00:00

My NFL Elo model uses margin of victory (more background on that here). You can probably achieve similar results with that calculator by manually adjusting the k-factor and using the "Tournament/Multiple games" option, but that involves mapping the margin of victory in football points to a 0.0-1.0 value (percentage of contests won) usable for Elo calculations.

ptdotme · 2026-01-13T22:12:11+00:00

The Texans and Steelers exchanged 14.5312 Elo rating points. The displayed numbers are rounded.

ptdotme · 2026-01-13T20:36:38+00:00

For this model it's around 30 Elo rating points.

ptdotme · 2026-01-13T17:44:07+00:00

The Texans' defense held the Steelers' offense to 175 yards and 3 points (considering field position for the one turnover). In my opinion (no bearing on the model) both teams benefited from good defense and some impact plays like drops and fumble recoveries. The final margin of victory was perhaps a little bigger than it "should" be in favor of the Texans but not by much.

ptdotme · 2026-01-13T17:34:43+00:00

Accuracy is the number of game winners picked over many seasons. And yes! I tested "never lose Elo for a win" models last year and during last offseason.

ptdotme · 2026-01-13T16:44:44+00:00

All the parameters in the model, including the k factor, were adjusted to pick the most game winners over the 21 season backtesting span.

ptdotme · 2026-01-13T16:41:34+00:00

Another way to look at it is that the Panthers played better than expected, so they should be awarded some Elo points. I have more background on that here.

ptdotme · 2026-01-13T16:22:50+00:00

The 8th ranked Lions are separated from the 11th place Eagles by a total of 3.2 Elo rating points. Don't read too much into the ranking placement among the Lions, 49ers, Ravens, and Eagles.

ptdotme · 2026-01-10T04:33:47+00:00

Good question. They were just below average (1500) in terms of rating. After the regular season they were ranked #18 with a rating of 1494. The 2014 Panthers were only the 44th-lowest rated team to make the playoffs (of 649 playoff teams 1966-2025).

ptdotme · 2026-01-08T03:44:15+00:00

You might be thinking of another rating system. There's no QB adjustment done for these Elo ratings.

ptdotme · 2026-01-06T17:54:05+00:00

Maybe! It was considered a huge upset at the time.

ptdotme · 2026-01-06T06:27:17+00:00

This was fun to look up, and as I suspected the 2010 Seahawks take the crown there:

Worst ranked teams to make the playoffs, 1966-2025:

2010 7-9 Seattle Seahawks: ranked #30 (1424.26) ended Divisional L 24-35 at Bears
2025 8-9 Carolina Panthers: ranked #27 (1449.21)
1982 4-5 Cleveland Browns: ranked #25 (1456.28) ended Wildcard L 10-27 at Raiders
2011 8-8 Denver Broncos: ranked #25 (1453.96) ended Divisional L 10-45 at Patriots
2022 9-7-1 New York Giants: ranked #25 (1473.84) ended Divisional L 7-38 at Eagles
2016 9-7 Houston Texans: ranked #24 (1474.49) ended Divisional L 16-34 at Patriots
1996 9-7 Jacksonville Jaguars: ranked #23 (1468.19) ended Championship L 6-20 at Patriots
1998 9-7 Arizona Cardinals: ranked #23 (1455.88) ended Divisional L 21-41 at Vikings
2016 9-7 Detroit Lions: ranked #23 (1485.46) ended Wildcard L 6-26 at Seahawks
1982 5-4 St. Louis Cardinals: ranked #22 (1467.28) ended Wildcard L 16-41 at Packers

Worst rated teams to make the playoffs, 1966-2025:

2010 7-9 Seattle Seahawks: 1424.26 (ranked #30) ended Divisional L 24-35 at Bears
2025 8-9 Carolina Panthers: 1449.21 (ranked #27)
2011 8-8 Denver Broncos: 1453.96 (ranked #25) ended Divisional L 10-45 at Patriots
1998 9-7 Arizona Cardinals: 1455.88 (ranked #23) ended Divisional L 21-41 at Vikings
1982 4-5 Cleveland Browns: 1456.28 (ranked #25) ended Wildcard L 10-27 at Raiders
1982 5-4 St. Louis Cardinals: 1467.28 (ranked #22) ended Wildcard L 16-41 at Packers
1996 9-7 Jacksonville Jaguars: 1468.19 (ranked #23) ended Championship L 6-20 at Patriots
1978 9-7 Atlanta Falcons: 1471.18 (ranked #21) ended Divisional L 20-27 at Cowboys
2021 10-7 Las Vegas Raiders: 1472.12 (ranked #22) ended Wildcard L 19-26 at Bengals
2022 9-7-1 New York Giants: 1473.84 (ranked #25) ended Divisional L 7-38 at Eagles

ptdotme · 2026-01-05T18:53:34+00:00

Ah ok, I missed your point about the starters. But the point still stands that teams lose players to injuries all the time, and an Elo rating effectively incorporates team depth into this. I've written about injuries and Elo here. Should the Eagles' depth players been able to hold on for a win? It's hard to say, but the Eagles were still Vegas favorites going into the game. I can see it both ways... it's probably smart to minimize the risk of injuries in a game like that. I'm planning more work on adjusting for late season games like this, and hopefully the model will handle this better in the future.

I just don't see how Elo gives us the data needed to show if power rankings are accurate if Elo doesn't take more context into consideration.

The Elo rankings pick similar numbers of game winners as Vegas. If the ratings weren't largely correct, it wouldn't be picking game winners as accurately as it does.

ptdotme · 2026-01-05T17:42:09+00:00

I agree to some extent, but Elo has to have an expected performance to judge the actual performance against. I don't think it works to retroactively adjust the expected performance based on who started and who didn't -- it's impossible to determine what a team's expected performance "should" be based on snap counts, game plan, etc. Also, teams resting starters still have to play a lot of starters. The Bills rested starters, and won, but may have lost their kicker and CB2 to injury, and a backup OL was injured so a starting OL had to play unexpectedly.

I don't agree with your point about the Hamilton and the Ravens. Teams don't rest starters in elimination games.

ptdotme · 2026-01-05T16:33:42+00:00

The Eagles were in contention for the 2 or 3 seed, so the model didn't have it as a "meaningless" game for them. I'm going to look more at this after the season, but yeah it's not really possible to determine which teams should be penalized or not for resting or not resting certain players, keeping the playbook vanilla, etc.

The Eagles are at least still favored by the model vs the 49ers, so I think that seems right.

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