๐Ÿ† Matchup Predictorwho's actually going to win?

๐Ÿ“ˆ How Good Are NFL Predictions, Really?

We don't just make predictions and move on — every one gets written down and checked against what actually happened. Here's the honest scorecard, good or bad.

โฌ‡ Download the full graded history as CSV — don't take our word for it, run your own numbers.

60%
Right about 60 times out of every 100 games this season, based on replaying 203 real games.
For context, just always picking the home team would only be right 52.2% of the time — so the model's real analysis is worth about 7 points over that simplest possible guess, a genuine edge, not just noise.

๐ŸŽฏ When We Say We're Sure, Are We Actually Right?

The single most honest check of any prediction model: if we say a team has a 70% chance and that's a fair number, they should actually win about 70% of the time we say that — not 50%, not 95%. Below, the bar shows how often the home team actually won when we gave a prediction in that range; the marker shows what we predicted. A bar that reaches its marker means our confidence levels mean what they claim.

30-40% predicted
12.5% actual
40-50% predicted
33.3% actual
50-60% predicted
44.8% actual
60-70% predicted
66.7% actual
70-80% predicted
94.4% actual

Based on replaying 203 real NFL games this season, only ever using information the model would have actually had before each game.

๐Ÿ†š Us vs. Vegas vs. ESPN

Every prediction we make is written down before the game happens, then graded once it's over — so this is a real report card, not hindsight. 0 games graded so far, 1 still waiting on a result.

Results last checked 2026-08-03 02:03:09 UTC, across all sports — 0 newly graded that run.

No games have finished yet since we started keeping score — check back once today's games wrap up.

Show the stats behind this

For each prediction we also track how confident we were, not just whether we got the winner right — a model that says "90%" and is wrong should be judged more harshly than one that says "51%" and is wrong. That's what "average error" below measures (lower is better; 0 would be a perfect psychic, 0.25 is what you'd get by always guessing 50/50).

๐Ÿงช The Longer History

We also replayed this whole season game-by-game, only ever using information the model would have actually had before each game — a much bigger sample (203 games) than the live scorecard above, though it's a simulation rather than predictions made in real time.

Show the stats behind this

The sample size behind the calibration chart above, range by range:

When we saidThey actually wonSample size
30-40%12.5%8 games
40-50%33.3%27 games
50-60%44.8%96 games
60-70%66.7%54 games
70-80%94.4%18 games

"All games" includes stretches early in a season where teams don't have much of a track record yet, which makes predictions noisier. "5+ games of history" filters those out. We don't compare against Vegas here because ESPN's data doesn't keep betting odds around for games that already happened — only the live scorecard above can do that comparison.

All Games
58.9%
285 games · average error 0.2311
5+ Games of History
59.6%
203 games · average error 0.2256

๐Ÿ”ง Are We Improving the Model Over Time?

We don't have enough game history yet to safely test whether small adjustments would help — testing too early risks mistaking luck for a real improvement. For now, NFL runs the settings we started with.