📈 How Good Are WNBA 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.
⬇ Download the full graded history as CSV — don't take our word for it, run your own numbers.
64%
Right about 64 times out of every 100 games this season, based on replaying 253 real games.
For context, just always picking the home team would only be right 52.6% of the time — so the model's real analysis is worth about 11 points over that simplest possible guess, a genuine edge, not just noise.
🎯 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.
20-30% predicted
0.0% actual
30-40% predicted
29.6% actual
40-50% predicted
34.9% actual
50-60% predicted
45.8% actual
60-70% predicted
68.5% actual
70-80% predicted
67.6% actual
80-90% predicted
83.3% actual
Based on replaying 253 real WNBA games this season, only ever using information the model would have actually had before each game.
🆚 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, 23 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).
🧪 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 (253 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 said | They actually won | Sample size |
|---|
| 20-30% | 0.0% | 5 games |
| 30-40% | 29.6% | 27 games |
| 40-50% | 34.9% | 43 games |
| 50-60% | 45.8% | 59 games |
| 60-70% | 68.5% | 73 games |
| 70-80% | 67.6% | 34 games |
| 80-90% | 83.3% | 12 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
64.9%
305 games · average error 0.221
5+ Games of History
64.0%
253 games · average error 0.2222
🔧 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, WNBA runs the settings we started with.