Public model evidence
Model Leaderboard
Compare verified public model versions. Choose a market and the evidence that should determine rank.
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Log loss leaderboard
Probability accuracy with a larger penalty for confident forecasts that are wrong. Lower is better; 0 is perfect.
Observed leader
MLB Win the Game 2
Public tracking active
0.6757
Quick read: The leader has the lowest observed probability error after larger penalties for confident misses. Log loss does not measure betting profit. Ranks 1 and 2 have overlapping 95% intervals; their order is not clearly separated.
- 0.6757
Log loss
Best observed
- Metric sample
- 320 eligible · 30 required
- Graded sample
- 320 graded · 30 required
- Period
- Oct 2, 2026 – Sep 30, 2026
- Uncertainty
- 95% CI 0.6535 to 0.7066
Open permanent version evidence →Latest eligible public forecast Sep 30, 2026
2 pending · 0 excluded total · 0 voided · 0 invalidated · 0 corrected
- 0.6887
Log loss
0.0130 from leader
- Metric sample
- 292 eligible · 30 required
- Graded sample
- 292 graded · 30 required
- Period
- Oct 9, 2026 – Sep 23, 2026
- Uncertainty
- 95% CI 0.6584 to 0.7220
Open permanent version evidence →Latest eligible public forecast Sep 23, 2026
2 pending · 0 excluded total · 0 voided · 0 invalidated · 0 corrected
- 0.6809
Log loss
Not ranked
- Metric sample
- 24 eligible · 6 short of 30
- Graded sample
- 24 graded · 6 short of 30
- Period
- Sep 18, 2026 – Sep 18, 2026
- Uncertainty
- 95% CI 0.6809 to 0.6809
Open permanent version evidence →Latest eligible public forecast Sep 18, 2026
0 pending · 0 excluded total · 0 voided · 0 invalidated · 0 corrected
Sorted by Log loss (lower is better). Gaps are differences between observed point estimates, not proof that models are meaningfully separated. Equal displayed values share a visible rank; canonical ordering still uses full precision, then eligible sample size, then stable identity. “Establishing” versions remain visible but are not ranked.
Method, sample rules, and exclusions
Rank is the beginning of the question
Compare sample, period, uncertainty, and evidence—not only position. Then test a model whose assumptions you can inspect.