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Every trained model, ranked by how far it beats the benchmark its own market has to clear. Accuracy across different markets is not comparable, because a line that falls one way most of the time hands a model a high score for learning very little. The gap to the benchmark is what ranks here.
| # | Model | Edge | Accuracy | Baseline | Log loss | Sample | Since last train |
|---|---|---|---|---|---|---|---|
| 1 | statistical_basketball_totals unknown · — · Always pick the majority class | +10.20 | 61.08% | 50.88% | 0.6543 | 8,988 | — |
| 2 | Tennis games over 23.5 tennis · Totals · Always pick the majority class | +9.28 | 65.08% | 55.80% | 0.6076 | 14,562 | ▲ 0.20 |
| 3 | NBA winner basketball · Moneyline · Always pick the home side | +9.02 | 66.14% | 57.12% | 0.6154 | 7,012 | ▲ 1.25 |
| 4 | Match result football · 1X2 · Always pick the majority class | +5.52 | 49.22% | 43.70% | 1.0189 | 23,602 | ▼ 0.12 |
| 5 | Tennis games over 21.5 tennis · Totals · Always pick the majority class | +4.57 | 59.78% | 55.21% | 0.6196 | 14,562 | ▲ 0.21 |
| 6 | Corners over 9.5 football · Corners · Always pick the majority class | +3.68 | 53.98% | 50.30% | 0.6880 | 13,739 | ▼ 0.52 |
| 7 | Goals over 2.5 football · Goals · Always pick the majority class | +3.52 | 55.55% | 52.03% | 0.6821 | 23,602 | ▼ 0.67 |
| 8 | Cards over 4.5 football · Cards · Always pick the majority class | +3.23 | 61.12% | 57.89% | 0.6657 | 14,798 | ▲ 0.69 |
| 9 | Tennis games over 19.5 tennis · Totals · Always pick the majority class | +0.75 | 67.31% | 66.56% | 0.5820 | 14,562 | ▼ 0.03 |
| 10 | Both teams to score football · BTTS · Always pick the majority class | +0.66 | 55.14% | 54.48% | 0.6863 | 23,602 | ▼ 0.03 |
| 11 | Tennis winner tennis · Moneyline · Always pick the higher rating | +0.33 | 64.81% | 64.48% | 0.6201 | 14,562 | ▲ 0.10 |
| 12 | lightgbm_over_under_3_5 unknown · — · Always pick the majority class | +0.11 | 70.68% | 70.57% | 0.5951 | 23,602 | ▲ 0.24 |
| 13 | Cards over 2.5 football · Cards · Always pick the majority class | 0.00 | 77.25% | 77.25% | 0.5280 | 14,798 | ▼ 0.86 |
| 14 | Goals over 1.5 football · Goals · Always pick the majority class | 0.00 | 75.66% | 75.66% | 0.5473 | 23,602 | ▼ 0.14 |
| 15 | Corners over 7.5 football · Corners · Always pick the majority class | 0.00 | 73.27% | 73.27% | 0.5757 | 13,739 | ▲ 0.39 |
| 16 | Corners over 8.5 football · Corners · Always pick the majority class | 0.00 | 61.75% | 61.75% | 0.6596 | 13,739 | ▲ 0.54 |
| 17 | Half-time goals over 0.5 football · Goals · Always pick the majority class | 0.00 | 70.67% | 70.67% | 0.6014 | 16,829 | ▼ 0.49 |
| 18 | Cards over 3.5 football · Cards · Always pick the majority class | -0.76 | 59.45% | 60.21% | 0.6593 | 14,798 | ▼ 3.60 |
| 19 | NBA total 225.5provisional basketball · Totals · Always pick the majority class | +5.20 | 60.34% | 55.14% | 0.6629 | 827 | ▲ 0.53 |
| 20 | NBA total 235.5provisional basketball · Totals · Always pick the majority class | +1.08 | 66.26% | 65.18% | 0.6185 | 827 | ▼ 0.33 |
| 21 | NBA total 215.5provisional basketball · Totals · Always pick the majority class | -0.73 | 71.46% | 72.19% | 0.5702 | 827 | ▼ 0.45 |
Edge is accuracy minus the baseline, in percentage points, measured on the held-out test period each model was evaluated against, never on data it trained on. A model with no recorded baseline shows its accuracy but no edge, because there is nothing to say how much of that accuracy is skill.