home wins v3: can we beat the market's own feature?
β lab Β· AUC 0.688 (real signal) Β· ran 7/3/2026
What this is: Asks which pre-match factors drive one specific outcome, using a walk-forward model and permutation importance.
| Factor | Importance | Direction | Survives all eras? |
|---|
| market.p_away | 0.0371 | β -0.371 | β³ yes |
| market.p_home | 0.0157 | β +0.382 | β³ yes |
| home__team.goal_diff_avg_l5 | 0.0051 | β +0.184 | β³ yes |
| home__team.elo_momentum_l5 | 0.0041 | β +0.022 | β³ yes |
| home__team.shot_diff_avg_l5 | 0.0039 | β +0.212 | β³ yes |
| away__team.goals_volatility_l10 | 0.0030 | β -0.125 | β³ yes |
| home__team.cards_avg_l5 | 0.0027 | β -0.039 | β³ yes |
| market.p_draw | 0.0025 | β -0.186 | β³ yes |
| home__team.corner_diff_avg_l5 | 0.0021 | β +0.170 | β³ yes |
| match.humidity_pct | 0.0021 | β -0.005 | no |
| away__team.corners_volatility_l10 | 0.0018 | β -0.069 | β³ yes |
| away__team.goals_for_avg_l5 | 0.0016 | β -0.149 | β³ yes |
Reading the columnswhat each number actually means
| AUC | predictability: 0.50 = coin flip, ~0.70 = ceiling for sports |
| Importance | how much the model leans on this factor (permutation importance) |
| Direction | sign of the raw correlation with the outcome |
| Survives all eras | effect points the same way in every historical era |
Spec Β· the reproducible recipe
{
"name": "home wins v3: can we beat the market's own feature?",
"sport": "football",
"target": {
"equals": "H",
"metric": "match.result"
},
"features": "all"
}