sweep: match.total_goals >= 2
← lab · AUC 0.543 (weak signal) · ran 7/4/2026
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? |
|---|
| away__team.dominance_l5 | 0.0004 | ↑ +0.004 | no |
| away__team.shots_for_avg_l5 | 0.0004 | ↑ +0.041 | ⏳ yes |
| home__team.conversion_l5 | 0.0002 | ↑ +0.006 | no |
| market.p_away | 0.0002 | ↓ -0.011 | no |
| away__team.ht_lead_rate_l20 | 0.0001 | ↑ +0.009 | no |
| home__team.rest_days | 0.0001 | ↑ +0.013 | no |
| home__team.corner_diff_avg_l5 | 0.0001 | ↑ +0.020 | no |
| away__team.elo_momentum_l5 | 0.0001 | ↓ -0.002 | no |
| match.mismatch | 0.0001 | ↑ +0.052 | ⏳ yes |
| away__team.defensive_leak_l5 | 0.0001 | ↓ -0.002 | no |
| home__team.goals_volatility_l10 | 0.0001 | ↑ +0.039 | ⏳ yes |
| away__team.matches_since_blank | 0.0001 | ↑ +0.012 | no |
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 · the reproducible recipe
{
"name": "sweep: match.total_goals >= 2",
"sport": "football",
"target": {
"op": ">=",
"value": 2,
"metric": "match.total_goals"
},
"features": "all"
}