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🎲SimulationsπŸ§ͺLab≣Catalog?How this works

scorer model v1: P(player scores)

← lab Β· AUC 0.762 (real signal) Β· ran 7/6/2026

What this is: A one-off study β€” its numbers below are exactly what the run reported.
notewalk-forward chronological folds; players need 180+ prior minutes
brier0.0727
auc mean0.7623
base rate0.0879
n player matches151,430

calibration

nbinp predp actual
46,6940.00-0.070.03540.0364
15,5770.07-0.150.1060.1102
7,2990.15-0.220.18150.1841
3,6970.22-0.300.25550.2589
1,6800.30-0.370.3290.344
6620.37-0.450.40070.4048
1040.45-0.520.46540.4808
20.52-0.590.56430.5

Reading the columnswhat each number actually means

AUCpredictability: 0.50 = coin flip, ~0.70 = ceiling for sports
Importancehow much the model leans on this factor (permutation importance)
Directionsign of the raw correlation with the outcome
Survives all eraseffect points the same way in every historical era
Spec Β· the reproducible recipe
{
  "kind": "scorer_model",
  "features": [
    "goals_p90_l10",
    "shots_p90_l10",
    "shots_on_p90_l10",
    "start_rate_l5",
    "minutes_avg_l5",
    "is_forward",
    "is_mid",
    "is_home",
    "team_attack",
    "opp_defence"
  ]
}