๐ŸŽฏ โšฝ

Prediction methods

Every method implements one walk-forward behaviour, so new approaches drop in without touching the backtest engine. This is the "naive" baseline set; advanced models come later.

Base Rate

base_rate

Predicts the historical home/draw/away frequency, split by neutral vs non-neutral venue.

Elo

elo

World-football Elo: home-field advantage, goal-difference-weighted updates, and match-importance-weighted K (World Cup 60 โ†’ friendly 20).

Poisson

poisson

Independent-Poisson goals model from running team attack/defense strengths; predicts scorelines.

Dixon-Coles

dixon_coles

Poisson goals model with the Dixon-Coles low-score correction (better draws) and recency time-decay.

Bivariate Poisson (diagonal-inflated)

bivariate_poisson

Dixon-Coles goals model with a diagonal inflation lifting all drawn scorelines โ€” the bivariate-Poisson draw correlation as a tunable.

Calibrated Elo

calibrated_elo

Elo forecasts remapped through online histogram-binning calibration learned walk-forward from past matches โ€” better-calibrated probabilities (Brier/log-loss) and fairer odds.

Squad Value

squad_value

Transfermarkt squad value (Peeters 2018): log(home/away top-23 value) โ†’ logistic win probability with an Elo-style draw model. Falls back to base rates where a team has no valuation.

Elo + Value

elo_value

Online multinomial-logistic blend of Elo rating and Transfermarkt squad value (Peeters 2018), fitting the value-vs-Elo weighting walk-forward. Warm-started to Elo so it never starts worse.

Elo + Value + Venue

elo_venue

EloValue plus venue effects: per-team travel/jetlag (host-country streak + arrival timezone jump) and altitude gap (venue elevation above each team's home base โ€” matters on neutral high-altitude venues like Mexico City), fitted walk-forward.

Elo + Value + Importance

elo_value_importance

Elo + squad-value blend extended with game-importance interactions (trust the favourite less in dead rubbers, more in high-stakes games) and a dead-rubber draw bias. Warm-started to Elo+Value so it never starts worse.

Calibrated Elo + Venue

calibrated_elo_venue

EloVenue (Elo + squad value + travel/altitude) remapped through online histogram-binning calibration โ€” the richest model with corrected confidence (Brier/log-loss) and fairer odds.

Ensemble (Venue + Dixon-Coles)

ensemble_venue_dc

Equal-weight linear opinion pool of the EloVenue blend (strength: ratings, squad value, travel/altitude) and the Dixon-Coles goals model (scoreline structure) โ€” two families pooled for steadier calibration.

Coming later: recency-weighted Poisson / Dixon-Coles, squad-aware Elo, and ML models โ€” plus TAB market odds for value detection.