WAFLW
Performance

How our tipping heuristics are performing.

Current Season 2026

21 / 21 rounds completed

How profit is calculated: each tip carries a simulated $10 stake. Games with bookmaker odds (The Odds API) settle at the real decimal price for the tipped team; games without an odds snapshot settle at a representative $1.90; drawn games refund the stake. Odds coverage shows the share of tips settled at real prices.

Best Bet

Current Season
Year-to-Date Profit $276.00
Projected Annual Profit $276.00
Projections are based on early season performance and may change as the season progresses.
Accuracy71.1%
Rounds Played21
Avg Profit/Round $13.14
Odds Coverage0%

Weighted Tip

Current Season
Year-to-Date Profit $257.00
Projected Annual Profit $257.00
Projections are based on early season performance and may change as the season progresses.
Accuracy69.7%
Rounds Played21
Avg Profit/Round $12.24
Odds Coverage0%

Boosted Tip

Current Season
Year-to-Date Profit $428.00
Projected Annual Profit $428.00
Projections are based on early season performance and may change as the season progresses.
Accuracy81.6%
Rounds Played21
Avg Profit/Round $20.38
Odds Coverage0%
Individual Model Accuracy
Elo Rating★
73.3%
Accuracy
$295
Profit
Form
73.2%
Accuracy
$278
Profit
Value
70.7%
Accuracy
$257
Profit
Matchup
69.2%
Accuracy
$123
Profit
Home Advantage
44.4%
Accuracy
$-112
Profit

Weighted Tip Model

v72
Trained: Tue, 10 Nov, 08:00 amTraining rows: 76Intercept: -2.24R²: 0.4406MAE: 19.2

The Weighted Tip model combines all 5 ML model predictions using a linear regression trained on 76 historical games. Each model contributes a margin weight (influence on score margin) and a confidence weight (influence on confidence). The current model (v72) has R² = 0.441 with intercept -2.24. Most influential models: elo rating diff, form wins diff, home advantage home constant. The model is retrained weekly with updated coefficients.

Model Equation
predicted_margin =-2.24+0.000·elo rating diffm+0.000·form wins diffm+0.000·home advantage home constantm+0.000·matchup h2h wins diffm+0.000·value win rate diffm

Each model contributes a margin weight (× its predicted margin toward home) and a confidence weight. Models with larger absolute weights have more influence on the final tip.

Margin Weights

Active Boosted Model (XGBoost)

v58
Trained: Tue, 10 Nov, 08:00 amTraining rows: 76R²: 0.8532MAE: 8.3SHAP base value: -0.23

The Boosted Tip model is a gradient-boosted tree ensemble (XGBoost) trained on 76 historical games to predict the home-team-signed margin from the same model predictions the Weighted Tip model uses. The current model (v58) reaches R² = 0.853 with MAE = 8.3 points and is retrained weekly. Feature importances below are mean |SHAP| values — how much each model's margin and confidence signal moves the prediction, with elo rating diff, value win rate diff, form wins diff the most influential.

SHAP Feature Importance