QAFLW
Performance

How our tipping heuristics are performing.

Current Season 2026

20 / 20 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 $318.00
Projected Annual Profit $318.00
Projections are based on early season performance and may change as the season progresses.
Accuracy72.1%
Rounds Played20
Avg Profit/Round $15.90
Odds Coverage0%

Weighted Tip

Current Season
Year-to-Date Profit $413.00
Projected Annual Profit $413.00
Projections are based on early season performance and may change as the season progresses.
Accuracy77.9%
Rounds Played20
Avg Profit/Round $20.65
Odds Coverage0%

Boosted Tip

Current Season
Year-to-Date Profit $603.00
Projected Annual Profit $603.00
Projections are based on early season performance and may change as the season progresses.
Accuracy89.5%
Rounds Played20
Avg Profit/Round $30.15
Odds Coverage0%
Individual Model Accuracy
Matchup★
78.0%
Accuracy
$198
Profit
Value
75.6%
Accuracy
$375
Profit
Form
74.1%
Accuracy
$330
Profit
Elo Rating
68.6%
Accuracy
$261
Profit
Home Advantage
44.6%
Accuracy
$-127
Profit

Weighted Tip Model

v77
Trained: Tue, 10 Nov, 08:00 amTraining rows: 86Intercept: -0.62R²: 0.4634MAE: 31.5

The Weighted Tip model combines all 5 ML model predictions using a linear regression trained on 86 historical games. Each model contributes a margin weight (influence on score margin) and a confidence weight (influence on confidence). The current model (v77) has R² = 0.463 with intercept -0.62. 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 =-0.62+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)

v63
Trained: Tue, 10 Nov, 08:00 amTraining rows: 86R²: 0.7668MAE: 16.7SHAP base value: 3.03

The Boosted Tip model is a gradient-boosted tree ensemble (XGBoost) trained on 86 historical games to predict the home-team-signed margin from the same model predictions the Weighted Tip model uses. The current model (v63) reaches R² = 0.767 with MAE = 16.7 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, form wins diff, value win rate diff the most influential.

SHAP Feature Importance