QAFL
Performance

How our tipping heuristics are performing.

Current Season 2026

24 / 24 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 $526.00
Projected Annual Profit $526.00
Projections are based on early season performance and may change as the season progresses.
Accuracy74.6%
Rounds Played24
Avg Profit/Round $21.92
Odds Coverage0%

Weighted Tip

Current Season
Year-to-Date Profit $450.00
Projected Annual Profit $450.00
Projections are based on early season performance and may change as the season progresses.
Accuracy71.4%
Rounds Played24
Avg Profit/Round $18.75
Odds Coverage0%

Boosted Tip

Current Season
Year-to-Date Profit $868.00
Projected Annual Profit $868.00
Projections are based on early season performance and may change as the season progresses.
Accuracy88.9%
Rounds Played24
Avg Profit/Round $36.17
Odds Coverage0%
Individual Model Accuracy
Elo Rating★
75.4%
Accuracy
$545
Profit
Form
75.0%
Accuracy
$510
Profit
Value
70.6%
Accuracy
$431
Profit
Matchup
68.8%
Accuracy
$147
Profit
Home Advantage
55.3%
Accuracy
$62
Profit

Weighted Tip Model

v76
Trained: Tue, 10 Nov, 08:00 amTraining rows: 126Intercept: 5.40R²: 0.4650MAE: 34.1

The Weighted Tip model combines all 5 ML model predictions using a linear regression trained on 126 historical games. Each model contributes a margin weight (influence on score margin) and a confidence weight (influence on confidence). The current model (v76) has R² = 0.465 with intercept 5.40. 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 =5.40+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)

v62
Trained: Tue, 10 Nov, 08:00 amTraining rows: 126R²: 0.8515MAE: 16.9SHAP base value: 6.72

The Boosted Tip model is a gradient-boosted tree ensemble (XGBoost) trained on 126 historical games to predict the home-team-signed margin from the same model predictions the Weighted Tip model uses. The current model (v62) reaches R² = 0.851 with MAE = 16.9 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