VFLW
Performance

How our tipping heuristics are performing.

Current Season 2026

19 / 19 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 $171.00
Projected Annual Profit $171.00
Projections are based on early season performance and may change as the season progresses.
Accuracy61.5%
Rounds Played19
Avg Profit/Round $9.00
Odds Coverage0%

Weighted Tip

Current Season
Year-to-Date Profit $342.00
Projected Annual Profit $342.00
Projections are based on early season performance and may change as the season progresses.
Accuracy70.8%
Rounds Played19
Avg Profit/Round $18.00
Odds Coverage0%

Boosted Tip

Current Season
Year-to-Date Profit $532.00
Projected Annual Profit $532.00
Projections are based on early season performance and may change as the season progresses.
Accuracy81.3%
Rounds Played19
Avg Profit/Round $28.00
Odds Coverage0%
Individual Model Accuracy
Value★
73.7%
Accuracy
$380
Profit
Form
69.7%
Accuracy
$288
Profit
Matchup
66.7%
Accuracy
$48
Profit
Elo Rating
63.2%
Accuracy
$190
Profit
Home Advantage
54.3%
Accuracy
$30
Profit

Weighted Tip Model

v75
Trained: Tue, 10 Nov, 08:00 amTraining rows: 96Intercept: -3.79R²: 0.3689MAE: 21.6

The Weighted Tip model combines all 5 ML model predictions using a linear regression trained on 96 historical games. Each model contributes a margin weight (influence on score margin) and a confidence weight (influence on confidence). The current model (v75) has R² = 0.369 with intercept -3.79. 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 =-3.79+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)

v61
Trained: Tue, 10 Nov, 08:00 amTraining rows: 96R²: 0.8487MAE: 10.9SHAP base value: -2.22

The Boosted Tip model is a gradient-boosted tree ensemble (XGBoost) trained on 96 historical games to predict the home-team-signed margin from the same model predictions the Weighted Tip model uses. The current model (v61) reaches R² = 0.849 with MAE = 10.9 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