VFL
Performance

How our tipping heuristics are performing.

Current Season 2026

26 / 26 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 $306.00
Projected Annual Profit $306.00
Projections are based on early season performance and may change as the season progresses.
Accuracy59.3%
Rounds Played26
Avg Profit/Round $11.77
Odds Coverage0%

Weighted Tip

Current Season
Year-to-Date Profit $382.00
Projected Annual Profit $382.00
Projections are based on early season performance and may change as the season progresses.
Accuracy61.2%
Rounds Played26
Avg Profit/Round $14.69
Odds Coverage0%

Boosted Tip

Current Season
Year-to-Date Profit $1256.00
Projected Annual Profit $1256.00
Projections are based on early season performance and may change as the season progresses.
Accuracy83.3%
Rounds Played26
Avg Profit/Round $48.31
Odds Coverage0%
Individual Model Accuracy
Form★
58.2%
Accuracy
$206
Profit
Elo Rating
55.6%
Accuracy
$116
Profit
Home Advantage
55.4%
Accuracy
$108
Profit
Value
51.7%
Accuracy
$-36
Profit
Matchup
35.5%
Accuracy
$-101
Profit

Weighted Tip Model

v74
Trained: Tue, 10 Nov, 08:00 amTraining rows: 209Intercept: 3.15R²: 0.0885MAE: 30.0

The Weighted Tip model combines all 5 ML model predictions using a linear regression trained on 209 historical games. Each model contributes a margin weight (influence on score margin) and a confidence weight (influence on confidence). The current model (v74) has R² = 0.089 with intercept 3.15. 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 =3.15+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)

v60
Trained: Tue, 10 Nov, 08:00 amTraining rows: 209R²: 0.6568MAE: 17.9SHAP base value: 4.42

The Boosted Tip model is a gradient-boosted tree ensemble (XGBoost) trained on 209 historical games to predict the home-team-signed margin from the same model predictions the Weighted Tip model uses. The current model (v60) reaches R² = 0.657 with MAE = 17.9 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