NRL
Performance

How our tipping heuristics are performing.

Current Season 2026

31 / 31 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 $321.00
Projected Annual Profit $321.00
Projections are based on early season performance and may change as the season progresses.
Accuracy60.6%
Rounds Played31
Avg Profit/Round $10.35
Odds Coverage0%

Weighted Tip

Current Season
Year-to-Date Profit $397.00
Projected Annual Profit $397.00
Projections are based on early season performance and may change as the season progresses.
Accuracy62.4%
Rounds Played31
Avg Profit/Round $12.81
Odds Coverage0%

Boosted Tip

Current Season
Year-to-Date Profit $1176.00
Projected Annual Profit $1176.00
Projections are based on early season performance and may change as the season progresses.
Accuracy81.7%
Rounds Played31
Avg Profit/Round $37.94
Odds Coverage0%
Individual Model Accuracy
Elo Rating★
61.0%
Accuracy
$340
Profit
Form
59.5%
Accuracy
$268
Profit
Value
58.2%
Accuracy
$226
Profit
Home Advantage
52.9%
Accuracy
$9
Profit
Matchup
49.4%
Accuracy
$-48
Profit

Weighted Tip Model

v79
Trained: Tue, 10 Nov, 08:00 amTraining rows: 213Intercept: 0.34R²: 0.1004MAE: 15.4

The Weighted Tip model combines all 5 ML model predictions using a linear regression trained on 213 historical games. Each model contributes a margin weight (influence on score margin) and a confidence weight (influence on confidence). The current model (v79) has R² = 0.100 with intercept 0.34. 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 =0.34+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)

v65
Trained: Tue, 10 Nov, 08:00 amTraining rows: 213R²: 0.6738MAE: 9.0SHAP base value: -0.04

The Boosted Tip model is a gradient-boosted tree ensemble (XGBoost) trained on 213 historical games to predict the home-team-signed margin from the same model predictions the Weighted Tip model uses. The current model (v65) reaches R² = 0.674 with MAE = 9.0 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 value win rate diff, elo rating diff, form wins diff the most influential.

SHAP Feature Importance