Louis Dallimore //Strength & Conditioning
Tool 01//Rugby Moneyball Predictor PairAnalytics

The match model is LASSO logistic regression with class-balanced weighting, trained on 302 team-match outcomes pooled across Japan Rugby League One D1 23/24 (n=194) and D2 24/25 (n=108). Pooled AUC 0.894 (95% bootstrap CI [0.86, 0.93]); cross-league transfer 0.86-0.89.

The player model is the Pt 4 Layer 2 fit: position-controlled OLS on 34 Bronco-tested Kintetsu players (median 7 player-matches each across both seasons). Only height has a bootstrap-stable effect on the carry-metres family; other physical predictors come with wide uncertainty. The profile output is illustrative and the disclosure says so on the predict pane.

Both predictions run in the browser; nothing you enter is sent anywhere. URL state syncs for the match tab so the prediction is shareable.

Quick-load · real Kintetsu matches
Match inputs
Predicted win probabilityToss-up
52%
baseline 52%
0%100%
Figure // SHAP-style attributionlogit contributions
← LOSSWIN →Points per carry+0.00Yellow cards+0.00Turnover diff+0.00LBs per defender beaten+0.00Metres per carry+0.00Post-contact m/carry+0.00Dominant carry %+0.00Missed tackle %+0.00Possession %+0.00Territory %+0.00Penalties conceded+0.00Offloads+0.00Kicks+0.00
Each bar = standardised feature value × model coefficient. Bars right of zero push toward win, left of zero toward loss. Sum + intercept → log-odds → probability. Sorted by magnitude.
Model honesty

Trained on 302 team-matches across 20 Division 2 clubs (full 2025 season). AUC 0.91, 95% bootstrap CI [0.88, 0.94]. Single-team predictions still vary widely. Strong illustrative model, not a tactical decision tool. See the methodology essays for the full picture.