Documentation
Technical Specification
Paper-ready documentation with model formulations and methodology.
Read Technical DocsAPI Examples
Get Race Predictions
GET/api/f1/predict/race/{race_id}?model=xgb
curl "http://34.204.193.47:8000/api/f1/predict/race/2024_01?model=xgb"Get Explanation
GET/api/f1/explain/race/{race_id}?driver_id=VER&model=xgb
curl "http://34.204.193.47:8000/api/f1/explain/race/2024_01?driver_id=VER&model=xgb"Counterfactual Analysis
POST/api/f1/counterfactual?model=xgb
curl -X POST "http://34.204.193.47:8000/api/f1/counterfactual?model=xgb" \
-H "Content-Type: application/json" \
-d '{
"race_id": "2024_01",
"driver_id": "HAM",
"changes": {"qualifying_position_delta": -2}
}'Available Models
xgb, lgbm, cat
Gradient boosting models with SHAP explanations
lr, rf
Linear and ensemble models with permutation importance
quali_freq
Baseline using historical qualifying position frequencies
elo
Pairwise rating system updated chronologically
nbt_tlf
Neural Bradley-Terry with temporal latent factors and ablation analysis