DanielTomaro13/sportsdata-agents
Skill Claude CodeCodex
How to design and read backtests honestly — lookahead/leakage traps, point-in-time discipline, multiple comparisons, CLV vs ROI, sample size.
6 yesterday A 36 tokens
original MIT
DanielTomaro13/sportsdata-agents
Skill Claude CodeCodex
The general model-building method for ANY market — framing, sample-size discipline, feature selection (user priors + data-driven), baselines, leakage-safe validation, calibration, persistence.
6 yesterday A 40 tokens
original MIT
DanielTomaro13/sportsdata-agents
Skill Claude CodeCodex
Working definitions of the core quant concepts — Brier, log-loss, calibration, logistic regression, gradient boosting/XGBoost, regularization, walk-forward CV, CLV — and when each tool fits.
6 yesterday A 45 tokens
original MIT