Separating Signal from Noise in Results

## The Fundamental Challenge Every result is a mix of signal (reflecting genuine edge or its absence) and noise (random variance). The central challenge of performance evaluation in betting is separating these two components. ## The Sample Size Reality Statistical significance in betting requires large samples: - 100 bets: almost no distinguishable signal from noise - 300 bets: weak signal — trend visible but not reliable - 500 bets: moderate confidence in edge estimation - 1,000 bets: strong confidence; 95% CI narrow enough for meaningful conclusions - 2,000+ bets: near-definitive edge validation A 5% ROI over 200 bets could be genuine edge OR luck. The same 5% ROI over 1,000 bets is very likely genuine edge. ## The CLV Shortcut CLV-based analysis is signal-rich even at smaller samples. Because CLV compares your price to the most efficient price in the market (Pinnacle closing), positive CLV at 200 bets is more informative than positive ROI at 200 bets. This is why CLV tracking is the preferred short-sample indicator — it filters out result noise and isolates the genuine market position signal. ## The Noise Floor All betting strategies operate above a "noise floor" — the level below which results cannot be reliably distinguished from chance. Operating near this floor (with small samples and small edge) requires particular discipline: acting on results that may be noise creates costly strategy changes. The discipline: do not change a strategy based on short-sample results. Change a strategy based on long-sample CLV trends, model calibration failures, or clear process errors — not because results have been bad for 2 months. ## The Signal Test Before making any strategic change based on results: ask "Is this signal or noise?" Calculate the 95% confidence interval for your performance metric. If the confidence interval includes zero (no edge): cannot distinguish from noise. Do not change strategy.