## The Perennial Question
"How many bets do I need before my results are meaningful?" This question is central to every betting operation. The answer depends on the size of the edge you are trying to detect.
## The Signal-to-Noise Problem
A small edge (2% ROI) is harder to detect in a noisy dataset than a large edge (8% ROI). The required sample size to distinguish real edge from random variance scales with the square of the edge — smaller edges require much larger samples.
## A Practical Guide to Sample Size Requirements
For a 5% significance level (95% confidence) to detect a true edge:
| True Edge (ROI) | Required Bets |
|---|---|
| 8% | ~150 bets |
| 5% | ~350 bets |
| 3% | ~950 bets |
| 2% | ~2,100 bets |
A typical professional bettor targeting 3% ROI needs approximately 1,000 bets before they can be reasonably confident their results are not pure luck.
## Why Most Bettors Misread Their Results
After 200 bets with 4% ROI, many bettors conclude they have "proven" their edge. Statistically, 200 bets at 4% ROI is consistent with both genuine 4% edge AND zero edge with lucky variance. The confidence interval is too wide to conclude anything.
## The CLV Shortcut
Closing Line Value (CLV) requires smaller samples to detect genuine edge than results-based ROI. This is because CLV directly measures market position (did you beat the closing price?) rather than outcomes (did the selection win?). 200 bets of consistently positive CLV is meaningful evidence; 200 bets of positive ROI is not.
## The Practical Approach
- Track CLV from bet 1 (meaningful early signal)
- Track ROI but do not interpret it until 500+ bets
- Do not change strategy based on short-sample results (either direction)
Create a free account to track your progress and save bookmarks.
