VMR Analyzer
Determine if a prop market is consistent or volatile compared to Poisson
Enter comma-separated numbers (minimum 5 data points)
The sportsbook line for context
Understanding Variance-to-Mean Ratio
The Variance-to-Mean Ratio (VMR), also called the index of dispersion, measures whether data is more or less spread out than a Poisson distribution would predict.
VMR = Variance / Mean = σ² / μ
For a Poisson distribution, the variance equals the mean, so VMR = 1.0. This is the baseline for count-based props.
- VMR < 1.0 (Under-dispersed): The player is more consistent than expected. Outcomes cluster tightly around the mean.
- VMR ≈ 1.0 (Poisson-like): Standard randomness. A Poisson model fits well.
- VMR > 1.0 (Over-dispersed): The player is more volatile. Consider using a Negative Binomial distribution instead.
VMR helps you choose the right statistical model for pricing props. Using the wrong distribution can lead to mispriced probabilities and bad bets.
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