Distribution Selector
Answer a few questions to find the right statistical distribution
Is the outcome a whole number (count-based)?
Why Distribution Selection Matters
Choosing the right statistical distribution is the foundation of accurate prop modeling. Using the wrong distribution leads to mis-estimated probabilities, which means you'll misjudge your edge and make unprofitable bets.
Poisson works for low-count discrete events (touchdowns, goals) where variance roughly equals the mean. Negative Binomial handles overdispersed data where variance exceeds the mean, common in yardage-based props. Normal applies to continuous outcomes or high-volume counts where the Central Limit Theorem kicks in.
The Variance-to-Mean Ratio (VMR) is a key diagnostic: VMR ≈ 1 suggests Poisson, VMR > 1 suggests Negative Binomial, and very high volumes often justify Normal regardless. When in doubt, check the VMR with our VMR Analyzer tool.
For a deeper dive into the selection framework, read the Selecting the Right Distribution module.
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