Player Prop Simulator

How the NBA Player Prop Simulator Works

This tool uses a Monte Carlo simulation — the same statistical method used in quantitative finance — to model an NBA player's performance distribution and calculate the true probability of hitting a sportsbook prop line. Instead of relying on a simple average, the model runs 1,000 independent game simulations and estimates how often the player would statistically exceed the given line.

The Three Inputs That Matter

• Season Average: The player's statistical baseline for the season. This is the anchor of the model.
• Recent Form (Last 5 Games): When entered, the model weights recent performance at 60% and season average at 40%. A hot streak or cold stretch has real predictive value that pure season averages obscure.
• Volatility (Standard Deviation): How consistent is this player game to game? Consistent players like Nikola Jokic have low volatility (3.5-4.5 on rebounds). Streaky shooters have higher volatility. The category presets give you a starting point but you can adjust.

The Edge Calculation — The Most Important Number

When you enter the bookmaker's American odds on the Over, the simulator calculates the implied probability baked into those odds and compares it to the simulated probability. A sportsbook offering -110 on the Over is implying a 52.4% probability. If the simulation returns 61%, your mathematical edge is +8.6% — meaning the line is undervalued and the Over represents positive expected value over time.

Default Volatility Values by Stat

• Points: 5.5 — scoring has high game-to-game variance for most players
• Rebounds: 2.5 — rebounding is more consistent night to night
• Assists: 2.0 — assists vary with matchup and pace but less wildly than scoring
• 3-Pointers Made: 1.5 — shooting volume is relatively stable even when makes fluctuate
• Pts+Reb+Ast: 7.0 — combined stats smooth individual fluctuations but total variance is higher