CS2 Player Prop Predictions: The Data Method
How to build CS2 player prop predictions from hit rates, sample sizes and posted prices, using real map 1 kill and headshot lines from StatsBench.
sample size
Prediction Interval vs Confidence Interval
A prediction interval vs confidence interval: one covers a single future result, the other your long-run rate. How prop bettors use both.
Longitudinal vs Cross-Sectional Bet Research
Longitudinal vs cross-sectional research, explained for prop bettors: when a player’s game log beats a one-slate snapshot, with real StatsBench data.
Which Situation Involves Descriptive Statistics?
Which situation involves descriptive statistics vs inferential? A clear, bettor-friendly breakdown with real prop data, plus how to use each one. 21+.
Standard Deviation of Percentages in Betting
How to read the standard deviation of percentages like hit rate, why a 60% prop on 10 games proves little, and how to size the error bar around any rate.
Sample Size in Betting: How Much Is Enough?
Sample size in betting decides if a prop hit rate means anything. Learn why 6 of 10 is noise, how many games you need, and how to read hit rates honestly.
Extrapolation Explained for Sports Bettors
What does extrapolation mean, and how do bettors use it on player props? A plain-English guide to projecting stats forward without fooling yourself.
Betting Statistics 101: What They Actually Mean (And How to Use Them)
Betting statistics only help if you know what they measure. Here’s a plain-English guide to hit rates, samples, and how to read them like a bettor.
Why “Last 10 Games” is a Trap in NBA Prop Betting (And How to Fix It)
Seeing a sea of green checkmarks on a “Last 10” log feels good, but it’s often a trap. We break down why raw trends lie, and the 3 specific filters you need to apply to find the real story.