Start here · Essential guide
Simulating Games: Using Code and Spreadsheets to Test Odds
Learn how game simulation estimates probabilities that are hard to derive by hand, using short scripts or spreadsheet formulas and simple checks on accuracy.
Applied Math
Simulation and Statistics Tools
Spreadsheets, code and tests for checking game claims.
Building a Dice Probability Table in a Spreadsheet
Build a dice spreadsheet step by step: list every outcome, count sums with COUNTIF, convert to percentages, and compare your table with simulated rolls.
Chi-Square Tests for Checking Loaded Dice
Learn how a chi-square test compares observed die counts with the counts a fair die would give, with a worked example, formulas, and cautions on interpretation.
Common Mistakes When Tracking Your Own Game Results
Tracking mistakes such as selective logging, shifting categories and stopping at a good moment can mislead you about your skill. Here is how to keep cleaner records.
Confidence Intervals for Win Rates
See how uncertain an observed win rate is. Worked examples of 10, 100 and 1,000 games show how the confidence interval narrows as the sample size grows.
Monte Carlo Methods Explained with a Simple Card Game
A step-by-step Monte Carlo method example: estimate the chance of drawing at least one ace in five cards, then check the estimate against the exact answer.
Random Number Generators in Games Explained
How random number generators work in games: pseudo-random sequences, seeds, what statistical quality they guarantee, and the mistakes that cause biased results.
Sample Size and Statistical Significance in Game Data
How many games before a difference means anything? Learn how statistical significance and sample size work, with worked examples for win rates and rule changes.
Seeds and Reproducible Randomness
Random seeds explained: how a starting value makes a pseudo-random sequence repeatable, how to use them in Python and spreadsheets, and the mistakes to avoid.
Visualizing Outcome Distributions with Histograms
Learn to plot game results as outcome histograms so the shape of the spread is clear: bin choice, counts versus proportions, and what skew and tails reveal.
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