Start here · Essential guide
Variance and Standard Deviation in Games of Chance
How variance and standard deviation measure the spread of results around the average, explained with simple coin and dice examples and checked arithmetic.
Design and Decisions
Swings, streaks and why short runs differ from long-run averages.
Start here · Essential guide
How variance and standard deviation measure the spread of results around the average, explained with simple coin and dice examples and checked arithmetic.
A general explanation of how stake size relates to swings and expected loss, using checked examples and without suggesting any way to profit.
How confidence intervals show how much a small sample of wins and losses really tells you about a true win rate, with worked and checked examples.
The classic gambler's ruin problem explained with small worked examples: why a finite bankroll meets a negative expectation and eventually runs out on average.
Why outcomes over a few plays vary widely while averages settle only over many, shown with coin-flip arithmetic and clear limits on what long runs mean.
Why genuinely random sequences contain more streaks and clusters than people expect, with checked coin-flip examples and a note on what streaks do not mean.
The Kelly criterion explained as theory: how it relates stake size to a known edge, why it gives zero when the edge is negative, and what it cannot do.
What the law of large numbers does and does not promise, with coin and dice examples, and why it is not the same as the gambler's fallacy.
Why sums of many random events form a bell curve, illustrated with dice and coins, with the one and two standard deviation rules of thumb and their limits.
How game volatility contrasts frequent small outcomes with rare large ones at the same average, using two simple illustrative games with checked arithmetic.
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