Runs per innings distribution
Run 500 innings to see the outcome range and confidence interval.
A single score is a story. A distribution shows how often the story changes when pitch, opposition, era, and randomness move.
Sensitivity
Longer bars mean the conclusion changes more when that assumption moves.
Normalization ledger
| Assumption | Raw | Adjusted |
|---|---|---|
| Protective equipment | 1979 | neutral |
| Boundary size | venue | matched |
| Fielding | selected | era index |
| Bowling workload | career | matched spell |
Tester feedback report
Exports the setup, seed, distribution summary, and your comments. No proprietary data is claimed.
What the model can and cannot say
Monte Carlo simulation can expose consequences of explicit assumptions, calibrate against known records, and reveal uncertainty. It cannot recreate an unplayed match, fully capture tactics or psychology, or turn incomplete historical data into certainty.
Common traps: cherry-picked venues, unmatched opposition, survivorship bias, small samples, and treating career averages as complete player descriptions.
Knowledge check
Why run hundreds of innings instead of one?
Ball-by-ball