How often does the player who is behind still win, and by how much behind?

A game with no comebacks feels cruel, and one with too many feels pointless. This entry shows how to group matches by how far a player was behind at a fixed moment and read the odds in each group without trusting groups that are too small.

Why this works

Whether a comeback is fair depends on how far behind the player was, so one overall win rate hides it. Fixing a moment and grouping by size of the gap shows where hope fades, and holding back thin groups stops luck from posing as a pattern.

When not to use it

Don't use it when comebacks aren't meant to be common, such as in games where an early lead should win, or when you have too few matches. Then listen to what trailing players say about whether it felt worth playing on.

In the full entry

• What to build, step by step
• Starting values and the reason for each
• 3 common mistakes and the fix
• 27 lines of example code with 3 checks that pass
• How your AI shows you that it works

Say this to your AI

Use the Spielerando entry "How often does the player who is behind still win, and by how much behind?" (read_entry strat-comeback-by-deficit) in my game. Build it step by step, and show me how you checked that it works.

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