Stone Selection in Go Games for Studying Empirical vs. Theoretical Probability

Data from a study investigating discrepancies between empirical and theoretical probability in human binary choices, using stone selection in the game of Go as a model. The dataset includes analyses of 21,212 professional Go matches among 311 masters and 586 games from 293 amateur players. It was authored by Yong-Hwan Kim and last updated on 2026-04-30.

Use Cases

• Analyzing the relationship between player rank and black stone selection probability based on professional match data
• Testing hypotheses about strategic interaction in binary choice games based on the Go stone selection model
• Comparing empirical choice probabilities against theoretical odds in controlled amateur player games
• Modeling sequential strategic decision-making processes referenced in the description

Strengths

• Includes data from a large-scale analysis of 21,212 professional Go matches
• Contains results from controlled in situ games with 293 amateur participants
• Released under a permissive CC-BY-4.0 license for reuse

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• The dataset is very small at 17.2 KB, indicating limited scope

Provenance

Source

Yong-Hwan Kim via figshare

Collection Method

Analysis of professional Go match records and controlled experiments with amateur players

Freshness

Last updated 2026-04-30 05:24:39; freshness should be verified