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

Data Sheet 4_Discrepancies between empirical and theoretical probability in human binary choices within the game of Go.xlsx is a dataset by Yong-Hwan Kim investigating binary choice probability in the game of Go. It contains data from 21,212 professional matches among 311 Go masters and 586 games from 293 amateur players. The dataset was last updated on 2026-04-30.

Use Cases

• Analyzing the relationship between player rank and stone selection bias based on the professional match data.
• Modeling binary choice behavior in strategic interactions based on the described sequential stone selection process.
• Testing hypotheses about empirical probability discrepancies in human decisions based on the amateur player experiments.

Strengths

• Includes data from a large-scale analysis of 21,212 professional Go matches.
• Contains experimental data from 293 amateur participants, each playing 2 games.
• Released under the permissive CC-BY-4.0 license.

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 small at 51.7 KB, indicating limited scope.

Provenance

Source

Yong-Hwan Kim via figshare.

Collection Method

Analysis of professional match records and in situ experiments with amateur players.

Freshness

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