Empirical vs Theoretical Probability in Go Stone Selection, 21k Professional Matches

Research data from Yong-Hwan Kim investigates discrepancies between theoretical and empirical probability in human binary choices using the game of Go. The dataset includes analyses of 21,212 professional Go matches among 311 masters and 586 in situ games with 293 amateur players. The study was last updated on 2026-04-30.

Use Cases

• Modeling strategic interaction in binary choice games based on the stone selection process described.
• Analyzing the relationship between player rank and choice probability based on the described findings for professional and amateur players.
• Studying deviations from theoretical odds in human decision-making based on the described empirical results.

Strengths

• Includes data from 21,212 professional Go matches involving 311 masters.
• Contains results from 586 in situ games with 293 amateur participants.
• Released under a 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 in scale at 355.0 KB, indicating limited data volume.

Provenance

Source

figshare, author Yong-Hwan Kim

Collection Method

Large-scale data analysis of professional Go match records and in situ experiments with amateur players.

Freshness

Last updated 2026-04-30 05:24:36; freshness should be verified.