Empirical vs. Theoretical Probability in Human Binary Choices from Go Games

21,212 professional Go matches among 311 masters and 586 amateur games from 293 participants were analyzed to investigate discrepancies between empirical and theoretical probability in binary choices. The data, authored by Yong-Hwan Kim and last updated in April 2026, shows higher-ranked players had a significantly higher chance of selecting black stones. This suggests human binary choice odds may not equal theoretical expectations, relevant to game theory and decision-making research.

Use Cases

• Modeling strategic interaction in binary choice games based on the described stone selection process.
• Analyzing the relationship between player skill level and choice probability based on the reported rank-based discrepancies.
• Studying deviations from theoretical probability in human decision-making using the described large-scale game data.
• Investigating sequential strategic interactions similar to matching pennies, as mentioned in the description.

Strengths

• Includes data from 21,212 professional Go matches involving 311 masters.
• Contains results from in-situ games with 293 amateur participants, each playing 2 games.
• Explicitly tests a hypothesis about empirical versus theoretical probability in a controlled context.
• Released under a permissive CC-BY-4.0 license.

Limitations

• Dataset is very small at 18.5 KB, indicating limited scope or aggregated summary statistics.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.

Provenance

Source

figshare, author Yong-Hwan Kim.

Collection Method

Analysis of professional Go match records and in-situ games with amateur players.

Freshness

Last updated 2026-04-30 05:24:38; freshness should be verified.