Data Sheet 1_Discrepancies between empirical and theoretical probability in human binary c

21,212 professional Go matches among 311 masters and 586 amateur games from 293 participants form a binary choice model for studying probability discrepancies. The data shows higher-ranked players selected black stones significantly more often than lower-ranked players. Author Yong-Hwan Kim published this 20.8 KB PDF on figshare under a CC-BY-4.0 license, last updated in April 2026.

Use Cases

• Modeling strategic interaction in binary choice games based on the stone selection process described.
• Analyzing the relationship between player skill level and empirical choice probability based on the reported master level correlations.
• Investigating discrepancies between theoretical and empirical probability in human decisions as outlined in the study's objective.

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.
• Focuses on a specific, well-defined binary choice model (stone selection in Go).

Limitations

• The dataset is very small at 20.8 KB, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

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.