Olympic Coaching Effect Analysis with Decay Model

Figshare data by You Liu supports a study on the dynamic influence of great coaches on Olympic performance. The 9.5 KB XLS file contains results from a Change-Point Driven Difference-in-Differences with Decay Model, quantifying effect sustainability with metrics like half-life. The model predicts outcomes for the 2028 Los Angeles Olympics.

Use Cases

• Apply the Change-Point Driven Difference-in-Differences with Decay Model to quantify the net effect of coach turnover events.
• Analyze the half-life metric to compare sustainability between systematic coaching systems and technology-driven interventions.
• Use model predictions, such as the forecast for the Brazilian swimming team's medal count in 2028, for strategic resource allocation.
• Filter pseudo-abrupt performance signals by applying the dual test mechanism for medal continuity and competition size stability.

Strengths

• Data underpins a published methodological study proposing an explainable and predictive framework for dynamic causal inference.
• Model outputs include specific quantitative results, such as a 20-year half-life for systematic coaching and a 5.3-year half-life for AI-driven intervention.
• Provides a concrete prediction for the 2028 Olympics: Brazilian swimming team achieving 4.7–6.3 medals with 95% confidence.

Limitations

• Extremely small scale at 9.5 KB, indicating the dataset likely contains only summary model outputs or a few key results, not raw performance records.
• Unknown row and column structure limits direct analytical utility for building or testing machine learning models.
• Geographic and temporal scope of the underlying empirical data is not specified, limiting generalizability.

Provenance

Source

Figshare, authored by You Liu.

Collection Method

Derived from a study applying a Change-Point Driven Difference-in-Differences with Decay Model to Olympic coaching effects.

Time Range

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Freshness

Last updated March 2026.

Geography

Includes case studies on Chinese diving and Japanese judo, with a prediction for the Brazilian swimming team.