Predication of Final Medal Counts in Olympic Games by Monte Carlo Simulations
Maggie Barker, Daniel Guo, Justin Palmeri, and, Ridge Shepherd

TL;DR
This paper introduces a Monte Carlo simulation-based model to predict Olympic medal counts by evaluating country performances and historical data, validated with Paris 2024 results and used for 2028 forecasts.
Contribution
The paper presents a novel program strength model combined with Monte Carlo simulations to accurately predict Olympic medal outcomes.
Findings
Model accurately predicted 2024 medal counts
Monte Carlo simulations optimized model parameters
Predicted medal counts for 2028 provided as reference
Abstract
In the paper, a program strength model was proposed to evaluate the performance of countries across different Olympic events. The model assessed how strong a country's program was in each event and also factored in the influence of past Olympic performances. The final medal counts from the Paris 2024 Olympic Games were used to validate the model and to determine the optimal set of constants using Monte Carlo simulation. Based on this model, a prediction of the final medal counts for the 2028 Olympic Games is also provides for reference.
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Taxonomy
TopicsSports Analytics and Performance · Sports Performance and Training · Sport Psychology and Performance
