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October 17, 2025Deleted Journal

Predicting the 2028 Los Angeles Olympic Medal Table: A Machine Learning Approach with Gradient Boosting and Random Forest Models

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Authors

WGWeijun Gao

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Overview

This analysis uses machine learning techniques to predict medal counts in the 2028 Olympics, highlighting historical trends and coaching influence.

Key Points

  • The prediction model achieves an R^2 of 0.65, indicating a moderate fit for predicting Olympic medal outcomes.
  • By leveraging historical data, the study highlights the significance of factors like coaching impact and event settings on medal counts.
  • Emerging powerhouses are classified separately, with tailored machine learning models applied to improve forecast accuracy.
  • Key projections include the United States and China each leading with 92 total medals and 39 golds, followed by Britain, Australia, and Japan.

Cite This Study

Weijun Gao (2025) studied this question.

synapsesocial.com/papers/68f199ccde32064e504dd14bhttps://doi.org/10.54097/qh0xxk54
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Also Consider

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  1. 1Olympic Medal Prediction Based on Machine Learning Models2025
  2. 2A Quantitative Study of Medal Predictions and the Impact of Good Coaching at the Los Angeles Olympics2025
  3. 3Unlocking Olympic Success: Predictive Modeling and Strategic Insights for the 2028 Games2025
  4. 4Olympic Medal Count Prediction Research Based on A Hybrid ARIMA-Xgboost-Lightgbm Model2025
  5. 5Research On Olympic Medal Prediction Based on Random Forest-ARIMA Combined Model2025