Determinants of Scoring in the RSM Classic

This analysis is based on scores and stats from individual rounds in the last ten RSM Classics: 4,537 rounds in total.

Section 1: Absolute Correlation Coefficients with Score

Key Insights:

• SGApp consistently shows strong correlations with Score, highlighting the importance of approach play at The RSM Classic.
• SGTee saw a sharp rise in correlation in 2018, suggesting a pivotal role for tee shots that year.
• SGP has the weakest correlation, indicating putting is less critical compared to other metrics.

Key Insights:

• GreensInRegulation consistently correlates highly with Score, peaking in 2018, showcasing its importance in determining success.
• DrivingDistance saw a notable spike in 2019, indicating the course setup favoured long hitters that year.
• Scrambling becomes more relevant when GreensInRegulation correlations are lower, highlighting its role in recovery play.

Key Insights:

• Par4 consistently has the highest correlation, especially peaking in 2019, emphasising its critical role in scoring.
• Par5 correlations fluctuate, reflecting dependency on specific course setups.
• Par3 correlations are stable but generally lower, indicating their lesser impact compared to other par categories.

Section 2: Importance of Each Metric in Determining Score

Random Forest Regressor and Feature Importance

Random Forest Regressor is an ensemble learning method that constructs multiple decision trees during training and outputs the average prediction. It combines the predictions of several models to improve accuracy and robustness.

Feature importance is a technique used to interpret a machine learning model. It refers to the score that quantifies the contribution of each feature to the prediction made by the model.

In a Random Forest, the importance of a feature is computed by looking at how much the feature decreases the impurity (e.g., variance for regression tasks) across all the trees in the forest. The more a feature decreases the impurity, the more important it is considered.

The calculated importance scores for all features are then normalized to give relative importance as a percentage. This shows the relative contribution of each feature to the prediction task.

Interpreting Feature Importance

Features with high relative importance percentages have a strong impact on the model's predictions. They are crucial for accurate predictions and indicate key areas where performance matters most.

Features with low relative importance have a minimal impact on the model's predictions. While they can still contribute, they are less critical.

Key Insights:

• SGTee has a 5.66% lower relative importance compared to the PGA Tour average, indicating reduced influence at The RSM Classic.
• SGApp has a 3.86% higher relative importance compared to the PGA Tour average, highlighting its elevated impact at The RSM Classic.
• SGP has a 13.21% higher relative importance compared to the PGA Tour average, highlighting its elevated impact at The RSM Classic.

Key Insights:

• DrivingDistance has a 2.88% lower relative importance compared to the PGA Tour average, indicating reduced influence at The RSM Classic.
• GreensInRegulation has a 7.71% lower relative importance compared to the PGA Tour average, indicating reduced influence at The RSM Classic.
• PPGIR has a 14.20% higher relative importance compared to the PGA Tour average, highlighting its elevated impact at The RSM Classic.

Key Insights:

• Par3 has a 0.96% higher relative importance compared to the PGA Tour average, highlighting its elevated impact at The RSM Classic.
• Par4 has a 0.53% higher relative importance compared to the PGA Tour average, highlighting its elevated impact at The RSM Classic.
• Par5 has a 1.49% lower relative importance compared to the PGA Tour average, indicating reduced influence at The RSM Classic.

Top 5 Ranked Players - 2024 RSM Classic

The table below shows the top-5 ranked players and their average estimated scores from the different Random Forest models above.

Estimated scores for all players can be found here.