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playerElo: Factoring Strength of Schedule into Player Analysis

*Note: All numbers updated to August 12th, 2019*

Introduction

Consider the following comparison between Freddie Freeman (29) and Carlos Santana (33). Both players were starters for the 2019 All-Star teams of their respective leagues, and both are enjoying breakout seasons beyond their usual high production level, with nearly identical statistics across the board.

  PA wOBA xwOBA wRC+
Freeman, 1B 533 0.400 0.398 146
Santana, 1B 503 0.390 0.366 142

However, I argue that there is an underlying statistic that makes Santana’s success less impressive and Freeman’s worth MVP consideration. Recall the quality of competition of pitchers faced. The Atlanta Braves’ division, the NL East, contains the respectable pitching competition of the Mets (13th in league-wide in ERA), Nationals (15th), Marlins (16th), and Phillies (19th). Contrast this with the competition of the Cleveland Indians in the AL Central: The Twins (ninth), White Sox (22nd), Royals (24th), and Tigers (28th). Over 503 plate appearances, Santana has faced a top-15 pitcher (ranked by FIP) just 15 times, compared to 46 times by Freeman over 533 plate appearances. wRC+ controls for park effects and the current run environment, while xwOBA takes into account quality of contact, but all modern sabermetrics fail to address the problem of Freeman and Santana’s near-equal statistics despite widely different qualities of competition. Thus, I present the modeling system of playerElo. Read the rest of this entry »