“In the simplest terms, position scarcity exists when there are not enough positively valued players at a position to fill up every active roster.” – Mike Podhorzer, from a Fangraphs article titled “On Position Scarcity…Again”
We’re going to go position-by-position and break down an MLB roster, break down the landscape of MLB rosters across the league, and discuss what these findings mean to us from a DFS perspective.
*wOBA and xwOBA defined on the next chapter
Catcher: MLB-median for wOBA and xwOBA amongst catchers was .297 and .316 last season, respectively.
First Base: MLB-median for wOBA and xwOBA amongst first basemen was .347 and .345, respectively.
Second Base: MLB-median for wOBA and xwOBA amongst second basemen was .308 and .301, respectively.
Third Base: MLB-median for wOBA and xwOBA amongst third basemen was .329 and .327, respectively.
Shortstop: MLB-median for wOBA and xwOBA amongst shortstops was .318 and .313, respectively.
Outfield: MLB-median for wOBA and xwOBA amongst second basemen was .331 and .329, respectively.
Okay, so what positions carried the lowest wOBA and xwOBA over the course of the season? Catcher, second base and shortstop. Remember this fact as we get into the Game Theory lesson. Catchers, second basemen and shortstop carry the largest standard deviation in expected production of the available positions in addition to being lower-median-scoring positions. This is going to lead to a few players at each position who are also going to carry some of the largest standard deviations in pricing, which we need to pay attention to when we start thinking about things like crowd psychology and epistemology here shortly.
We also have positional scarcity at the pitcher position, but I want you to think about it a little differently. Think about positional scarcity for pitchers as a sliding scale, where the left side of the scale rests the innings-eaters, the pitchers that are relatively unassuming from looking at the box score but typically go 5-6 innings with three to five strikeouts, think about the middle of the scale as the highest variance pitchers, the ones that bring high K-rates and high walk rates, and the right side of the spectrum are the pitchers with high K-rates and good run suppression through low walk rates and low hard hit values. The further right we go on that sliding scale, the fewer pitchers there are in the league, creating a form of positional scarcity. We’ll see the same pricing standard deviations as we do with positional players, but the price buys you increased floor and a tighter range of outcomes with pitching.