JABO: Which Team’s Rotation Overachieved Most in 2015?

Luck. We know it’s a large part of baseball. It’s also the foundation for the central questions we ask when trying to analyze the game: what was a certain player or team’s actual performance? How much control did they have over their production? Can they recreate it next year? We never stop debating these points. We create new statistics to try to answer them a little better than we did last season. And, despite there being certain influences we can’t measure when looking at individual and team production, we do have a few tools at our disposal to tell us who might have been underperformed, and who might have overperformed.

One of those tools is Fielding Independent Pitching, which strips away some of the influences a pitcher can’t control — namely what happens when a ball is put into play and the timing of events that unfold against them. With FIP, we can see who might have gotten unlucky with batted balls finding holes in the defense more often than expected, and conversely, who might’ve benefited from batted balls being hit straight at defenders. After a lot of groundbreaking research, it was found that pitchers don’t have a lot of control over what happens once the ball leaves their hand. Comparing FIP to actual performance — namely ERA — we can see the teams and players who might’ve gotten lucky and unlucky over the course of this past season.

Today, we’re going to look at which team’s starting rotations overachieved and underachieved, as judged by FIP. I’ve charted each starting rotation’s ERA and FIP in an interactive graph, sorted by the best ERA in 2015. If a rotation’s FIP (their expected average runs against) was lower than their ERA (their actual average runs against), they underachieved; if their ERA was lower than their FIP, they overachieved. One of the best things about FIP is that it can be used exactly like ERA, so understanding it is intuitive: treat it exactly like you would Earned Run Average. After we look at the chart, we’ll go through some individual examples, but this should give us a good primer on the subject. Again, feel free to mouse over the chart to see each team’s specific data:

Read the rest on Just a Bit Outside.