tERA, the Pitching Metric of the Future

The year is 2050. Tim Lincecum Jr.-using the same famed delivery of his Hall of Fame father-has just won his 2nd consecutive Cy Young award. Lincecum Jr. lead the league in wins, ERA, and WHIP. These stats have almost become obsolete in determining the winners of the major MLB awards. That’s right, even the BBWAA has adopted the use of deep statistical analysis to determine who the best hitters, pitchers, and rookies are. Lincecum Jr. also was the far-and-away leader in a few key advanced statistics like FIP, WAR, tRA, and the newly created but widely used True ERA (tERA).

tERA, since its creation in 2009, has been a giant work in progress. In fact, the stat only became relevant recently once the sample size became large enough. That’s right, it took nearly 40 years to gather all of the data needed to create the most flawless pitching metric the SABR community has seen.

With the wide-spread use of HIT /fx beginning in April of 2009, tERA began its epic journey to become the greatest pitching statistic of all-time. So, what exactly is tERA? Well, it is the first truly DNPS (Defense Neutral Pitching Statistic). Using the trajectories and bat speed of each ball hit into play tERA will measure the exact percentage of times a batted ball will go for a single, double, triple, or out. For example, say a batter with the bases empty hits a ball with x velocity and y trajectory and it lands at location z, tERA will have enough data (40 years worth) to determine how that play turns out with a completely average fielding team. Let’s say the aforementioned ball would drop in for a single 20% of the time, get past the defender for a double 45% of the time, and be caught for an out 35% of the time. This play would then be worth (.29)(.20)+(.45)(.49)-(.35)(.20)=.2085 runs against. Unlike statistics before it such as FIP that paid zero attention to the situation of the game, tERA will be able to level upon itself because each play will measure a pitchers true ability. Complicated linear weights will be used to calculate the tERA for the 2nd, 3rd, 4th, etc batter of each inning because tERA is a completely neutral statistic. In other words, the pitcher can be held 100% accountable for his actions as expressed by tERA. Let’s run through an example. If the first batter of an inning hits a ball in the exact same location with the exact same trajectory as the previous example, we obviously have a situation where there is a base runner on first 20% of the time, a base runner on second 45% of the time, and no base runner 35 percent of the time. To make the math a little simpler, let’s say that the next batter hits home run. That is a play worth 1.00 runs with bases empty, 1.74 with a runner on first, and 1.60 with a runner on second. We then have to take the result of the first batter and use leveling to get the true value of this second outcome. The math looks like this: (.20)(1.74)+(.45)(1.60)(.35)(1.00). This equals .348+.72+.35=1.418 runs against. In this situation, the pitcher has given up two runs, but because a truly average defensive team would have made the first play 35% of the time, the pitcher is only held accountable for 1.6265 runs.

And therein lies the beauty of tERA. Every pitcher will be judged against the exact same baseline, with regards to game situation (read: “clutch”), and with a highly perfected way to measure truly earned runs.  tERA truly revolutionized the way baseball was looked at from an analytic perspective, and judging the value of pitchers has never been easier.

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6 Comments on “tERA, the Pitching Metric of the Future”

  1. Disco Says:

    Fucking awesome. This is the first I’ve heard of it, where’d you find out about it?

  2. Disco Says:

    Ah, I read it again without skimming. I got it.

  3. bkirst1 Says:

    my brain just exploded


  4. [...] While I like FIP and x-FIP, it doesn't try to measure game conditions. It ignores defense and assumes that batted balls are not relevant. Enter tERA. tERA stands for true Earned Run Average. x-FIP assumes that there is a normalized home run rate. What tERA tries to do is measure the pitchers performance but also includes batted ball data and game conditions. It's also backed up by 40 years of game data to show how a ball hit in similar circumstances over the years would react. Here is a site Explaining tERA. [...]


  5. […] to some extent.  Instead, what I would use is something more similar to a hitting equivalent of this version of tERA I found on a baseball blog.  What that article proposes is something much more detailed than what […]


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