Study: What Are The Best Metrics For Evaluating Hitters?

Recently, we’ve concluded what the most reliable metrics are for evaluating defense and pitching. However, today’s study is a critical one with regards to what moves the needle in the modern MLB. Here, at, we’ve already found that hitting is about five times more predictive of winning than defense, and is still more important than pitching. Therefore, teams need to be able to build as lethal of an offense as they can, which is where this study comes in; today, we’ll conclude what the best statistics are for judging a player’s offensive ability.

In this study, the goal is to discover which metrics are the most stable. Front offices want  to have players who they believe will perform well on a yearly basis, and in order to feel good about a hitter’s prospects, it’s best that they rate well on stable metrics. Meanwhile, if a hitter’s success is tied to less stable metrics, they are far less reliable and will likely struggle with inconsistency. To assess the stability of each metric, I plotted how each qualifying hitter fared in a statistic from one year to the next, going through 2015 to acquire a large enough sample size. By judging the coefficient of determination for each of the scatterplots, we’ll be able to gauge the reliability of each major hitting statistic.

With hitters, there are generally two different categories of statistics. There are the “peripheral” statistics, such as their strikeouts, walks, and hard contact rate , and then there are the “slash-line metrics”. Those “slash-line” metrics, such as on-base percentage, batting average, and weighted-runs-created-plus (wrc+) essentially attempt to tell the story of a quality of a hitter with one number, so it goes hand and hand with peripherals.

To start, we’ll examine the stability of each of the main peripheral statistics. For this exercise, they’ll be split into the following two categories: batted ball and plate discipline.

Batted Ball

Second Year BABIP vs. First Year BABIP


Second Year Hard% vs. First Year Hard%

Second Year LD% vs. First Year LD%-2

Second Year GB_FB vs. First Year GB_FB-2

Much like with pitchers, hitters are generally able to control the trajectory of their contact; it’s really just predicted on their approach and the amount of launch they are able to generate with their swing. Also, similarly to pitchers, hitters don’t tend to be able to consistently have a high line drive rate, which further backs up the idea that the art of having the perfect launch angle at the point of contact is mostly luck. Furthermore, although some hitters consistently have a high batting average on balls in play (BABIP) or low BABIP, the general population are unable to control their luck. Take Mookie Betts as a prime example. Although his batted ball numbers barely changed, his BABIP dropped from .368 to .309; he went from a 185 wrc+ to a 135 wrc+ mostly off of a shift in luck. Where hitters do contrast from pitchers, though, is that they have a higher ability to sustain their hard contact numbers- it’s clear that the quality of contact is more swayed by a hitter than the pitcher they are facing.


Second Year BB% vs. First Year BB%-2

Second Year K% vs. First Year K%

Second Year Sw Strik% vs. First Year Sw Strik%-2

Second Year Contact vs. First Year O Contact

Second Year Z Contact vs. First Year Z Contact

Second Year Chase vs. 1st Year Chase

Although hitters can generally control the quality of their contact, it doesn’t compare to the year-to-year stability of their plate discipline. Despite the fact that evaluators tend to believe that the ability to draw walks and make contacts can be taught and developed over time, I’m not sure that is actually the case. Based on this data, with very high coefficients of determination for each of these statistics, it appears that whiffs and the ability to recognize pitches is pretty stable.

Now that we determined that plate discipline is undoubtedly the most stable skill, with the quality of contact shortly behind, let’s see how reliable each of the main hitting statistics are:

Second Year AVG vs. First Year AVG

First Year OBP and Second Year OBP

Second Year SLG vs. First Year SLG

Second Year ISO vs. First Year ISO

Second Year wOBA vs. First Year wOBA

Second Year wrc+ vs. First Year wrc+

Second Year WPA vs. First Year WPA

Unsurprisingly, since BABIP luck tends to vary year-to-year, a hitter’s batting average shouldn’t be expected to be stable. However, the fact that it’s about as stable as more complex metrics such as wrc+ and weighted on-base average (wOBA) is fascinating, as it says a lot about the volatility of power. The ability to hit for power is generally seen as a natural skill, but is it really? After all, a player’s slugging percentage can be greatly impacted by the stadiums they play in and the quality of the opposing team’s outfield defense; any statistic that is dependent on external factors isn’t going to be stable. That also explains the results for Win Probability Added (WPA), which requires a hitter to have a lot of opportunities in high-leverage situations. Furthermore, as we should expect considering how well plate discipline metrics tend to correlate on a yearly basis, on-base percentage takes the cake as the top “slash-line” metric; for power, isolated power (slugging percentage-batting average) is a better metric than slugging percentage.

If you’re looking for one or two main statistics to project a hitter, I’d recommend using on-base percentage and isolated power. However, it’s clear from these results that in order to be as precise as possible with your projections, it’s better to dig deep into a hitter’s peripheral numbers. Although wOBA and wrc+ rightfully value on-base ability more than power, so they are useful when deciding on awards and judging a player’s production in just that one year, I wouldn’t even take them into account when projecting for the following season. Nevertheless, the main takeaway from this study has to be how much more stable on-base ability is compared to hitting for power. The general belief is that teams should target young players who have a lot of raw power, as they can teach them to have a better approach at the plate. Now, though, it appears we may have it backwards. A team like the Dodgers, for instance, has consistently targeted players with refined on-base ability, and have taught them to hit for power over time with swing adjustments, so it should come to no surprise that they consistently are an offensive powerhouse. Meanwhile, teams like the White Sox and Rangers, who have typically targets those “high-upside” prospects with a lot of power, have hit a crossroads in their rebuild. In the end, the difficulty of being consistently lucky is immense, and considering how valuable offense is, teams need to be able to count on their main hitters. By targeting players who can get on base, as well as buying-low on players with low BABIP and power numbers, they can take the first step forward towards building a winning lineup.

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