Most of you probably expected an exciting superstar to head the list of the most powerful hitters in baseball. Number one is anything but a superstar, but don't worry though, the superstars aren't far behind. The man who hit this incredible 502 foot blast in 2011 is, by the following measurement, the most powerful hitter in baseball.
That man is the unassuming Juan Francisco who makes up half of the Blue Jays' third base platoon and can flat out smash the ball. Well, against right handers he can flat out smash the ball. Francisco owns an excellent .908 OPS with 12 home runs in 157 at-bats versus right-handers. Conversely, his .356 OPS against left-handers warrants major concern, like why he was put into the box against a lefty at all. As long as Francisco gets a majority of his appearances versus righties then it looks like the Jays have a major asset on their hands, especially considering that Francisco did not even sign a major league contract when he signed with the Jays.
In order to first figure out who is the most powerful hitter, I combined a few different measurements. There are many ways to conceptualize power, but I began with fly ball distance. The more power a batter possesses, the farther a fly ball will travel on average. Fly balls are also a good data source because they have a larger sample size than home runs alone.
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Next, I pulled in two methods of home run measurements. HitTracker Online defines true home run distance as "if the home run flew uninterrupted all the way back to field level." Combining that measurement with standard home run distance, which removes all weather and park related variables from home runs, allows for a more encompassing account of power. Because standard home run distance can variate from true home run distance by as much as 21 feet, using both of them ensures home run distance is being measured fairly.
Home run rates were found for each player and added to the equation. To do so, I wanted to see how many of a particular batter's batted balls ended up over the fences. I modified the BABIP equation ((H-HR)/(AB-K-HR+SF) to solve for this: (HR)/(AB-K+SF+SH). Plugging in the data to date created the number for measuring home run rates.
The last part of the equation was the most subjective. HitTracker Online assigns a value rating to each home run: "No Doubter," "Plenty," or "Just Enough." "No Doubters" must travel 50 feet past the fence and 20 feet above the fence. "Just Enough" home runs are home runs that just barely made it over the fence either ten feet above it or slightly beyond the fence. Everything else (besides inside-the-park home runs) are described as "Plenty." To quantify this, I found the percentage of each player's home runs for each type. For example, a batter may hit eight home runs, two are "No Doubters," four are "Just Enough" and two are "Plenty." That would equate to a 25% ND, 50% JE, and 25% PL line. When finding what I like to call the "Tracker Number," I multiplied the "Plenty" home runs by 2 and the "No Doubters" by 3. Therefore, the "Tracker Number" would be weighted so that farther blasts are worth more than shorter ones.
Eventually, all these measurements were be added together and normalized so that each factor would not have more of an effect on the final statistic than any other. This is meant to be a fun exercise, as there is no perfect way to capture the latent concept of "power." Without further ado, here are the results of the endeavor.
Take a look at the visualization of this data below. The few players near the top become exponentially more powerful than one another as it peaks. Same path applies to the bottom rung of hitters that lack power.
(To access the original data sheet with all the calculations, click here)
The first look at the results can be surprising. As I said before, Juan Francisco is not the person anyone was expecting. I'll provide some further interesting thoughts here.
- Sean Rodriguez is ranked #12 in a backup role with the Rays. At first I was suspicious of the newfound power, and frankly, I'm still suspicious.
- As expected, Ben Revere bottoms the list with (quantifiably) less than half the power someone like Evan Gattis has.
- This is not a predictive formula. In other words, don't use the Power# to try and predict how many home runs a player will hit for the remainder of the season. The data only accounts for the past and one good game can change a lot in terms of ranking.
- This formula only measures power in the form of fly balls. You'll notice that more conventional measures like SLG, ISO, and Batted Ball Distance are not a part of the equation. Additionally, this is not a measure of who is the best at hitting home runs. A lot more goes into the creation of a home run - batted ball angle accounts for half of the battle.
- Rookie George Springer already makes the top ten at age 24. Imagine what he will be able to do in his prime.
- Breakout star Devin Mesoraco ranks #3 on the list, in part, because of his record five straight games with a home run earlier this season.
- Another befuddling player near the top is Mike Olt. The tweet here demonstrates how poor of a batter Olt is when it comes to off-speed pitches. Luckily for him, when he does make contact, he makes a boom with the bat. Strikeouts were removed from the equation so that only batted balls are taken into account, thus giving Mike Olt a chance to shoot up the rankings
- It is hard to look at some of the once-great stars struggle. Derek Jeter ranks 253rd, Howie Kendrick ranks 255th, Dustin Pedroia ranks 250th Joe Mauer ranks 247th, and Jacoby Ellsbury ranks 239th.
- Three batters who qualified did not hit a single home run and would have been ranked last: Gregor Blanco, Eric Sogard, and Adeiny Hechavarria.
- Not all batters qualified. Only the batters that were originally listed on the fly ball data were tracked. Inside-the-park home runs were also completely removed from the equation.
Fly ball power has always been thought of subjectively. My goal was move toward more concrete measurement. Hopefully, others will try to quantify some of the arbitrary baseball terms we use everyday and make suggestions for how the power metric could be improved. Speed already has a few statistics of its own. I encourage you to play with the data by downloading the Google Doc spreadsheet and playing with your own variables.
*All data as of the morning of Friday, July 4th, 2014
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