Thomas Vacanti
April 4th, 2013
WRT 381: Writing In Sports
Personal Essay
Statistics In Baseball: The Endless Debate
Wednesday, October 3rd 2012 in Kansas City, Missouri. The Detroit Tigers were playing the Kansas City Royals on a crisp autumn evening, two teams headed in different directions. The Tigers, freshly crowned the 2012 American League Central champions, were headed to their second consecutive postseason appearance while the Royals were wrapping up their season. Manager Jim Leyland, whether Miguel Cabrera was about to set a milestone or not, was likely going to pull him from this game. Unexpectedly, after Cabrera had taken his place at third base in the bottom of the fourth inning, Leyland motions Cabrera back to the dugout as utility infielder Ramon Santiago ran from the dugout to take his place. As Cabrera returned back to the dugout, every fan in Kansas City, including Royals fans, was on their feet, giving him a standing ovation.
What did Cabrera do to deserve such an ovation in hostile territory? He had just accomplished what no hitter has done since 1967, 45 years prior, when Carl Yastrzemski accomplished the feat for the Boston Red Sox: he had just completed a season where he won the Triple Crown. The Triple Crown club is one of the most exclusive clubs in all of professional sports, and a player wins the Triple Crown when he leads his league (American League or National League) in three categories: batting average, home runs, and runs batted in (RBI). It is such a rare feat, that only twelve Major League Baseball (MLB) players have ever completed it in the modern era, and it has only happened once since the 1960s. For comparison, twenty-three pitchers have thrown a perfect game in MLB history. One can assume, because the Triple Crown is so rare, because no one had done it in 45 years, and because Cabrera’s numbers helped contribute to Detroit’s postseason push, that Cabrera had to be a lock to be the American League’s Most Valuable Player, right?
The Triple Crown, as rare and incredible of an accomplishment as it is, surprisingly was not enough to automatically crown Miguel Cabrera as the AL’s MVP. Another player, Mike Trout, a center fielder for the Los Angeles Angels, was having a season for the ages himself, and many were engrossed by his sensational performance. When his season was over, at age 21 (he was 20 prior to August 7th), he had accomplished something no one had ever done in the history of MLB. Mike Trout, according to baseball-reference.com, finished his 2012 campaign with an impressive batting average of .326, second only to Miguel Cabrera’s .330, he also led the league with 49 stolen bases, and scored 129 runs, two statistics that Cabrera could not even come close to.
Trout also played pristine defense, winning a Fielding Bible award for being one of the best defensive players in the game of baseball. On many nights, Trout drew “ooh’s” and “ahh’s” from fans as he made superhuman catches. The most documented was on a sunny Baltimore afternoon, June 27th 2012, when the Angels were playing the Baltimore Orioles. Orioles shortstop J.J. Hardy crushes an 82 mile-per-hour curveball thrown by Jered Weaver. The ball was certain to go over the center field wall, but Mike Trout took a leap of faith, jumping what looked to be three feet in the air, snatching the ball out of midair as it was leaving the ballpark, and bringing it back into play as he crashed into the wall. Many pundits called this play “the catch of the year”, and Trout mania had begun.
Miguel Cabrera, on the other hand, did not have the same defensive credentials. A third basemen during the 2012 season, he had spent much of the past four years as a first baseman, a position that is generally acknowledged as a position that requires less defensive skill than most positions, and he was considered a below-average defender at first base. During the 2012 season, questions surrounded whether or not Cabrera could play third, and he held his own, but he was anything but stellar, he was not even an average defender at third base, according to traditional and modern statistics.
Late in the 2012 season, leading all the way up to the release of the final polling in November, baseball writers, broadcasters, and fans alike began debating which of the two was the league’s Most Valuable Player. The arguments became heated and almost barbaric, with writers calling out other writers for believing a certain player was more valuable than the other. Those who saw Cabrera as the MVP pointed to his Triple Crown, the rarest of all offensive feats, and the fact that without him, the Detroit Tigers would not be heading to the playoffs in 2012. Those who favored Trout felt that Cabrera’s Triple Crown and Detroit’s playoff berth did not outweigh Trout’s overall performance. They argued that Trout excelled in every facet of the game, while Cabrera excelled only offensively.
Trout supporters also considered traditional baseball statistics barbaric compared to modern day statistics, which, in their minds, should have convinced the baseball world that Trout was far and away the better player in 2012. Many pointed to the sabermetric Wins Above Replacement (WAR), as a tell-all that Trout was more valuable. WAR is a statistic that, in theory, takes every statistic, offensively, and defensively, and combines those many numbers into one number which shows how many wins above a replacement level player in the minor leagues a specific player was worth. If a player has a WAR above 0, they are more valuable than the average replacement level player, and anything below implies that a specific player could be replaced by a minor leaguer and their team would be better off. Trout led all Major Leaguers in 2012 with a staggeringly high 10.9 WAR, meaning he was worth nearly 11 wins more to his team than the average player. Cabrera, on the other hand, finished a distant fourth with a 7.3 WAR, so pundits argued that Cabrera was far and away an inferior player to Trout, and Trout was more valuable.
On the final day of the season, the Baseball Writers Association of America voted for their AL MVP, and in November Cabrera received 22 of 28 possible first place votes to claim the MVP in a surprising landslide. The debates running rampant through the MLB sportswriting world all but pointed to a tight vote and a Trout victory, but somehow, through all the white noise writers and broadcasters alike were generating, Cabrera had the voters’ support all along. But if Cabrera was only better by traditional offensive statistics, and Trout was widely regarded as the better player, why was Cabrera regarded as more valuable?
This essay will try to make sense of the unthinkable. Baseball, and sports in general, are markets that are widely numbers-based, which is why those who follow them are so engrossed by statistics. However, is society putting too much stock into the wrong statistics? This writer believes so, and thinks that MLB, and its following, are seeing the game the wrong way. The hope is that those who read this will have a clearer understanding of what value truly is in baseball, and that someday, traditionalists and modernists alike, can agree that a set group of statistics that define a players’ value better than any other.
Statistics play an integral role in not only baseball, but sports, and those who watch them in general. Statistics provide something concrete that tells anyone who cares “this is the kind of player so-and-so is.” Sure, one can see that, say, shortstop Jose Reyes is one of the most explosive, dynamic, and exciting players in all of professional baseball, but he never would have received a $100 million contract without statistics that back up the aforementioned statement. Good statistics bring money, and theoretically, wins to a particular team, but casual fans, diehard fans, and experts alike all seem to have differing views on which statistics are most important in determining player value, especially in the game of baseball.
Statistics may play an important role in other sports, but in baseball, they hold a critical importance to understanding the game and the value a particular player or team holds. Consider the following: a quarterback who throws for over 5,000 passing yards in the NFL is likely widely considered a pristine player, but a first baseman in the Major Leagues who hits for a .300 batting average does not necessarily tell the whole story about the player. That first baseman could have an on-base percentage of .315, which means despite his impressive batting average, he struggles to get on base other than through base hits, which could mean he lacks plate discipline. There are plenty of reasons why a player could have a .315 on-base percentage and a .300 batting average, but the point is this: in baseball, one statistic rarely tells the entire story.
Different statistics in baseball can infer what different things a player is and is not capable of doing on the baseball field. Want to gauge how powerful a player’s swing is? Home runs, slugging percentage, and isolated slugging tell a pretty good story of a player’s power. Wonder how efficient a pitcher is? WHIP (Walks and hits per innings pitched) and FIP (Fielding Independent Pitching) can show how efficient a player is either in a game or throughout an entire season. These statistics are merely the starting point for determining a player’s value. It is known that MLB publishes 85 different individual player statistics, and these statistics do not include sabermetrics, of which accumulate to hundreds of possible ways to evaluate a player.
So how do fans, broadcasters, talent evaluators, and front office executives alike make sense of all the madness? With so many statistics out there, which ones matter, and which ones not so much? There are many statistics that say something about a player, but not many that say everything about a player, and there are a few statistics, in the opinions of many, that say absolutely nothing about a player. In the definition of nothing, it is meant because what that statistic says, does not actually contribute to what that player is worth. For example, the pickoff statistic for pitchers really does not say a whole lot about how good or bad a particular pitcher is. If a pitcher picks off more runners than any other pitcher in baseball, is he better than every other pitcher in baseball? At picking off runners, maybe, but that statistic says absolutely nothing about the value of the pitcher, because, sure, he can catch a baserunner off-guard and throw him out, but suppose he also gives up a lot of runs as well. Does his ability to pick off runners outweigh his weakness of allowing those he does not pick off to score? Absolutely not.
So if there are statistics that say something, and statistics that say nothing, are there any statistics out there that say everything about a player? There are sabermetrics, modern-day statistics, that try to do just, but unfortunately, few, say anything all too helpful that traditional statistics cannot. Jump back a few pages, and consider the WAR statistic again. As previously explained, is a statistic that tries to bring all of a baseball player’s numbers down to one number: how many wins above a replacement-level player a particular player is. In theory, this sounds like a great way to say exactly how a player might stack up against all the others in baseball, but there is a huge problem with WAR that makes it a statistic that is so inconsistent it is as unreliable as it is near impractical. The biggest problem with WAR, is that if one is researching a particular player, they will likely see a different number depending on where they are researching the player.
Let’s say, for the sake of argument, this player is Howie Kendrick, a second baseman for the Los Angeles Angels, in 2011. On FanGraphs, one will see that Howie Kendrick has a WAR of 5.8, which was the highest among Angels’ position players that year. 5.8 would also be widely considered a high WAR, particularly for a second baseman, a position that rarely produces elite value. A 5.8 WAR would make Kendrick one of the best second baseman in the game. If, however, instead of FanGraphs, one looked up Kendrick’s WAR on Baseball Prospectus, one would see his WAR is 2.7, an above-average player, but nothing elite, not like FanGraphs was implying. There is also another site, baseball-reference.com, that also calculates its own version of WAR.
Each version of WAR incorporates different statistics into its formula and calculates it differently than the other two, because of plenty of differing opinion on the importance of statistics. It is quite ironic, really, a statistic that is supposed to be an all-encompassing statistic, but is calculated differently by different people because they feel some statistics are more important than others. Can we, based on the above information, truly trust WAR to gauge the value of a player? Until pundits can agree on one formula and one version of WAR applicable and agreeable by the sabermetrics experts, it is difficult to say that any kind of WAR statistic is a reliable source to find value in a player. It is like comparing apples to oranges, you just will not find any kind of specific agreement between them.
Another statistic that baseball “experts”, writers, fans, and even MLB itself uses constantly but is a statistic that is horrible for gauging player value is OPS, or on-base-plus-slugging percentage. This statistic combines two statistics: on-base percentage and slugging percentage, to show how good a hitter is at combining two integral skills, getting on base and hitting with power. Again, in theory, this seems like a good statistic for seeing how players stack up against each other, but this statistic is fatally flawed. Keith Law of ESPN (2013) said it best:
“OPS, the fauxbermetric stat that results from a straight addition of the two, ignores the difference in value between the two — a point of extra OBP is worth a lot more to a team’s run-scoring potential than a point of slugging.
Consider two players with an .800 OPS: One has a .350 OBP and a .450 slugging, and one has a .400 OBP and a .400 slugging. The second player is clearly more valuable: He makes fewer outs than the first player, and the number of additional times he’s on base exceeds the number of extra bases added by the first player.” (Law, 2013)
So, in short, two players with the same OPS are not necessarily equal players. The straight addition of both on-base percentage and slugging percentage is creating a fallacy that both of these statistics are equal, but on-base percentage is far more important when it comes to creating runs. How can we be expected to rely on this statistic if what is supposed to be equal is not equal? It is apparent that OPS is a flawed statistic that cannot be used to truly evaluate a player.
Obviously, there is a recurring theme in sabermetrics: two numbers that are equal in one statistic are not necessarily equal in determining player value. Essentially, what I feel is that to truly determine player value, one has to consider statistics that are equal for all players. No gimmicks, no underlying statistics that have to be taken with a grain of salt, no alternative ways to calculate the statistic, just pure equality. Maybe, if we cannot find such equality in regularly used sabermetrics, we can find equality in traditional statistics?
Sadly, the answer to this question is no. Consider the traditional statistic batting average, which is the division of hits by the number of at-bats a player had in a set duration of time. For example, if a player had 200 hits in 600 at-bats, his batting average would be .333. For any player, this is an excellent batting average, but does batting average determine how good a particular player is? The inclination is to say yes, but batting average, like so many other statistics, do not tell the whole story. A player who hits .333 might be a good hitter, or he may be completely lucky. Consider two players who hit .333, but both players have different BABIPs (batting average on balls in play). Batting average on balls in play is the likelihood that a player will receive a hit on a ball he put in play. The higher a player’s BABIP, the luckier a player is said to be, because not every ball that is hit into play results in a hit. So, a player with a .333 average, but a .350 BABIP, is likely a better hitter than the player who hits .333 but has a .410 BABIP, because he does more with fewer opportunities, while the other hitter merely has to put the ball in play to get hits.
Additionally, those two same hitters likely do not have the same amount of at-bats in the same season. Putting at-bats, batting average, and BABIP together tells a different story entirely. If the first player, with a batting average/BABIP of .333/.350 also had 600 at-bats, you know that player was not all that lucky, but the player with the .333/.410 slash line with only 100 at-bats, you can infer that this player has been going through a hot streak, and is a likely beneficiary of luck. So even traditional statistics have major flaws that go along with them.
If sabermetrics are not the answer, and traditional statistics are not the answer, where can we find value? Where can we find equality? Where, in all the inconsistencies and ambiguities, is there a proper means of evaluating a baseball player? Well, there have been clues hidden throughout this entire essay to help reveal part of the answer: there is no one statistic. It requires the assistance of other statistics to help solidify any case of evaluation. There are various statistics, however, that when used correctly, effectively determine the value of a player, and this writer believes that these are the most important statistics in today’s day and age. They are flawed, just like every other statistic out there in some way, shape, or form, but they provide a clearer idea of how valuable a particular player at the basic level than any other.
Batting Average on Balls In Play
Over any period of time, BABIP is a very helpful statistic. To review, a player with a higher BABIP is likely luckier than a player with a lower BABIP. If a player has a good offensive season out of the blue, look at his BABIP, if it is a lot higher than his career norm and the league average, heed caution when picking him up in a fantasy draft, or hold off on optimism when your MLB team signs him. The flaw with this statistic is that players who are speedier than others may benefit from an extra infield single or two which would inflate their BABIP, but it still is a good indicator of the amount of luck that has contributed to a player’s offensive value.
Miguel Cabrera: .331 (Batting average .330), Mike Trout: .383 (Batting average .326)
On Base Percentage
On base percentage by itself is a fantastic way to gauge how productive a player is with his at-bats. Players with higher OBPs are a tougher out than those with lower, and generally are more productive than those with lower OBPs. Is there any ambiguity that a player that gets on base more often than someone else is more valuable? In the game of baseball, I would think that there is only clarity in that statement.
Miguel Cabrera: .393, Mike Trout: .399
Slugging Percentage
Slugging percentage by itself is a way to determine not how many hits a player has, but what a player does with those hits. The higher one’s slugging percentage, the more powerful and more productive the hit. If a General Manager or a fantasy baseball player is looking for a powerful hitter, a player who slugs well is a pretty sure bet. Slugging percentage is slightly flawed because it puts an equal importance on each base when totaling them, but it is an excellent starting point in determining the productivity of a player’s base hits.
Miguel Cabrera: .606, Mike Trout: .564
Those three offensive statistics, for me, are the big three that do a very good job of determining how good a hitter truly is. I threw in the numbers that Cabrera and Trout had during the 2012 season for each of those statistics, and, no contest, Miguel Cabrera was the more valuable offensive player. These statistics show that Mike Trout, offensively, although he may have stolen more bases and scored more runs, was also luckier than Cabrera in terms of getting hits, got on base just a little bit more, and slugged a whole lot less. Cabrera, on the other hand, fought for his base hits due to his low BABIP, but maintained a high batting average. He also slugged a whole lot better, and got on base at a similar clip as Trout. There is no question the more valuable player offensively was Cabrera, based on these near all-encompassing statistics, without even including the facts that Cabrera had won the Triple Crown and slugged his team into the postseason, while Trout’s Angels did not make the playoffs in 2012.
Strikeouts/Walk Percentage
The hitter has three statistics that can display a hitter’s true value, but what about pitchers? Pitchers also have three statistics that represent a pitcher’s value well. The first is strikeouts and walk percentage. There are a lot of things that happen in baseball that a pitcher cannot control. Home runs, errors, terrible defense, different size ballparks, the list goes on, but a pitcher is not a Major League pitcher based on luck alone, because it is rarely the luckiest who pitch the best in professional baseball, but usually the most talented. There are two indisputable things a pitcher is capable of controlling: how many batters a pitcher strikes out, and how many walks a pitcher allows. If a pitcher does not walk many but strikes out plenty, he is a better bet to be a consistently good pitcher than his counterpart who does the opposite. If this is the case, why not use strikeouts and walks per nine innings as opposed to a percentage? Keith Law (2013), in the same piece above about baseball statistics, opines “It’s more instructive to use strikeout and walk percentage — as opposed to strikeouts and walks per nine innings — because some pitchers face more batters per inning than other pitchers, which means they get more chances to strike out or walk them” (Law, 2013). Makes sense.
Fielding Independent Pitching
To best explain what FIP is, I investigated the definitions that each FanGraphs, Baseball Prospectus, and Baseball-Reference had, and they, to the likely surprise and dismay of my readers, have the same formula and definition. FanGraphs (2013) describes it best as such:
Fielding Independent Pitching (FIP) measures what a player’s ERA [earned run average, number of earned runs allowed divided by innings pitched] should have looked like over a given time period, assuming that performance on balls in play and timing were league average. Back in the early 2000s, research by Voros McCracken revealed that the amount of balls that fall in for hits against pitchers do not correlate well across seasons. In other words, pitchers have little control over balls in play. McCracken outlined a better way to assess a pitcher’s talent level by looking at results a pitcher can control: strikeouts, walks, hit by pitches, and homeruns.
A walk is not as harmful as a homerun and a strikeout has less impact than both. FIP accounts for these kinds of differences, presenting the results on the same scale as ERA. It has been shown to be more effective than ERA in terms of predicting future performance and has become a mainstay in sabermetric analysis (FanGraphs, 2013).
If a pitcher has a high ERA, take a look at his FIP, if it is lower than his ERA, he likely was a victim of some bad luck, or some factors that he could not control. Baseball’s best pitchers have some of the games’ best FIP numbers, but pitchers with high ERAs but lower FIPs can be pointed to as guys destined to bounce back.
BABIP
BABIP is as useful a tool for pitchers as it is for hitters. If one applies what they know from BABIP and reverses the application of it, then it can be used to determine how lucky or unlucky a pitcher is. A pitcher with a low BABIP is likely more lucky than someone with a high BABIP, and anyone with an extreme either way should require some skepticism before declaring that particular pitcher “good” or “bad”.
So, to conclude, numbers and statistics are an important part of baseball. The right statistics allow the right evaluation of a player. Oftentimes, we tend to overlook the numbers that truly matter, and tend to go with the norms, what people generally regard as accepted. It is time we start looking at the numbers that truly matter, regardless of the status quo. It is time to start asking the right questions, as opposed to wondering silently why something is the way it is. Baseball will someday likely have a set of statistics that everyone involved or relatively interested in the sport will agree upon, but for now, the debate runs rampant. As baseball changes, there will always be a new mean of evaluation, but it is this writer’s hope, through all of the controversy and disagreement, we will find some way to make sense of things, and come to together in agreement. Until that day comes, well, I am anxiously awaiting the first rebuttal to my argument.
“A lot of players told me I’m going to be the MVP, I said, ‘I bet you’re saying the same thing to Trout.’ I always tell them to give credit to Trout. He’s the first rookie to do what he did. He’s great for baseball.” -Miguel Cabrera on his MVP Award, and rookie phenom Mike Trout.
Work’s Cited
2012 Major League Baseball Batting Leaders (2012, October). In baseball-reference.com. Retrieved April 4, 2013, from HYPERLINK “http://www.baseball-reference.com/leagues/MLB/2012-batting-leaders.shtml” http://www.baseball-reference.com/leagues/MLB/2012-batting-leaders.shtml
(2012). Must C: Catch [Online video]. MLB.com. Retrieved April 4, 2013, from HYPERLINK “http://mlb.mlb.com/video/play.jsp?content_id=22644539&c_id=mlb&topic_id=vtp_must_c” http://mlb.mlb.com/video/play.jsp?content_id=22644539&c_id=mlb&topic_id=vtp_must_c
DuPaul, G. (2012, June 16). Be Wary of WAR: A Cautionary Tale. In Yahoo Sports. Retrieved April 20, 2013, from HYPERLINK “http://www.beyondtheboxscore.com/2012/6/16/3085251/be-wary-of-war-a-cautionary-tale” http://www.beyondtheboxscore.com/2012/6/16/3085251/be-wary-of-war-a-cautionary-tale
FIP (2013). In FanGraphs.com. Retrieved April 25, 2013, from HYPERLINK “http://www.fangraphs.com/library/pitching/fip/” http://www.fangraphs.com/library/pitching/fip/
Law, K. (2013, February 19). The Stats I Can’t Live Without. In ESPN.com. Retrieved April 10, 2013, from http://insider.espn.go.com/mlb/blog/_/name/law_keith/id/8961789/obp-babip-most-important-baseball-statistics-needed-player-evaluation-mlb
Statistics courtesy of baseball-reference.com
Taken from the highlight video, “Trout’s Remarkable Grab”, June 28th, 2012 LAA vs. BAL
WAR is baseball-reference’s version of WAR, used by ESPN.com
Courtesy of the BWAA’s website
Divided by hitting, pitching, and fielding
Some information is used from a Yahoo Sports Article: “Be Wary of WAR: A Cautionary Tale”
All Miguel Cabrera/Mike Trout statistics are taken from FanGraphs
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Thomas Vacanti DATE \@ “MMM d, ”yy, h:mm AM/PM” Aug 15, ’13, 8:51 PM