Last Thursday, Miguel Cabrera ran away with the AL MVP Award, winning 22 of the 28 first-place votes. After all, he did win the Triple Crown. However, some computer-loving, mother’s basement-dwelling, female-avoiding stat geeks had the audacity to use both math and logic to suggest that Mike Trout was the better choice for MVP. What has this world come to?
Unfortunately, that previous paragraph is how the MVP race was characterized by many media outlets. There has been a massive backlash against sabermetrics, especially among supporters of Cabrera. These advanced statistics have been called “made up” and “useless” by some, whether because of ignorance, opposition to change, or because people just don’t want to believe what the stats say. And really, this has all been a major step back in baseball analysis.
To preface the rest of this article, both Miguel Cabrera and Mike Trout had fantastic seasons. Truly great ones. And MVP races are always a bone of contention because there is a great divide in the baseball community between old guard, steadfast writers and progressive, analytical thinkers. Additionally, there is no set definition for Most Valuable Player.
While not all baseball fans know as much about sabermetrics as, say, ESPN’s snarky Keith Law, many fans have, at the very least, a shallow understanding of advanced baseball statistics. One of the more important stats that has gone mainstream is WAR, an all-encompassing stat that uses offense, defense, and baserunning to measure how many wins a player adds to his team above a replacement level player. Mike Trout had far and away the highest WAR this year at 10.0–the first time a player broke double digits since Barry Bonds had 10.6 in 2004. Miguel Cabrera, on the other hand, had just 7.1 WAR.
But this argument over which player is the MVP is more than just about who has the higher WAR. It’s more of a discussion about how to measure value in baseball.
The common mantra for Cabrera voters has been that since Miggy won the Triple Crown, he is the MVP. Nobody’s won the award since Mike Yastrzemski in 1967, and therefore, Cabrera deserves the award. But things aren’t so cut and dry. Plus the Triple Crown isn’t the greatest indicator of player value.
As I explained last year, when discussing the MVP awards, two of the three categories in the Triple Crown are outdated and not very useful. RBIs are completely completely context dependent–the stat has more to do with how good the team is compared to how good the player is. As for batting average, well, that’s only showing part of the picture. Walks are vitally important to baseball, since the batter reaches base without making an out. On-base percentage is a far better measure of what batting average is trying to explain: how often the player reaches base.
And finally, the Triple Crown does not show the full value of a player, let alone a hitter. It mainly shows how good of a power hitter is, completely ignoring speed, the ability to get on base, and defense. That’s more than half of the game. If we’re looking for the player with the most value, that player needs to be complete beyond just power hitting. Or so utterly dominant offensively that the player’s bat makes up for any other deficiencies.
But that wasn’t the case for Cabrera.
Even without using sabermetrics, the case for Mike Trout is simple. Miguel Cabrera had an edge in the power department, but Mike Trout reached base at a higher clip. Trout is a far better defender at a far tougher position, whereas Cabrera is a well below average defender. Trout led the league in steals while running efficiently and wreaking even more havoc on the basepaths, but Cabrera is a flat-footed runner to be kind. The slight edge Cabrera has in hitting is more than cancelled out by Trout’s massive advantages in defense and speed.
Trout played in a pitcher-friendly ballpark, while Cabrera played half his games in a hitter-friendly ballpark. Trout also played in a harder division–the AL West had a .542 winning percentage versus the AL Central, which had a combined .468 winning percentage.
Using basic baseball knowledge and logic, the choice between Trout and Cabrera is easy. Using advanced statistics, the task becomes even easier. Use any number of metrics (WAR, UZR, BsR, OBP…) there are quantifiable ways to show that a Trout was the superior overall player this year. With all the objective data on Trout’s side, supporters of Cabrera have had to come up with a series of fallacious reasons to back Cabrera.
1) Cabrera was better down the stretch.
As simple as this sounds, a win is still a win in October or April. While a win on the last day of the season may seem more important, it still counts as much as an Opening Day win. People make the argument that Cabrera out-hit Trout in September and October, hitting .333/.395/.675 instead of Trout’s measly .287/.383/.500, conveniently ignoring that Trout actually out-hit Cabrera over the last two weeks (.341/.473/.705 vs .292/.333/.521). Also never mind that Trout out hit Cabrera in May (.324/.385/.556 vs .331/.371/.468), June (.372/.419/.531 vs .311/.387/.604), and July (.392/.455/.804 vs .344/.409/.677)–all months in which teams play baseball. Cherry picking a small sample size doesn’t carry nearly the same weight as a full season of data.
2) Cabrera’s team made the playoffs, and Trout’s team didn’t.
This argument just makes no sense as soon as you take one look at the standings. The Angels won 89 games. The Tigers won 88 games. Trout just happened to be in a division with two 93-win teams, while the second best team the AL Central had 85 wins. Trout’s team had a better record against harder competition. Additionally, the Angels are 81-56 since they called up Trout, the best record over that time period. Then again, a player’s team doesn’t impact their value. A single for the Yankees and a single for the Astros still gets the batter to first base. Whether a team wins 89 games, makes the playoffs, or loses 107 games doesn’t impact the value created by a player.
3) These sabermetrics are made up by geeks who have never played baseball.
This seems to be the real argument. For those who are stuck on the Triple Crown equating to the highest value, this is the easiest way to knock Trout’s value. Years ago, we didn’t have these advanced stats, so people had to analyze baseball with the readily available, easy to track stats like home runs, errors, and earned run average. Now, teams and analysts have poured time and resources into finding better, more efficient ways of looking at the same aspects of the game (wOBA, UZR, and FIP). Yet because many of the statistics have complicated formulas, have confusing names, or are just unfamiliar, some people refuse to acknowledge the measures’ values.
The central problem is that using data to support an argument is somehow seen as a bad thing. The biggest example of this outside of sports is the fantastic case of Nate Silver. Silver started as a sabermetrician, when he created a player performance forecasting system called PECOTA. He used player stats, age, size, and various other attributes to predict next season’s statistics using comparisons of similar players. Silver sold PECOTA to Baseball Prospectus in 2003 and wrote for the company until 2008, when he became a political analyst.
Silver created a projection system for the 2008 election, using poll data, especially looking at demographics. Silver looked at past results and biases of polls, which helped him to predict 49 of the 50 states and every Senate seat correctly. Yet come 2012, Silver received flak from all sorts of political analysts (and people who disagreed with his system) because his system gave President Obama such a great probability of winning. Come election day, Silver’s system gave Obama a 90.9% chance of winning, whereas most other analysts thought it was a toss-up at best. As it turns out, Obama ran away with the election, and Silver’s system correctly predicted all 50 states.
Just like in a high school, there is a stigma against being too smart in the media. General Managers of baseball teams have adjusted by using new, innovative ways to evaluate and valuate players, or else their respective teams fall behind the curve and they get fired. Baseball writers, though, haven’t yet faced the chopping block if they don’t adjust to newer ways of analyzing players, so they’ve lashed out against these progressive stats and this progressive thinking.
Strange, how when new medicine is released to the public, people accept the innovation and move on with their lives. They don’t complain and ask for leeches and voodoo, even though that was used in the past. Yet when new statistics come out to better look at players, fans cry out it horror.
For now people seem to be stuck in the past of baseball analysis, evidenced by Cabrera’s runaway victory in the AL MVP race. But whether or not the hard-nosed old guard like Mitch Albom like it, it’s the smarter thinkers like Nate Silver who are the future of baseball analysis. Lest we use math, computers, or this new fad called “the Internet” to form an argument.