Quantifying the Rays’ Hustle

The Rays are defined by how hard they run down to first every groundball. When a Rays player who isn’t coming off of an injury doesn’t bust it down the line, ti’s surprising. How does the Rays’ hustle manifest itself in the stats?

In a similar vein to what we talked about on Monday, we see the Rays’ hustle manifest itself in their aggressiveness on the basepaths both in terms of stealing bases and taking extra-bases. But hustle is just as relevant on groundballs and bunts.

When you put the ball in play, there’s always a certain amount of luck involved. Hustle can take some of that luck out of the picture. On groundballs, we see that they are hits sometimes by pure luck. Sometimes the hitter just places it in the perfect spot, and it goes through to the outfield for a base hit. Other times though, it’s a matter of hustle. If it’s a groundball deep into the shortstop hole, maybe a player who hustles makes it to first and maybe one who doesn’t is out. The baseball-wide BAbip (batting average on balls in play) was .237 in 2011. Looking at the Rays’ BAbip on groundballs, it was actually lower, coming in at .226! But what about percentage of groundballs that go for infield hits? The MLB average was 8.3% of groundballs ended up as infield single. The Rays were at just 7.9%. OK, but how about percentage of hits that went for infield singles? MLB: 11.6%, Rays: 11.0%. Percentage of infield hits among plate appearances? MLB: 2.6%, Rays: 2.4%. Percentage of infield hits among at-bats: MLB 3.0%, Rays 2.9%. Clearly we’re getting the exact opposite result of what we thought. Is the Rays’ hustle just a myth? Or is there some other variable that we have to worry about?

One of assumptions we naturally make that make the results above seem more extreme is that all groundballs are created equal. We know that they’re not. There are weak groundballs, routine groundballs, and bullet groundballs. Each team hits a certain amount of each variety of groundballs. Is it possible that the Rays’ groundballs are weaker than those of other teams? It’s definitely worth noting that 42.9% of the Rays’ batted balls in 2011 were grounders compared to the league average of 43.9%. As it turned out, the Rays ranked 7th in baseball in terms of lowest GB/FB (groundballs to flyballs ratio- line drives are counted as flyballs) at .78. The Rays were  a flyball-hitting team in 2011, and that led to quite a few extra-base hits as 36% of their hits went for extra-bases, the fifth-highest ratio in baseball (although 3 of the 4 teams ahead of them are in their division). But since the Rays were trying to lift the ball for extra-base hits so often, when they hit groundballs it often was unintentional, and maybe their groundballs were more softly hit than the average team. So now let’s try to neutralize for that. First, let’s compute percentage of infield hits among groundball singles, which takes out a lot of the harder variety of groundballs. Now we’re finally getting somewhere: the Rays come in at 38.8% by this statistic compared to the league average of 38.1%. Let’s compare the Rays to the other teams close to them in groundbball to flyball ratio. We’ll do this in a nice little table.

This table is every team in baseball with a GB/FB below the league average. Comparing the Rays’ ratios (bolded) to the averages of the table at the bottom, the Rays were well below the average of these teams in terms of BAbip but were close to average for most of these stats well above the average for percentage of infield hits among groundball sin

gles and percentage of extra-base hits among total hits. The Rays’ fault was that they, as a whole, were swinging to elevate the ball, and when they hit the ball on the ground it was so often routine groundballs. We know the Rays are a speedy team- they led the American League in stolen bases in 2011- yet just 11% of their hits were infield hits, actually a bit below the average of this table. That was because pretty much their entire team was composed of flyball hitters. One player who skewed their numbers was Casey Kotchman, who hit a ton of groundballs without very many infield hits. The only teams that are real comparisons based on extra-base hit rate are the Blue Jays and Red Sox. We see that the Rays blow away the Red Sox and they’re only slightly below the Blue Jays because the Blue Jays featured players Yunel Escobar and Rajai Davis for quite a few plate appearances (the Rays’ equivalents of those types of players, Desmond Jennings and B.J. Upton, hit the ball in the air and hit for power). Because of their approaches at the plate, the Rays don’t get all that many opportunities to beat out groundballs for infield singles. But when they do, they hustle and take advantage.

The other factor is bunting. The Rays actually had just 22 bunts hits on the season, tied for 10th in baseball. But they were by far the most efficient bunting team and arguably the best. The Rays SOPS+ on bunts was 139, meaning that for bunts, the Rays’ team OPS was 39% better than the league average. Their BAbip on bunts was .468, well above the league BAbip of .392, but that BAbip disregards sac bunts. We know that whenever the Rays lay down a bunt, they’re planning to beat it out, so let’s add sac bunts into the BAbip equation as outs. 18.9% of all bunts in the major leagues in 2011 ended up as singles, or in other words, a .189 BAbip. The Rays BAbip on bunts including sacrifices was .262, nearly 100 points higher. Bunting is the only time where the Rays really intend to hit the ball on the ground, and when they do lay down bunts, they consistently beat them out.

How many times watching baseball do we see hitters, even ones possessing great speed, running lackadaisically to first on groundballs? The Rays are a team that features very fast players, and they take advantage of that whenever they get the opportunity. They may be more of a power-hitting team than people realize, but they make full use of their speed. The Rays will continue to hustle, and who knows how many games that will win them this coming season.

Topics: B.J. Upton, Casey Kotchman, Desmond Jennings, Statistical Analysis

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