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Fun with Rays' two-month Statcast leaders

Stats on stats on stats

MLB: Tampa Bay Rays at Toronto Blue Jays Nick Turchiaro-USA TODAY Sports

It can be tough to keep up with all the new (and improved) baseball metrics available today. It seems it was just a minute ago that BABIP and FIP were at the cutting edge of baseball statistics, but now those metrics seem dated compared to some of what else is out there.

The cutting edge of what is being consumed publicly right now (there are plenty of front offices and fans who undoubtedly have their own even more advanced metrics privately) seems to be the Statcast gang of metrics. For the uninitiated, here’s a nice, full rundown from but at this point, most educated baseball fans (a sector to which many Rays’ fans belong) know the basics when it comes to Statcast. Terms like exit velocity, spin rate, and catch probability are no longer foreign to most baseball fans, as the sport has done a nice job bleeding this potentially niche core of metrics into the baseball mainstream.

With the end of May fast approaching, it’s worth taking a look at some of these new metrics with our Rays-colored glasses on. We’ll start with hitters, move to pitchers, and finish up with some brief fielding stats.

(Brief note before we start, and Baseball Savant have slightly different data, so if there’s a significant difference, the source will be noted. Baseball Savant will be the default setting, since they’re OG. All data through Sunday’s games.)

Brad Miller, the Velo Guy

Miller hasn’t had quite the season some had expected from him, as he has just two long balls through 39 games just one year removed from a season in which he hit a career-high 30 home runs. Maybe that was to be expected, however, as his previous season-high had been 11 before his monster 2016 season. And as his 2017 exit velocity shows, it’s not as if he’s failing to hit the ball hard.

Miller is the Rays’ leader in both average exit velocity (90.0 mph) and max exit velocity (118.4) in 2017 (per Baseball Savant). It’s worth mentioning that the max exit velocity event that is referenced above is a bit wonky. It was pounded into the ground (-77.9 degree launch angle) and traveled just three feet in the air, the shortest distance of any of the 50 hardest hits balls in baseball this entire season. It was also the hardest hit ball to be turned into an out (the fifth-hardest hit ball overall), so there are caveats aplenty. But hey, it’s still the hardest hit ball from a Ray this season, so…

(Steven Souza’s double on April 6 [116.2 mph] is the hardest hit ball by a Ray in 2017 that resulted in a hit - a double for Mr. Space Jam.)

Miller clearly isn’t relying on just his one hard-hit grounder, however. His average exit velocity on the season is also the highest on the Rays, coming in at 90.0 mph. (Souza is the top average exit velocity Ray by’s rankings.) That velo has led to only eight extra-base hits in 2017 for Miller, but he is a prime candidate to see increases to both his HR/FB rate (7.1 percent) and BABIP (.291) in the months to come if he continues to hit the ball this hard.

Logan Morrison, Really Good

Morrison has been absolutely tearing the cover off the ball for the entirety of 2017 (and most of 2016, in fact), so you probably don’t need any Statcast numbers to convince you of just how locked in he is, but here are a few anyway: Morrison is leading the team in average home run distance (410 feet), barrels (17), and xwOBA (.388).

I truly hope you can figure out that first metric, but let’s dig into the second two a little bit, (and here is JT Morgan’s look at this statistic in 2016). Barrels are a rather new stat that were created by the infamous Tom Tango. Here’s a brief quip from describing the stat:

To be Barreled, a batted ball requires an exit velocity of at least 98 mph. At that speed, balls struck with a launch angle between 26-30 degrees always garner Barreled classification. For every mph over 98, the range of launch angles expands.

Basically the stat is attempting to find balls that were put in play with the highest expected outcome for the batter. The range is defined using data from seasons past to set a range of velocity and angle in which batted balls had a batting average of at least .500 and a slugging percentage of at least 1.500. When a batter gets a barrel, it’s almost always good news for the hitter and bad news for the batter. Given Morrison’s 14 homers and wRC+ of 141, it’s not surprising that he’s leading the Rays in a metric that measures “bad news for opposing pitchers.”

Finally, xwOBA is a metric trying to figure out the expected future outcome for hitters. It’s another stat that attempts to strip luck out of the equation using all the data we have these days. Once upon a time, BABIP was the best we had in terms of stripping out luck, but these days we have xwOBA. It’s a great sign for Morrison keeping up his future production that he is not only leading the Rays, but he has a higher xwOBA than some big names like Robinson Cano, Francisco Lindor, Eric Thames, and Manny Machado, just to name a few. In fact, among players with as many plate appearances, Morrison ranks ninth in all of baseball in xwOBA.

Colby Rasmus, Back with a Vengeance

Rasmus may have started his 2017 season late (season debut: May 2), but he has hit the ground running, leading the Rays in percent of balls hit 95+ mph (43.9 percent) and barrels per batted ball event (17.1 percent). Neither of those metrics are cumulative, which makes sense since Rasmus missed all of April, but in May he’s been among the Rays’ best hitters.

Rasmus is another one of several go-big-or-go-home types in the Rays’ lineup right now, which plays into his high percent of hard hit balls. Rasmus doesn’t get cheated when he’s up at the dish, and the fact that exactly half his 70 at bats this season have ended in either a home run or a strikeout feed right into that narrative.

Jose Alvarado, Faster Than You Think (And Maybe Better Than You Think, Too)

Alvarado has made quite a Statcast impact in his 10.1 innings at the major league level so far. Alvarado has been decent by surface metrics (3.48 ERA, four holds), but his velocity and expected results are even more interesting.

Among pitchers with at least 100 pitches, only three pitchers have a higher average pitch velocity, and one of those pitchers is Aroldis Chapman, a man with a fastball so fast, they literally invented a filter on the highest pitch speed leaderboard to filter out his results. Amazingly, Chapman actually trails Trevor Rosenthal and our very own Ryne Stanek in terms of average pitch velocity this season. The reason Alvarado is the man of the hour here and not Stanek, is that Alvarado has some interesting results with that speed.

Maybe that should be re-framed to say he has the potential for some interesting results. Despite the rather pedestrian ERA, Alvarado has a 0.58 WHIP and .111 batting average allowed, both of which are backed by a wxOBA (that fancy metric from before) of just .227. That figure is the best among all Rays’ pitchers in 2017, and it ranks 22nd among pitchers with as many balls in play as Alvarado this season. Alvarado has been solid in his jump directly from Double-A to the majors, and, if Statcast has anything to say about it, he may have some even better results in the not-too-distant future.

Tommy Hunter, Spin Doctor

Another Rays’ reliever is at the forefront of the spin revolution, as there have only been 16 pitchers with a better spin rate on their respective pitches than Tommy Hunter in 2017, and that number shrinks to 12 if they need to have thrown as many pitches as Hunter.

Hunter just returned from the DL less than a week ago, having missed just over a month from April 22 to May 25. With that large chunk of time missing, he has thrown only 11.2 innings this season, but he has been extremely effective in that time, with a 2.31 ERA and 3.13 xFIP.

The high spin rate that Hunter has (2,557 rotations per minute) helps his fastball have a little extra rise (at least in the eyes of the batters), while helping his cutter and curveball have that prototypical “bite” that scouts have been talking about for decades. This is not a fluke for Hunter either, as he ranked 38th in spin rate in 2016 and top 50 in perceived velocity.

Steven Souza Jr., Five-Star General

One of the big Statcast roll-outs for 2017 was their new Catch Probability tool that rates each defensive play made in the outfield on a scale from one star to five stars based on historical Statcast data. The data mostly deals with how far the fielder had to go to field the ball and how fast he had to go to get to it, and it is more of a loose tool than perfect metric for the time being, but that doesn’t mean we can’t have a little fun with it.

So far in 2017, Rays’ outfielders have had a combined 30 opportunities for five-star plays, and they have converted five of them. That 16.7 percent success rate is right in line with the overall range set for those five-star plays. Historically, 0-25% of five-star opportunities have been turned into outs. Four-star opportunities are turned into outs 26-50% of the time; three-star plays 51-75% of the time; two-star plays 76-90%; and one-star plays 91-95%.

Here’s how the Rays outfield has done this season:

Rays Catch Probability (2017)

Name 5-Star 4-Star 3-Star 2-Star 1-Star
Name 5-Star 4-Star 3-Star 2-Star 1-Star
Steven Souza Jr. 2-5 (40%) 3-4 (75%) 3-5 (60%) 11-11 (100%) 7-8 (88%)
Corey Dickerson 1-2 (50%) 2-4 (50%) 0-1 (0%) 3-4 (75%) 8-10 (80%)
Kevin Kiermaier 1-6 (17%) 5-7 (71%) 5-5 (100%) 5-6 (83%) 13-13 (100%)
Shane Peterson 1-4 (25%) 1-2 (50%) 0-0 (0%) 0-1 (0%) 2-3 (67%)
Peter Bourjos 0-5 (0%) 0-0 (0%) 1-2 (50%) 1-1 (100%) 6-6 (100%)
Daniel Robertson 0-1 (0%) 0-0 (0%) 0-0 (0%) 0-0 (0%) 0-0 (0%)
Colby Rasmus 0-6 (0%) 0-2 (0%) 2-2 (100%) 4-5 (80%) 6-7 (86%)
Mallex Smith 0-1 (0%) 0-0 (0%) 1-2 (50%) 2-2 (100%) 1-1 (100%)

Souza is the lone Ray with multiple five-star plays, and he has done so in fewer chances than Kiermaier and Rasmus. (You can watch both plays here.)

A few things stand out with the chart above.

  • Kiermaier is definitely still doing the damn thing in centerfield even if he has had a few head-scratching (and Space-Jam-theory-inducing) plays along the way.
  • Peter Bourjos definitely isn’t looking like an MLB player based on these limited opportunities. In his prime, his ability to make tough plays in the outfield was his calling card.
  • The Rays outfield defense is really darn good.

That’s it for our Statcast check in today. We’ll be checking back periodically to dive into the Rays performances based on this great new tools.