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Which Twins does Statcast love and hate?

MLB Statcast’s new stats will shine a brighter light on players’ individual contributions (or lack thereof).

MLB: Spring Training-Toronto Blue Jays at Minnesota Twins
Sorry, Phil. MLB Statcast data wasn’t kind to you in 2016 — and there’s more on the way.
Kim Klement-USA TODAY Sports

Since its release in 2015, MLB Advanced Media’s Statcast has gone from being an occasional nifty doodad that popped up during the 2015 playoffs — mostly to tell us just how dang fast Jarrod Dyson and Terrence Gore were, if memory serves — to a powerful tool in divining the individual contributions of certain players in a game that’s riddled with context.

Saturday at MIT’s Sloan Sports Analytics Conference, MLB Advanced Media architects and ambassadors Mike Petriello, Darren Willman and Tom Tango unveiled two new Statcast metrics that will be released by Opening Day 2017: Hit Probability and Catch Probability.

These two stats represent, as you probably surmised, the odds that a given batted ball will be a hit or caught, respectively.

Petriello explains Hit Probability thusly:

While there's a lot of complicated math that goes into it, it attempts to answer a very simple question: Based on the exit velocity and launch angle of the batted ball, how likely was the ball to land for a hit? That's trying to get to the heart of what a pitcher and hitter control while attempting to take out the effects of defense and ballpark.

It can be expressed as a percentage, which adds instant context without even needing to know all the underlying data that goes into it.

Exit velocity and launch angle are two stats that have already creeped into common baseball-nerd parlance, and Hit Probability is therefore relatively straightforward.

And here’s Petriello’s explanation of Catch Probability:

It's a simple number that can be applied to every tracked batted ball to the outfield, and it's on a scale of 0-100 percent, where a zero percent Catch Probability is "that ball is never, ever caught" and a 100 percent Catch Probability is "caught by everyone, always."

That's important, because we know that not every fly ball is created equally. An out may be an out in the scorebook, but there's a very different amount of skill required to catch the lazy fly ball that has a 95 percent Catch Probability as opposed to the sinking liner that has a 10 percent Catch Probability. Regardless of how it "looks," we should attempt to credit that difference in difficulty accordingly.

For some added context, the Statcast team has also determined how many “stars” a defensive play is worth based on its difficulty.

Based on the ability to quantify each play, we've crunched the numbers and come up with identifiers based on the Catch Probability.

0 to 25 percent --- 5 Star play *****

26 to 50 percent -- 4 Star play ****

51 to 75 percent -- 3 Star play ***

76 to 90 percent -- 2 Star play **

91 to 95 percent -- 1 Star play *

Beyond that, you don't merit a star, and the bands get smaller as they get easier because the frequency increases so much.

Because Hit and Catch Probability haven’t been released yet, we’re not privy to the full data, but Petriello does give Twins fans a little tasty morsel about the team’s defense in 2016.

In terms of team outfields, the Reds and Twins tied for most Five Star plays made with 18; this is just a taste, of course.

Damn. That didn’t sate me, but it sure did whet my whistle.

MLB: Spring Training-Toronto Blue Jays at Minnesota Twins
Praise Jesus! Byron Buxton can catch the hell out of some baseballs.
Kim Klement-USA TODAY Sports

Statcast superstar

Perhaps unsurprisingly, Twins phenom Byron Buxton was responsible for much of the Twins’ stellar Statcast ‘D.’

Petriello named Twins centerfielder Byron Buxton one of his “Statcast All-Stars” last season for his ludicrous speed, both on the bases and in the outfield. Among right-handed hitters, Buxton recorded the four fastest home-to-third times and six of the top 10; he also tallied the nine fastest home-to-second times on doubles among righties. And, as the icing on the cake, his 14.05 seconds around the bases clocked during his inside-park-homer off Chris Sale — on the first pitch of the game, to boot — was the fastest recorded home-to-home time in the Statcast era.

And in the outfield, he does this kind of stuff.

This is where Statcast shines: demonstrating just how difficult a seemingly simple catch truly was. Sure, Buxton makes his fair share of jaw-dropping diving catches, which Statcast’s Catch Probability will also capture and quantify.

But I love Statcast’s ability to show the difficulty of plays that aren’t punctuated with a dramatic leap or dive but more subtly demonstrate just how doggone far — and with efficiency and quickness — an outfielder traveled to track down a would-be hit. Statcast allows us to appreciate the finer points of fielding, and Buxton is damn fine at fielding.

Minnesota Twins v Miami Marlins
Phil Hughes was hurt in 2016, which may have accounted for the violent contact inflicted upon his pitches.
Photo by Rob Foldy/Getty Images

Turns out Statcast wasn’t kind to Twins pitchers

Buxton was a Statcast stalwart for the Twins, and Miguel Sano found himself near the top of numerous exit-velocity leaderboards.

The Twins also boasted several pitchers near the top of the Statcast leaderboards, though unfortunately these leaderboards were sorted in descending order. Twins pitchers got lit up in 2016.

Wherever you look on Baseball Savant — the site created by Willman that hosts the Statcast data — Twins pitchers show up in the worst way. Tyler Duffey and Hector Santiago gave up the second- and third-longest home runs of 2016; Pat Dean surrendered some of the hardest-hit balls in baseball; hitters “barreled” more of Duffey and Santiago’s pitches than nearly any other pitcher in MLB.

But the Twins pitcher featured at the top of numerous Statcast leaderboards is none other than Phil Hughes, the former staff ace who is currently recovering from thoracic outlet syndrome, which required rib-removal surgery last July.

Hughes gave up the hardest-hit ball in the 2016 season, according to Statcast. Fortunately for Hughes and the Twins, the 123.9 mph batted ball he surrendered to Giancarlo Stanton was hit at a -4.83 launch angle (i.e. into the ground) and actually was converted into two outs.

Unfortunately for Hughes and the Twins, the former Yankee also ceded the highest average exit velocity on batted balls last season; the fifth-highest average exit velocity on line drives and fly balls; and the fifth-highest Barrels/PA rate in MLB. (“Barrels” are well-struck balls with an estimated BA/SLG above .500/1.000.)

Hughes wasn’t healthy in 2016 and only threw 59 innings. It’s very rude for me to pick on him.

But his Statcast data illustrate just how useful the forthcoming statistics will be for evaluating players going forward.

Let’s look at a specific example.

On May 17, 2016, Hughes made his eighth start of the year and one of just 11 he managed before the injury sidelined him. Here’s his pitching line, courtesy of Baseball Reference.

Screenshot via Baseball Reference

Hughes pitched well! He certainly gave the Twins a chance to win, and Tonkin and May did their best to squander said chance.

But a closer look at Statcast data betrays just how close to the sun Hughes was flying.

Hughes gave up five batted balls with an expected batting average above .700 and three of them became harmless outs. That’s called beating the odds.

Screenshot via Baseball Savant

Two of those batted balls — Miguel Cabrera’s lineout to left in the first inning and Justin Upton’s lineout to center in the fifth — were hit in excess of 110 miles per hour. Upton’s 110.8 laser beam and Cabrera’s 110.4 mph shot represented the fourth- and fifth-hardest hit balls against Hughes all season, and neither caused him a mite of damage.

But people noticed. People like Justin Upton.

Upton scanned the infield in hope that someone would please explain how the frozen rope he just smacked to deep center was caught — and by Danny Santana, no less! Perhaps those adorable Fans of the Game have an explanation.

By my back-of-the-envelope calculations, Upton’s screamer had a Hit Probability of 75%; this is a simple, easy-to-understand number arrived at through mountains of data and advanced number-crunching — a sure sign of a good statistic.

Thankfully for Hughes, both Upton and Cabrera’s liners were hit with relatively low launch angles, the kind that don’t normally turn into dingers. They do generally turn into doubles, however.

110 MPH Batted Balls (2016)

Launch Angle Hits AB AVG wOBA 1B% 2B% 3B% HR%
Launch Angle Hits AB AVG wOBA 1B% 2B% 3B% HR%
14° 29 41 0.707 0.832 22 46 2 0
15° 20 29 0.690 0.907 3 55 7 3
16° 32 38 0.842 1.087 16 55 5 8

Cabrera’s F-7 was hit at a 14° launch angle and Upton’s F-8 at 15°; it’s difficult to get away with conceding those type of launch angles at 110 MPH, but Hughes did it on May 17.

Hughes got away with a few that day at Comerica Park, and he also seems to have a good attitude about the whole thing when he doesn’t get away with it.

The 2017 season promises many new and exciting things, and I, for one, think Statcast’s new Hit and Catch Probability tools — and hopefully their integration into MLB broadcasts — are two of them.

I suppose we’ll find out if the Twins agree.