Toronto Blue Jays’ Danny Barnes has dominated the first hundred (and four) batters he’s faced

 

Jays From the Couch looks into the relative early success of Toronto Blue Jays reliever, Danny Barnes

 

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On Wednesday night, Toronto Blue Jays’ reliever, Danny Barnes, crossed the hundred batter mark for his career. Now, I don’t think that really means anything. It is probably just an arbitrary milestone. But I was there to see it. He stepped up in the 5th inning of a 7-7 game, faced eight batters and got six outs. Later that evening, I caught Jays in 30 (nothing beats watching Jays in 30 after a good win). As a testament to Danny Barnes’ style and success, they edited out both of his innings. He has developed into a human fast forward button. Nothing exciting happens when he pitches. That’s a really useful trait for a reliever to have.

 

Projection systems love him

 

Fangraphs publishes two single-season projection systems: ZiPS and Steamer. Both systems are fans of Danny. ZiPS projects him to produce one win above replacement this season, a solid amount for any relief pitcher and the second highest projected WAR among the Jays’ bullpen staff (after Roberto Osuna). Steamer also projects him to be the second most valuable reliever on the Blue Jays this season (also after Osuna). Thus far, Danny’s way ahead of schedule, having produced 0.3 WAR in only 12 IP.

 

 

Danny is also a standout in the KATOH projection system. Unlike the others, KATOH tries to project the WAR that a prospect might produce in their first six MLB seasons. Its focus on prospects requires it to use minor league data in its projections. This might help explain why KATOH loves Danny: he had an unexpectedly brilliant minor-league career, particularly at the upper levels. During the 2015/16 seasons, Danny struck out about 30% of the batters he faced at the AA-level (96.1 IP). That earned him a promotion to AAA, where he proceeded to strike out 42% of the batters he faced (25.2 IP)!

 

KATOH projects Danny to produce 2.8 WAR in his first six seasons, a decent amount for any reliever. For perspective, only 70 relievers produced a total of 2.8 WAR over the last six seasons (2011-2016). For more perspective, 2011-2016 represented the first six MLB seasons of relievers Brad Brach and Bryan Shaw, two solid setup men. Brach produced 2.2 WAR, while Shaw produced 2.4 WAR.

 

He does not surrender good contact

 

The key to Danny’s success is generating weak contact. His much better-than-average xwOBA (.236) and wOBA (.256) are driven primarily by his much, much better-than-average xwOBA and wOBA on balls in play (.266 and .296). He’s shown remarkable consistency thus far, maintaining a five-game rolling average xwOBA below.280 (the average MLB reliever has an xwOBA of .307). He’s no slouch on non-balls in play, as he’s maintained better-than-average strikeout (23.1%) and walk rates (7.7%). He particularly stands out in generating infield flies (6.8% of the batters he’s faced have popped out), the least-dangerous of the batted ball types, and soft contact more generally (26.4% of balls in play). He has also effectively limited line drives (15.5%), the most dangerous batted-ball type.

 

 

 

Danny steps up against the league’s best hitters

 

Danny Barnes might have generally been used in low-leverage situations thus far (career gmLI of 0.7, where 0.85 and below is considered low-leverage), but he has definitely not been handed the easiest opposition batters. Most of his opponents have been above-average hitters (63 of the 104 batters he has faced have a career wOBA above .318, the 2016-17 MLB average) and he has been handed more than his fair share of truly elite hitters (27 batters he’s faced have a career wOBA of .350+). He has absolutely owned this group of hitters, limiting a murderer’s row of Trout, Pujols, Ortiz, Holliday, HanRam, Betts, Carpenter, Judge, Cruz, Encarnacion, Dickerson, Springer, Pedroia, Longoria, Correa, Santana, Lindor and Piscotty to two singles and two doubles, while striking out six and walking none.

 

 

Barnes’ Arsenal

 

As discussed by BP Toronto’s Sean Addis, Danny primarily uses three pitches: a four-seam fastball, a changeup and a slider. Thus far, all three have been above-average pitches based on PITCHf/x’s weighted runs per 100 pitches metric. His slider has been particularly effective, his likely motivation for increasing his use of the pitch in 2017.

 

 

In examining his pitches, I found a few nuggets of interest. He has the 7th highest vertical gap (8.1 inches) between his fastball and changeup (among 143 relievers who used both pitches at least 5% of the time). Intuitively, this vertical gap should have two positive effects: batters should be more likely than usual to get under the rising fastball and on top of the sinking changeup. For the most part, this holds true in Danny’s case. His fastball generates an above-average number of fly balls (46.2% of batted balls vs. roughly 35% for MLB relievers) and a way-above-average number of infield flies (23% of batted balls vs. roughly 3.5% for MLB relievers). His changeup generates a slightly-above-average number of groundballs (47.1% of batted balls vs. roughly 45% for MLB relievers).

 

However, his 2017 “slider” is definitely his most interesting pitch. I’m not even sure it is a slider. I always thought sliders…well, slide across the plate, particularly moving towards the pitcher’s glove side. According to PITCHf/x, his 2017 slider moves significantly to his arm side (SL-X of -8.4)! The other relievers with very negative SL-X are lefties (in fact, only Brad Hand has a more negative SL-X thus far). Aaron Loup’s SL-X is -7. Andrew Miller’s SL-X is -6.5. In terms of horizontal movement (-8.4 vs. -10), vertical movement (2.2 vs. 2.1) and average pitch velocity (79.8mph vs. 79.6mph), his 2017 slider seems identical to his changeup (so maybe there’s an identification issue on PITCHf/x’s part, though I wouldn’t reject the possibility that I’m simply misunderstanding the data). Whatever it is, it’s been effective (66.7% grounder rate, .200 xwOBA). This is definitely something I intend to dig into further (please pass on any answers you might find).

 

 

Danny Barnes’ Future

 

In his first 20 big league games, Danny Barnes has more than held his own, producing better-than-average results (.256 wOBA). His performance does not seem to be of the typical luck-driven, small sample size variety. His BABIP luck is pretty neutral (.292 BABIP vs. .296 average reliever BABIP) and he probably was a tad unlucky in terms of contact vs. outcomes (-.020 xwOBA – wOBA). The only red flag is his 0% HR/FB%, but even that’s not too damning. If three of the fly ball outs he produced turned into home runs, his HR/FB% would move up to 10%, just below the MLB reliever average (11.9%). Those three extra home runs would have increased his wOBA to .317, still making him an average MLB reliever (a very useful thing).

 

The quality of his performances thus far are not in question, but it is fair to ask what the future holds for Danny Barnes. The most accurate answer is: I have no idea. Predicting reliever performance might be the biggest fool’s errand in baseball. But there is a lot to like in what he has done and how he has done it (and three different projection systems all seem bullish on him). Keeping up his successful approach should put him in a good position to continue producing successful outcomes. Of equal importance will be his ability to adjust to the adjustments batters will make now that they have more data on him and his pitching style.

 

As usual, I’m optimistic. I think his adjustments between 2016 and 2017 reflect positively on his adaptability (his two-seam fastball was his worst pitch last year, so he ditched it this year). Plus, he was an economics major who used his statistics skills to write a thesis on baseball. Sounds like my kind of guy!

 

 

 

*Featured Image Credit: Joel Dinda UNDER CC BY-SA 2.0

 

 

 

 

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I’m an economics professor in the GTA whose lifelong love for the Jays was reignited by that magical August of 2015 and the amazing moments since.

Jeff Quattrociocchi

I’m an economics professor in the GTA whose lifelong love for the Jays was reignited by that magical August of 2015 and the amazing moments since.