Analyzing Blue Jays Hitters’ Seasons To Date, Using the xSeries
(Title photo courtesy of Keith Allison, https://www.flickr.com/photos/keithallison/)
Breaking Blue has been releasing and updating batting models that use batted ball and plate discipline data to predict important peripherals, which are in turn converted to superior summary statistics wOBA and wRC+.
You can read about the initial methodology here are see our updated numbers on the Breaking Blue Statistical Resources page. Since the introductory article, numbers were park adjusted and the formulas were improved and that’s reflected in the updated numbers.
Breaking Blue releases general baseball analytical content but we’re also Blue Jays fans who aim to inform the Blue Jays fanbase of what’s happening inside the numbers with the Blue Jays. This article will look at how Blue Jays hitters are really performing, in terms of their batted ball and plate discipline peripherals as expressed in the July 4th xSeries update.
To date, the Toronto Blue Jays have enjoyed extraordinary offensive production. They lead the Major Leagues in run scored by a considerable margin, scoring 5.4 runs per game, a pace that makes them seem removed from our present era. And their summary stats suggest they actually have been that elite too: their 115 wRC+ leads baseball (although the Dodgers are at 122 without pitchers) based on a .266/.334/.447 line. Second base and centrefielder were projected as deficiencies entering the season and when Dalton Pompey was demoted, the situation in centre appeared dire. But, Kevin Pillar and Devon Travis have performed more than admirably and role players Danny Valencia and Chris Colabello have stepped up too.
Will this continue? To a significant degree, yes. Fangraphs Depth Charts, which combines two respected public projection systems, Steamer and ZiPS, expects the Blue Jays to score 4.61 runs per game over the remainder of the season, tied with Boston for tops in the Majors. That’s not 5.4 runs, but it’s a considerable output and the Blue Jays realistically are not going to continue scoring over five runs a game.
The BaseRuns system, also displayed by Fangraphs, models the run-scoring process using the events produced by hitters, removing sequencing effects that can over- or under-represent the quality of a team’s output. The Blue Jays have scored a league-leading 5.02 BaseRuns per game so far. This is a great offense but probably not one that blows every other team out of the water.
Now, to the individual stats. I grabbed the real and expected batting lines and summary stats for each Blue Jays hitter with 100 PA or more. This is illustrated in Figure 1.
The real stats to date are in blue and expected stats in purple. wRC+ is painted conditionally. On a composite level, the real numbers appear inflated. The average wRC+ for Jays hitters here is 119, well above the average xwRC+ of 105. Most Blue Jays hitters are over-performing compared to their plate discipline and batted ball stats. They are generally hitting for better average, getting on base more, and accumulating extra bases at rates that exceed their peripherals. There are surely factors that the xSeries doesn’t properly account for, but it succeeds in modelling expected rates based on the available plate discipline and batted ball data.
Now let’s look at the individual hitters in depth, starting with the under-performers. No Blue Jays really stick out from this perspective, although that’s to be expected from a team that has scored 5.4 runs a game.
Jose Reyes is a very accomplished major league hitter who projects by Steamer and ZiPS to be exactly a league-average hitter. His OBP skills have deteriorated to the point that he’s not really the special leadoff hitter that he was previous in his career and is still assumed by some to be, but he’s fine in that role, especially since John Gibbons smartly hits his three best hitters immediately following instead of going traditional with his lineup. Reyes profiles as being almost a league-average hitter to date, coming in with a 95 xwRC+. This is built on his solid plate discipline rates. He goes up there hacking but has the contact skills (90% Z-Contact% is good) necessary to limit strikeouts and pick up the occasional walks. A 95 xwRC+ isn’t great in general and it won’t make Reyes worth his contract, but it means that he’s been playing better than the real 86 wRC+ suggests.
Ryan Goins has an xwRC+ mark that is 14 points above his real wRC+, but both marks are awful and his defence is not good enough to make him a player you specially want in the lineup. He’s best used as a utility infielder who spends time split between the big club triple-A. Goins is not particularly skilled at any of the four major peripherals modeled by the xSeries. His walk and strikeout rates are okay if you’re getting some other production, but his contact isn’t productive. Still, his performance to date has probably been better than what he’s shown.
Most of the hitters fall into the middle group. The real statistics they’ve compiled accurately represent how their talents have expressed themselves objectively at the plate.
Justin Smoak leads the team in xwRC+ and his real stats are also outstanding. His average fly ball/line drive exit velocity of 98.17 mph is third in the Major Leagues (min. 100 PA) behind two guys who really hit the crap out of the baseball: Giancarlo Stanton and Joc Pederson. He’s also not chasing many pitches (23.1% O-Swing%) and is pulling many batted balls (48.1% Pull%). The overall package has been outstanding.
Kevin Pillar has really done all the Blue Jays could have asked. He isn’t a great hitter or anything, but the total package of his bat, glove and baserunning has made him an above-average regular this season. He’s been solid with the bat and his peripherals verify that. Pillar rarely walks and his xBB% is just 2.2%. But he doesn’t swing through many pitches in the zone (90.3% Z-Contact%), has good speed (speed score of 6) and has posted okay fly ball and ground ball exit velocities. He still can’t be banked on as a true long-term solution for the Blue Jays, but he’s alright and is plugging what looked like a considerable hole.
Most of the Blue Jays hitters are slightly or more seriously over-performing their peripherals.
Josh Donaldson has a 133 xwRC+, which is still fantastic and would keep his season to date a success. He is a great hitter who makes contact at an okay rate and does a lot with the contact he makes. His average fly ball/line drive exit velocity is 25th in the Major Leagues at 95.79 mph. Donaldson swings through his share of pitches but not at an alarming rate, just a rate that suggests his near-.300 batting average isn’t legitimate. But, he’s still great and you should be very excited about him. Jose Bautista is much of the same story. He hits the ball very hard, swings through some pitches, has good plate discipline and is a great hitter any way you slice it.
Devon Travis and Russell Martin have probably been hitting more like above-average hitters than like great ones. Travis sprays the ball all over the field, doesn’t swing through that many pitches and has a balanced batted ball profile. His expected numbers are fine and the Blue Jays would be very happy should he keep playing like this going forward. Martin has popped up a massive number of fly balls; his 24.2% IFFB% has led to him popping up nearly 8% of all batted balls. That’s too many, but it should regress heavily as he’s shown a much more typical batted ball profile over his career. His other skills look good; better-than-average power, walk and strikeout indicators.
Edwin Encarnacion is the disappointment in this list although I wouldn’t panic yet about him going forward. There is power in him (.186 xISO) and he has a great track record. However, his Hard% is below-average at 27.7%, he’s not making great contact in the zone (83.3% Z-Contact%) and is popping up at a crazy rate (17.7% IFFB%). Not a great picture to date, even though his real stats have come around somewhat following the very slow start.
Danny Valencia and Chris Colabello are certainly playing over their heads; that doesn’t take much digging to realize. Both have fine expected stats though. Colabello is hitting the ball hard (94.23 mph average fly ball/line drive exit velo) and has a very good .369 xBABIP. However, he doesn’t profile as much of a walker and he strikes out a lot. The skills are there for him to be a major league hitter, but not a great one as he’s shown. Valencia is a useful bat off the bench against lefties who can play multiple positions. He’s hitting the ball really hard (9th best average fly ball/line drive exit velo, at 96.97 mph) and he hasn’t yet hit an infield fly! The type of contact he is making more than buoys his minicule walk ability (4.5% xBB%). He’s been a legitimately good hitter although the Blue Jays shouldn’t really expand his role going forward. He’s a fine piece of the team’s puzzle.
Ezequiel Carrera just isn’t a very good hitter and nobody would confuse him as such. He’s best utilized as a fourth or fifth outfielder and that’s the extent of the Blue Jays plans for him. Carrera doesn’t hit the ball hard and his contact skills are lacking (below-average 85% Z-Contact%).
That’s how the Blue Jays have been hitting so far. How they will hit going forward is anyone’s guess, although the expected numbers that Breaking Blue produces provide valuable information into how a hitter’s talents have translated into production in the past and these numbers are relevant to the future. The Blue Jays have been a great hitting team by all angles.
September 16, 2015
I’m curious if you know of, or can create, data on how the jays perform vs “elite”* pitching (ie vs all MLB including mediocre and poor pitching).
My interest/concern is that in the playoffs the jays will face (more) elite pitching.
Feel free to email me if you’re so inclined.
Thanks in advance
*obviously elite can be defined a number of ways…ERA, WHIP etc…
September 18, 2015
Yes, I could use play-by-play data to figure out how the team (compared to other teams) performs against different qualities of pitching. That’s an interesting idea for an article, I may end up using it. I’d probably pick multiple stats (maybe ERA- and xFIP-) and reference’ 2015 numbers to define the pitcher buckets.