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Joey Gallo: Elite Baserunner?

In the boom-or-bust era of plate appearances, baserunning value has become less important than it’s been in quite some time, but it’s a fascinating part of the game in which you can literally steal a win here and there. Given that this fourth pillar of the game is a pillar nonetheless, here’s a list of the top six baserunners this year by BsR, with their stolen base and caught stealing totals as well (as of 06/18/2017):



Billy Hamilton

6.8 28


Xander Bogaerts

6.6 8


Jarrod Dyson

5.7 17


Dee Gordon

5.7 25 3
Paul Goldschmidt 5.6 13


Joey Gallo 4.8 4


Some of the guys on this list are the burners you would expect to see, and Xander Bogaerts is a pretty athletic, fast guy. Paul Goldschmidt is a freak and has been far and away the best at baserunning among 1B by BsR since 1950 (relative to the smaller number of games he’s played), which is a highly underestimated part of his game.

Other than Goldschmidt, who you should already know is fantastic at everything in baseball, the name that really sticks out is Joey Gallo, the barrel-chested guy with an 80 power rating as a prospect who thumped homers at every level of the minors. He’s also hit some big ones in the majors; we’d be talking about his homers a lot more if Aaron Judge wasn’t doing his own thing in the Bronx. If you Google “Joey Gallo home run” and go to videos, words like “mammoth,” “crushes,” and “monster” pepper the results. Gallo is 6’5” and 235 lbs. In short, he’s not the guy you expect to be atop the BsR leaderboard, earning his team nearly half a win this year with his legs, especially given his low SB total.

So how has Gallo achieved this high level of baserunning despite clearly not passing the baserunning eye test? He is generally athletic, which he recently discussed. The obvious first take is that Gallo strikes out a lot, so he doesn’t have the opportunity to ground into double plays and negatively affect his BsR. This is true, to a certain extent, but doesn’t tell the whole story. Of the three components of BsR (UBR, wSB, and wGDP), UBR is the primary source of value for Gallo. This can generally be perceived as a measure of baserunning skill, as it looks at how often the baserunner takes extra bases in the same situations. This metric may be a little team-dependent, but Gallo ranks seventh in baseball at 3.1 runs added. The value from this metric is derived from both taking extra bases on hits as well as while already on base. However, Gallo only has 24 non-home run hits this year, only 11 of which went for extra bases, leaving him without much room to boost his UBR rating. Therefore, a lot of this value likely comes from his time running the bases while already on them. Gallo has been on the bases 59 times this year (including non-home run hits, walks, HBP, and reaching on an error or fielder’s choice), giving him many more opportunities to make plays on the bases.

Gallo’s overall assessment by BsR as a good baserunner is a result of the other metrics as well. Couple that high UBR rating with a tenth-place ranking in wGDP (1.0 run), the metric that favors Gallo because such a high percentage of his plate appearances result in either strikeouts (37.2%) or medium/hard contact (81.7% of his batted balls). Both of these outcomes reduce the number of double plays he grounds into, leading to a slightly positive contribution to his BsR. In fact, Gallo has only hit into one double play this whole season over 247 PA. Gallo’s wSB (0.7 runs) is respectable as well, if only because he has yet to be caught stealing.

It’s possible that Gallo isn’t on the bases enough to have his BsR statistic stabilize and he’ll regress quite a bit as the season wears on, but that remains to be seen. What we do know is that Gallo is a good baserunner this year because he does a pretty good job taking extra bases, hasn’t been caught stealing, and strikes out/crushes the ball enough to rarely hit into double plays. Does that add up to being an actually good baserunner? Gallo has still been an effective baserunner this season compared to his peers, albeit not by the usual definition of the term, especially considering (and likely assisted by) his profile as a high-strikeout, high-power hitter. That value is derived from a variety of factors, so don’t expect to see him go 30-30 (or even 20-20) anytime soon, but keep an eye out for him when he is on base.

A One-Man Marte Partay Between the Bases

This article originally appeared on the Pirates blog Bucco’s Cove.

“Speed kills.” –Al Davis

Starling Marte is having a hell of a season stealing bases and this is one of the things that should have propelled him into the All Star Game without needing the stupid final vote. He is the top baserunner in the NL this year, he’s second in the league with 25 stolen bases, and he has a better percentage than the leader Jonathan Villar.

A recent game against the Cardinals gave a strong piece of evidence of Marte’s preternatural baserunning ability when he stole second base with Carlos Martinez pitching in the sixth inning:

The Pirates’ announcers commented on the fact that people very rarely steal off of Martinez. I went to look at the numbers: in 399 2/3 innings since entering MLB, Martinez has yielded only 10 stolen bases in 19 attempts. I think the 19 attempts is really indicative of his abilities to control the running game; people just don’t even try to run on Carlos Martinez. Martinez ranks 36th among all pitchers in SB/IP who have thrown at least 200 innings since 2013, which is decent. However, if we limit ourselves to looking at only righty starters over this time period (since it is much harder to steal against lefties and game circumstances are a bit different between starters and relievers), Martinez ranks 13th among pitchers with the same innings restrictions. (I’m not including tables for all of these stats, but if you want to see for yourself, mosey on over to the Baseball Reference Play Index, where all of this data comes from.)

Martinez has really shut down the running game since becoming a full-time starter in 2015, however. Over that time period, he ranks fourth among all pitchers (lefty, righty, starter, and reliever alike) having at least 250 innings in SB/IP, yielding only four SB in nine attempts over 282 innings.

Rank Player SB IP SB/IP
1 David Price 1 336.2 0.00297
2 Wade Miley 2 281 0.00712
3 Yordano Ventura 3 250.2 0.01199
4 Carlos Martinez 4 282 0.01418
5 Chris Tillman 4 279.1 0.01433
6 Wei-Yin Chen 5 290 0.01724
7 Danny Salazar 5 284 0.01761
8 Johnny Cueto 6 334.1 0.01796
9 Chris Sale 6 328.2 0.01828
10 R.A. Dickey 6 324 0.01852

(Note: If you bump this down to 150 innings to get more relievers on the list, Martinez is still in the top 10 for SB/IP.)

Of the four pitchers ahead of him in the table, two are lefties. (Sidebar: How the hell is R.A. Dickey on this list given the fact that he throws a knuckleball? It seems like it should be really easy to steal on him given that.) Martinez is similarly ranked (fifth) if you look at SB/Total Baserunners over the same period; in short, Martinez is really, really good at controlling the running game.

Furthermore, reigning eight-time Gold Glove winner Yadier Molina was behind the dish attempting to throw Marte out. Molina ranks first among all catchers since 2002 in his ability to control the running game by the defensive metric rSB. Obviously Martinez’s ability to prevent the stolen base is helped by having Molina behind the dish, but the combination of these two has been deadly over the past season and a half, making Marte’s accomplishment all the more impressive.

The Martinez/Molina duo (and Martinez in general) has only allowed one other stolen base this season so far. Who was it? None other than Bartolo Colon! Actually, I’m kidding, it was Starling Marte, which is almost as crazy! He has the only two stolen bases this season against a guy who only gave up two all of last season. These are also the only two attempts against Martinez all season. On May 6, after a bunch of false starts, pickoff moves, foul balls, and laughs between Molina and Marte, he finally got his stolen base:

The thing I find most entertaining is how loose everyone seems, goofing off and laughing about the play that just happened, which seems relatively rare in this day of boring interviews and generic soundbites. Molina had a good laugh about that one, but he was pretty upset about the more recent stolen base.

There’s nothing to be mad about, though; Martinez and Molina simply got burned by the best baserunner in the game right now.

The Future of Analytics In Baseball: How Will Small-Market Teams Fare?

This post originally appeared on the Pittsburgh Pirates blog Bucco’s Cove.

A recent episode of the Baseball Prospectus podcast Effectively Wild (and if you don’t listen to it, this is one of the best baseball podcasts out there) had two analysts from the LA Dodgers’ front office as guests. During the episode, one of them said, “Even though we have grown substantially in the last year…” and went on to talk about the size of their analytics department and how they work together. This is a scary prospect for small-market teams like the Pirates; embracing analytics before such things were en vogue allowed teams like the Moneyball A’s, the Royals, the Pirates, and many others to gain a competitive advantage over their comparatively retrograde competition still throwing money at their problems every offseason.

The window of opportunity for small-market teams to use advanced analytics to their advantage may be closing faster than we think. Most (and possibly all, I don’t have access to every team’s front office payroll) teams have some sort of analytics department (or “Baseball Operations Department,” as they’re often dubbed). According to this ESPN article from about 14 months ago, only two woeful teams are listed as “nonbelievers,” the Marlins and the Phillies, and the Phillies have since seen some significant shuffling in their front offices. Larger teams are beginning to emulate their smaller counterparts to varying extents, with results that will bear fruit over the coming seasons. As a fan of a small-market team, this is concerning; the limited dividends paid from the analytics advantage may mean a return to the old power structure in baseball in which larger-market teams with more money have the ability to acquire players at will. The difference, however, will be that stats will have informed the signings, so if two teams are targeting the same player for “sabermetric reasons,” the team with more money will obviously still have the upper hand.

Scarier still for fans of small-market teams is that the greater financial capital available to geographically-favored franchises is that these financial resources can not only be employed to sign the best players, but also the most talented analysts and more of them. The premise that teams all have access to effectively the same data and analysis is rendered moot if larger franchises can secure a stronger analytics department, both in terms of the number of analysts and the talent of the analysts (money could even be used to lure talented analysts to the richer franchises in the same way that players are). For example, the Cubs thus far this season seem to be a perfect confluence of young talent, effective free-agent signings based on a strong analytics department, and a hell of a lot of money, which is exactly where you want to be if you’re trying to create a dynasty and win multiple Commissioner’s Trophies.

Parity in the league is still greater than that of the NFL, but we could be witnessing the last generation of such parity. How is such a situation solved? The one obvious choice is a salary cap; the player’s association would be loath to support such an idea, although it’s perhaps beginning to be in their interest. As the league’s revenue increases, players haven’t been getting the same share of that revenue, according to Nathaniel Grow on FanGraphs. A quote from that article:

“The biggest difference between the NBA and MLB, then, isn’t the fact that the former has a salary cap while the latter does not. Instead, the primary difference between the two leagues’ economic models is that by agreeing to a “salary cap,” NBA players in turn receive a guaranteed percentage of the league’s revenues, while MLB players do not.”

According to the same article, the players’ share of revenue has fallen about 13% to 16% since 2002 or 2003. While this argument is unlikely to induce the MLBPA to support a salary cap, a downturn in league parity could force their hand at some point in the future. This would be a long-term effect, however; many years of a “lack of parity,” coupled with a downturn in the popularity of the sport as a whole, would be required to even have the MLBPA thinking about acquiescing to a salary cap.

Coming back to the proliferation of analytics departments among MLB teams and their effect on important advantages held by those willing to embrace statistics: I don’t know what’s going to happen. There are many facets to analytics, more than just comparing players based on the BABIP or K% or arm slot or determining what players to acquire and how much they’re worth. For example, one of the Effectively Wild guests from the episode I cited earlier was a biomedical engineering major during her undergraduate studies, implying that the front office is becoming interested in the medical side of analytics: preventing injuries, improving player health, and looking at the biomechanical aspect of baseball, which takes a significant toll on players’ bodies. This is not too dissimilar from what the Pirates have done in recent years and is just one of the many components to assembling and maintaining a competitive squad.

This line of thinking admittedly removes the human component from the equation, which is still incredibly important to this entire process. There will always be GMs who are more willing to try new strategies to win and those who are unwilling to change (*cough* Ruben Amaro, Jr.). Coaching and player development, especially in the minor leagues, will continue to be extremely important for MLB franchises and is largely outside the purview of the type of statistical analysis that is widely considered in evaluating players. Rather, this part of baseball can be thought of, to a certain extent, as producing the statistics that analysts ultimately study. As a result, there will always be opportunities for smaller-market teams to hire talented personnel, including trainers, coaches, scouts, and other employees outside the scope of the Major League analytics departments that will influence franchises’ success and failure.

However, analytics at the MLB level may start to be influenced by money. Ultimately, stories like the Pirates’ repeated acquisitions of undervalued Yankee catchers who are stellar pitch framers, the Royals’ World Series win relying on great defense and a crazy strong bullpen, and the general parity of the league beyond the traditionally great franchises may be fewer and further between. Those franchises with more money may regain the competitive advantage that the sabermetric revolution has wrested away from them for the past decade, and smaller-market teams will have to find yet another way to adapt to the ever-changing baseball landscape.