ESPN Analytics Rankings: Jays still believing


ESPN the Magazine recently published its rankings for 122 sports teams analytics departments, ranking the strength of the departments, buy-ins from players and coaches, its investment in biometric data and how much of its approach is predicated on analytics.

Unequivocally, baseball has been emersed in analytics or sabremetrics (the fancy word) far longer and to a far greater extent than other sports since Billy Beane started the moneyball era. Despite baseball’s dominance, analytics have slightly tailed off in terms of new inventions with WAR, FIP, XFIP, BABIP, DRS, wOBA, and wRC+ already been established as the predominant way writers, fans and most importantly the front office predicts future performance.

With that said, there are some teams who, despite the science being a decade old, still refuse to believe in it’s applicability and instead confer to the intangibles on the field like hard work, “the bounces,” small ball and the old way of doing things.

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In this year’s rankings, the Toronto Blue Jays were placed in the second category as “believers”. Among them are teams like the Baltimore Orioles, Washington Nationals, New York Mets, Kansas City Royals, Los Angeles Dodgers and the San Diego Padres.

For Toronto, it all started in the short time after Moneyball took place (no I don’t mean the movie) with the hiring of General Manager J.P Ricciardi. Ricciardi, with the help of now ESPN baseball analyst Keith Law, implemented some of what Moneyball had taught the baseball world but not nearly enough. As the story goes, the two had a falling out around 2006 and Ricciardi, was let go in 2009 to be replaced by the current GM Alex Anthopoulos.

In 2011, the Jays hired Jay Satori to take over the department but resigned last year for a job at Apple. Joe Sheehan took over the department, hiring Jason Pare last year as the number two man to help out with the department. But, sadly, that’s pretty much it.

Dec 8, 2014; San Deigo, CA, USA; Oakland Athletics general manager Billy Beane (right) during MLB Winter Meetings at Manchester Grand Hyatt. Mandatory Credit: Jake Roth-USA TODAY Sports

With that said, there isn’t a lot the public can discover about how strong the Jays analytics department is. Anthopoulos won’t allow the two to speak to the media so things are about as opaque as the ongoing left-field/second base situation.

What the public does know about their analytics department is that they apparently used it to predict Dioner Navarro’s 2014 offensive success. However, they failed to see how bad he actually is behind the plate. The advanced approach is also manifest in the 686 shifts the Jays exhibited in 2014, saving 16 runs.

Most of their present work is attributed to the BEST program created in January 2013 that was designed to unify scouting reports, proprietary analytics, medical reports, contractual information and video in a single spot. Essentially, it’s Google in one link.

Despite the advanced system, some of the moves the Jays have made via the analytics department should leave the average Jay fan scratching his head. For example, in 2012 the Jays hired a biometric firm to test the mechanics of Brett Cecil and Brandon Morrow. Biometrics in baseball, for those who don’t know, is basically the study of a pitchers mechanics. With that in mind, the Jays received the results and, seeing no relevance in the findings, tossed them in the garbage. Unlike the Orioles, Rays, Brewers and Indians, the Jays made the statement-albeit two years ago- that they don’t believe in biomechanics.

What may be more alarming is Anthopoulos’ comments to Shi Davidi in an interview last year. In the piece, David quoted Anthopoulos saying he was “leery” of appearing like “we’re doing something someone else is not…trust me we’re not.”

That is a problem. Any analytic department’s main aim should be exploiting market inefficiencies to get an edge on other teams across the league. The goal should not be to do what everyone else is doing. This axiom exists in all walks of life; if everyone is doing the same thing, how could you expect to arrive at a different destination? If the Jays are attempting to build a championship team, being homogenous isn’t typically the right avenue to accomplish it.

It’s unclear why the Jays front-office analytics department is so small. It’s hazy whether they will add to this department.

For now, the Jays will continue implementing the shift among other proprietary information they’ve acquired through their analytics department. Mostly, they will continue to look for the championship team using the same methods everyone else is.