The Future of Technology in Player Development

This post was written by Adam Guttridge and David Ogren, the co-founders of NEIFI Analytics, an outfit which consults for Major League teams. Guttridge began his MLB career in 2005 as an intern with the Colorado Rockies, and most recently worked as Manager of Baseball of Research and Development for the Milwaukee Brewers until the summer of 2015, when he helped launch NEIFI. As part of their current project, they tweet from @NEIFIco, and maintain a blog at their site as well.

The novel data coming into Major League Baseball from entirely new spaces, such as the wearable tech companies we mentioned yesterday, was something we should have anticipated. Within the past few years, restrictions have been imposed which attempted to dramatically flatten out the possible differences between teams in their volume of amateur spending. While the rules have proven to be easily manipulated on the international front, the intent and goal is clear, and the long-term plan for the league is to equalize the spending on talent acquisition. Therefore, greater investment in amateur talent can no longer be a long-term strategy to the extent that it drove success under previous models. At the same time, a million dollars spent on MLB talent can be expected to provide a smaller return than ever, so the influx of cash in MLB had to go somewhere.

Thus, two major areas remain where an organization’s spending is not only unrestricted, but has the potential to provide much greater dollar-for-dollar return than elsewhere: player development and evaluative advancement.

It’s probably useful to provide a description of player development, as it’s a term used liberally with nebulous definition. Speaking concretely, coordinators and directors develop guidelines for instructing/improving pitchers and hitters and fielders. Coordinators and coaches determine how to apply those guidelines to each individual. Strength and conditioning (which also encompasses nutrition and injury rehabilitation) is a vital department within player development, and works along a similar coordinator/coach structure.

So, due to the restrictions and marginal utility of other investments, there’s an impending horizon for teams in their application of resources. Just as an example: surely pitching coaches and coordinators exist who could provide something like 10% more value at the Major League level, if given the same player talent, then the average of their current peers. Given the pay scales in those roles, and given what teams may expect to receive for a marginal $100,000 invested in amateur or MLB players, it would be the most rational thing in the world for teams to pay double-market rates for the person they felt was the best pitching coordinator, or infield instructor, or hitting coach.

This behavior has already manifested itself in one related form. A minor league clubhouse spread in 1992 may have served watery soup and crackers. While things still vary greatly organization-to-organization, such an austere fueling of your own players is no longer the standard. It simply became clear, as player prices (and therefore values) rose sharply, for an investment that’s incredibly modest relative to player value, nutrition must only provide an ounce of tangible benefit to pay itself off, and it may well produce far more than that.

There’s a reason the advanced investment hasn’t yet happened with staff, and it goes beyond the inertia of industry standards: it is very, very difficult to tell if a pitching coordinator has been more effective than his peers. There’s an assignment of credit issue, as many directors, coordinators, coaches interact with each player. There’s the issue of controlled inputs; it would be very difficult to accurately normalize pitching coordinators for the quality of amateur talent they received. There’s the issue of time; to observe the effectiveness of converting 16-year-old or 18-year-old or 21-year-old pitchers into good 25-year-old pitchers takes a while. There’s also the issue of replacement; how would one know, until they were utilized, if the AA pitching coach’s philosophies may actually be better than the coordinator’s?

These issues are, as mentioned, the reason the tech has sprung up in the exact areas which it has. To practically evaluate the effectiveness of development, our current tools are very poor.

The first step in evaluating (then, improving) developmental efficiency would be the definition of values, which may be trickier than it sounds. To what degree is increased bat speed actually a virtue? For that matter, what about posterior shoulder laxity? Or greater breaking-ball movement? Or faster pitch recognition?

The new data will not solve all of the coordination challenges in measuring the value of a program or a coach. At least, though, it ought to provide tangible information by which to begin benchmarking and approaching such questions. And if teams find that certain organizations are meaningfully improving on these benchmarks in the minor leagues, then they can begin to drill down on why that is happening, and attempt to reward those responsible with salaries that reflect their impact.

Once again, these tools may only wind up having modest value for our evaluation of ballplayers. It’s entirely possible (if not likely) that the expectation for how effective a pitcher will be in the future is best informed simply by his performance record to date. The new tools, however, seem to be well positioned to assist in the creation of ballplayers, if not their evaluation, and then, incidentally, the evaluation of coaches/programs designed to develop them.

Moving forward, one should expect to see an explosion of understanding on the developmental side of baseball. Front offices may flatten their structures, though the change in this standard may be gradual. Team-to-team differences in evaluative ability (which determines the value of a front office) come from their diligence in refining and systematizing the thought processes in player evaluation, infinitely more than their mathematical/statistical sophistication. That’s always been the case, and will continue to be what drives progress in our ability to make sense of baseball, whether publicly or privately.

But right now, most of the focus in analytics is on figuring out what a player is. With the coming technical revolution, that may shift towards finding those who can help maximize what already acquired players can be.