Saturday, July 26, 2014
More Statcasting…and the death of the amateur sabermetrician?
Another incentive for the league—particularly in the face of rising salaries—is an improved understanding of player value, particularly on the defensive end, where teams have focused more attention in the past few years. Defensive shifts, once only employed by the wonkiest teams, have become a league-wide staple thanks to advances in batted-ball data. The problem is, shifts or not, evaluating glove work remains difficult, as most teams rely on some combination of scouting reports, play-by-play data and manual charting. Statcast offers something better: a way to focus on a player’s defensive attributes—his reaction time, range, route efficiency and so on—rather than his results, which are influenced by too many independent variables to list. This potential has excited many outside the industry (especially with the promise that the data will be made public) and even more within.
The only negative to come from all the new technology could be the death of the hobbyist. An important consideration, because some hobbyists have done research that changed how people inside and outside the industry approach the game. For example, Mike Fast was working as a physicist when he used PITCHf/x data to confirm the long-held suspicion that catchers influence how umpires call balls and strikes. Fast is now employed by the Houston Astros. Because the new data are so unwieldy, the barrier to entry so high, only select outsiders will possess the computing strength and wits to scale the wall. In time, someone might make a discovery that eluded the industry. Otherwise, the real advances—those that change how teams are built and how strategies are employed—will happen behind closed doors.
Tuesday, July 08, 2014
Having advanced performance data at even the most junior levels will make it less likely that players get filtered out based on 60-yard-dash times or radar-gun readings, and more likely that they advance on the merits of practiced skills. The ability to “paint the corners” of the strike zone, to swing only at pitches within that zone, and to manage the subtle footwork required of a difficult fielding play is accessible to any player willing to commit to the “10,000 Hour Rule” (the average amount of practice Malcolm Gladwell, in his book “Outliers,” says is needed to excel in selected fields). A whole new class of players whose skill sets previously were not fully appreciated will be able to reach the highest levels thanks to a more nuanced understanding of their abilities.
The current modus operandi of building rosters to maximize the sum of individual talent also will be challenged; data compiled using new technologies will enable management to assemble players in new ways, emphasizing their ability to complement one another. Whereas current metrics describe players’ performance in isolation, front offices will increasingly rely on statistics that measure a player’s value in the context of the rest of the team, picking up externalities such as how a player’s defensive abilities may compensate for the deficiencies of those playing around him.
In a new twist to the “old school vs. new school” debate in sports, technology-based roster-building and algorithm-driven decision-making thus will be the strongest propagators of the traditional virtues of teamwork and chemistry. (I should note here that these opinions are my own—and not those of my club, the Oakland Athletics, or Major League Baseball.)
Technology will create an equally drastic shift in front offices. Aspirants to the front office already are just one click away from decision makers, thanks to social media. It is not uncommon for a blogger’s analysis post to show up in a general manager’s Twitter feed—a level of proximity and access unheard of a decade ago. Many sports franchises are already hiring analysts based on their work in the public sphere; as social media become more targeted and efficient, the line between the “outsiders” and “insiders” will narrow.
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