The real winner of the World Series? Data Strategy
The real winner of the World Series did not throw a strike, hit a home run or caught a fly ball. The real winner didn’t wear a uniform, chewed gum or showed any emotion.
The real winner knows everything about baseball, can predict the probability of any baseball moves with remarkable accuracy, and lives in the world of mainframes, cloud and smartphones.
As The Guardian reported:
In a now famous Sports Illustrated story from 2014, Ben Reiter described an enclave in the team’s offices where a group of employees have created an evaluation database that contains piles of information about every player in the organization, as well as those the team considered drafting. “The inputs include not only statistics but also information – much of it collected and evaluated by scouts – about a player’s health and family history, his pitching mechanics or the shape of his swing, his personality,” Reiter wrote. “The system then runs regressions against a database that stretches back to at least 1997, when statistics for college players had just begun to be digitized. If scouts perceived past players to possess attributes similar to a current prospect, how did that prospect turn out? If a young pitcher’s trunk rotates a bit earlier than is ideal, how likely were past pitchers with similar motions to get hurt?”The Astros were not alone. The Dodgers are not very far behind:
The Dodgers, for instance, employ a Senior Analyst in Research and Development, Dan Cervone, who studied math and statistics at the University of Chicago, interned at Google, earned a PhD in statistics at Harvard, served a fellowship at NYU, and turned down offers from hedge funds to crunch baseball stats, or more accurately, according to his web site, focus on “spatiotemporal data and hierarchal models, with particular application to sports analytics and player tracking data.”The Astros and Dodgers turned data into insights and knowledge by following three guidelines that should be at the core of any data-driven business:
- They put data the core of their corporate strategy: While many teams claim to play Moneyball, most teams and companies still underestimate the importance of data. Both teams regard data as an essential ingredient of their success formula and their hire accordingly.
- They regard data as a key asset of their team: Both teams sign players based on complex data models, based the contract size and length on data sets and managers are not relying on their intuition anymore when replacing pitchers and hitters. Human intuition is just another data set just like multiple other decision points.
- They treat data like currency: While data should be easily accessible, it needs to be managed and tracked carefully. This allows team to tap into the data stream when needed and establish controls to prevent mishandling.