Question: How can analytics determine when a player is going to have a stress fracture or tear an ACL? Athletes can step or land the wrong way at any time in soccer, rugby, basketball and especially football.
Answer: It's all about the data. If the player's injury history, the maximum levels the player can perform and his functional movement patterns and limitations are tracked over time, the length of time specific body parts will function at high levels can be forecasted. Of course, some athletes are freaks of nature and outlast more than others but if the Chicago Bulls had this information upfront about Derrick Rose, they could have adjusted their roster and payouts accordingly.
Question: Most sports like the NBA, NFL, MLS and MLB have scouts that travel to watch practices and games all the time to evaluate players and watch film. Does analytics replace these jobs in the future?
Answer: Absolutely not. You can never replace the skilled eye and intuition for talent, especially from people who have either played the sport on a professional level or have studied the sport and what it takes to be successful on the professional level. Analytics, however, can be used to determine which types of players (build/physical makeup, speed, reach/span, age) are more likely to be successful based on a team's dynamic and the blending of other players on the team - again based on well-defined history of data tracked.
Question: NBA teams seem to use analytics for their coaching as well to determine what are the most successful plays given certain scenarios. Analytics seems to take the art from coaching and makes it a science created by algorithmic nerds.
Answer: Always an engineering and systems supporter but never a fan of using analytics to devalue the competition and athleticism during games, it is, however, a good extra piece of information that coaches can use to augment their decisions based on match-ups, team members in foul trouble, PPG of key players at a point of time and opponent history during the same quarter in similar situations. Mark Cuban and Rick Carlisle are huge supporters of analytics in how it coaches up from the data to give the competitive advantage to increase the team's chances of winning the game. Keep in mind if every team uses analytics, it turns into which Ivy League analyst and data developer is the smartest - definitely not what any sports fan wants to hear about when it comes to the love of the sport.
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