Elite soccer is a multibillion-dollar business, and top clubs are constantly looking for the next promising young player that they can develop into a superstar. Youth academies are one way for clubs to do this, but they have to find the players with potential before they can work with them. Counterpoints talks with Chelsea Football Club’s head of research and innovation, Ben Smith, who is on an analytics-driven hunt for star material.
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What happens when a free-agent player with a hot hand and great stats gets signed to a big, long-term contract, only to perform at a mediocre level? Counterpoints examines the problem of “shirking” in professional sports by looking at the data with Richard Paulsen, who presented his paper, “New Evidence in the Study of Shirking in Major League Baseball,” at the Sloan Sports Analytics Conference.
When teams perform consistently, it’s easy to ascribe their winning (or losing) ways to the coaching staff. But the data sometimes tells a different story. So just how much credit — or blame — for team performance should coaches get? Counterpoints looks at the evidence.
In this episode of Counterpoints, the subject is baseball — specifically, the analytics-centered strategy for pitchers called out-getting, which focuses on pitchers’ efficiency rather than on when, how often, and how much they pitch. Will this practice transform baseball in the classic Moneyball tradition — or will it simply be an interesting tactic that teams sometimes use to gain a temporary advantage?
Baseball teams routinely use analytics to shift fielders’ positions so they can be placed where a hitter is most likely to hit the ball. This works well for preventing the opposing team from hitting and scoring — but it’s not so great for the game, which relies on base hits and scored runs to keep fans excited and engaged. Should “shifting” be banned for the sake of the fans?
Football players who seem mediocre in college suddenly flourish as top pro performers, while hot prospects flounder when they reach the NFL. Can teams’ recruiters and coaches accurately identify the key players that will help their team win games based on the players’ past performance? In this episode of Counterpoints, Wharton professor Cade Massey, host of “Wharton Moneyball,” argues that they can’t.
This episode of Counterpoints examines the strategic value of data analytics — and more to the point, whether the data scientists creating the analysis are being rewarded appropriately for their contribution to strategy.
While many businesses have embraced the idea that analytics can help improve performance, there are plenty of skeptics. Can analytics really show business leaders something old-fashioned intuition can’t? In this podcast episode, analytics expert Ben Alamar seeks proof that analytics really do lead to improved results.
In this episode of the sports analytics podcast, Counterpoints looks at the unusual case of Larry Murphy, a right-handed hockey defenseman whose support for Hall of Fame lefthanders helped two teams win the Stanley Cup in the 1990s. Was this outcome due to a unique quality Murphy brought to the game, or does a more general strategy of finding complementary talents improve team performance?
This episode of the sports analytics podcast Counterpoints shows that the greatest legal advantage in sports is a good night’s sleep. Using wearable devices to monitor athletes’ sleep, physiologists have shown that at least 8 hours of sleep can greatly improve performance — with implications not just for sports, but all areas of business and daily life.
- Read Time: 1 min
MIT Sloan Management Review and MIT Sloan School of Management will chat on Twitter (#MITSMRChat) about the intersection of business and sports analytics. Participants will learn how insights from the sports industry can help companies in other industries excel at performance measurement.
A winning record seems like it would help teams draw more fans to their games, yet there’s plenty of evidence that even losing teams can be profitable — sometimes more so than winners. This episode of the sports analytics podcast Counterpoints looks at the problem of selling a product with unpredictable performance by focusing on baseball.
- Read Time: 5 min
Sports analytics first proved its case on the field and in the front office, but as the practice spreads into business operations, the industry is addressing adoption challenges found in many sectors. At the MIT Sloan Sports Analytics Conference, speakers from teams and leagues discussed how they are using analytics to boost revenue, and how they’re managing transitions in culture and strategy.
- Research Highlight
- Read Time: 16 min
The successful use of analytics in sports, both on the field and off, comes down to integrating analytics within an organization. Three strategies — collaborative analytics, a common language, and accessible technology — are key.
When it comes to putting data to use, communication — or rather, lack of it — between the data scientists and the executive decision makers can cause problems. The two sides often don’t speak the same language and may differ in their approach to and respect for data-based decisions. Given these challenges, organizations may need to call upon a “data translator” to improve how data is incorporated into decision making processes.
- Read Time: 4 min
Organizations across an increasing number of sports and levels of competition are capitalizing on data to gain a competitive edge. Indeed, few industries have implemented data-driven decision making as successfully as sports. And learnings from the sports analytics revolution are applicable to a broad range of other industries.
In a conversation with MIT Sloan Management Review, Michelle McKenna-Doyle, the NFL’s senior vice president and first-ever CIO, discusses the organization’s customer-focused approach to big data and analytics. She explains how the NFL works to make its employees comfortable with their own data sets.
- Research Highlight
- Read Time: 10 min
In professional sports, some teams are becoming sophisticated in using data to measure team and player performance, sports business and health and injury prevention. Sports teams’ use of analytics has much to teach other managers about alignment, performance improvement and business ecosystems. For instance, teams are beginning to assess performance in context, seeing how teams do with or without a particular player. This “plus/minus” analysis could be a valuable technique for many businesses as well.
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