The sporting world has turned to advanced statistics and analytics in recent years, and it’s given fans a variety of new ways to measure an athlete’s skill, play, and success. But with traditional qualities like work ethic and compete level so difficult to quantify, are these numbers only telling part of the truth?

Win shares is a popular and common way of calculating the impact an athlete has on their team. While the term was first coined in 2002 by Bill James and Jim Henzler in their book about baseball, appropriately titled “Win Shares”, the concept has since expanded to basketball.

The metric uses a computer algorithm to estimate the number of wins a player produces for his team based on their yearly statistics. A high win shares number means a player adds value to their team and directly contributes to its wins, while a player with negative win shares performs so badly that they essentially take away wins that their teammates had generated. It calculates a player’s impact on their team, but does it give an accurate portrayal of the player as a whole? Can it allude to someone’s work ethic?

Malcolm Gladwell, a Canadian author and journalist, wrestled with this idea while giving a presentation on the impact of technology at Citrix Systems, Inc.’s 2017 Synergy conference, held in Orlando from May 23 to 26.

He compares the win shares of four players, all drafted in the top 20, who broke in to the NBA in the same 2010-11 season: Paul George (Indiana Pacers), Demarcus Cousins (New Orleans Pelicans), Eric Bledsoe (Phoenix Suns), and Gordon Hayward (Utah Jazz).

Malcolm Gladwell comparing the win shares of four NBA players at Citrix Synergy 2017, held in Orlando from May 23-25.

While it’s difficult to see the exact numbers in the picture from his presentation, it’s clear that the first three of the aforementioned players saw their highest win share numbers in their fourth year in the league, and subsequently declined from there. “Several factors likely contributed to this,” Gladwell points out, including physical prowess generally peaking at the age of 24 (the age all these players were in their fourth seasons), and signing new (very large) contracts in their third seasons, an achievement of stability which can often make a player complacent.

But in continuing to examine this small sample, Hayward is an obvious anomaly. His win shares steadily (albeit inconsistently) climb over the years and peak in the most recent 2016-17 season. Gladwell says that Hayward “beat the system” by not declining in his fourth season like the other players on the list.

When examining exactly how Hayward did this, Gladwell explains the player upheaved his old training regiment and implemented a completely new one that saw him waking up at 7:00 am for intense gym sessions followed by skills practice every day.

It was also widely reported that at the end of the 2015-16 season, Hayward reached out to basketball legend Kobe Bryant to see if he could mentor him on the art of the midrange shot, and ended up spending a week practicing with Bryant in Newport Beach, Calif.

“Instead [of declining in his fourth season], Hayward continued to improve his abilities through hard work and practice and got better over time,” Gladwell elaborates, adding that any coach or general manager would want these qualities in a player.

He argues that “statistics won’t show you what kind of person someone is or what their work ethic is like,” and that human judgment is needed to fill the holes computer algorithms leave.

“Any coach and general manager wants a highly motivated guy like that on their team, but how do you find such players?” Gladwell questions.

He says that while advanced statistics are valuable and can serve as the basis for judging a player’s skills and impact on a team, it can’t be the only metric. Analytics complement human interactions like player-manager interviews.

“Advanced technology clarifies what the role of humans ought to be moving forward. People have social abilities and will need to evolve into a more analytical, contextual position while tech does the work of collecting data,” Gladwell concludes.

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