Number crunchers rejoiced when bestselling-book-turned-Hollywood-movie Moneyball pulled back the curtain on a major league baseball team's use of undervalued analytics to identify players to covet. 

Since being pioneered by Oakland A's manager Billy Beane, the practice of selecting players based on once-overlooked data is no longer a novelty. 

UNC Professor of Sport & Exercise Science (SES) Bob Brustad attests to this.  A friend of his works with the Tampa Bay Rays, which now employs 11 full-time analytics gurus.

"Teams see the value in this approach," he says. "It drives every part of the decision-making process." 

In a way, Brustad is working on the next chapter of Moneyball. Brustad presented his initial findings at Major League Baseball's 2016 annual analytics conference. 

His presentation, focusing on talent-projection errors based on players' ages when they were drafted, led to at least three teams expressing interest in working with Brustad. 

"I believe the prediction equation we use in projecting talent is wrong — not fatally wrong, but it's distorted." Brustad said during his presentation. 

An aficionado of the game, Brustad wants to help teams project the success of players they're considering and seeks to improve sports at all levels for athletes coaches and families. 

Bear in Mind Podcast logoListen to the Bear in Mind Podcast, Episode 16 where Brustad discusses the advantages and disadvantages of specialization in youth sports.

Brustad reviewed widely available draft data of high school players from the first 20 rounds from 2005-12 to examine how age influences the probability of being selected in the draft. He expected to find that younger high school players might provide greater value in the long run. 

In his presentation at the MLB conference, two players drafted in 2007 served as Exhibit A and Exhibit B. The first, a 19-year-old "can't-miss prospect" who was drafted in the first round by the St. Louis Cardinals. And the second, an 18-year-old pitcher taken in the later rounds by the Colorado Rockies. 

The Cardinals' pick, Pete Kozma, was a top-20 prospect who played two years for St. Louis before being optioned to the minors. He spent the 2017 season as a backup infielder with the New York Yankees. 

On the other hand, the Rockies' pick, Chris Sale, received much less fanfare, ranking outside the top 1,000 prospects in the draft class. His fastball, a key measure teams use in draft analysis, reached 86 mph (over 8 mph below the average of a major-league pitcher). Brustad says that not only was Sale young for his age group, but he also had a less mature body type and he focused more on basketball in high school. After opting to go to college, he was re-drafted in 2010 by the Chicago White Sox as the 13th overall pick. Last year he made the All-Star team for the sixth time.

Sale clearly outperformed his talent projection from the 2007 draft, and Brustad says he's an example of the importance of taking growth and maturational development into analysis. 

"It's remarkable how much growth can take place between ages 17 and 18 years old," Brustad says. "The more specialized player looks better now, but he's closer to his ceiling. The players getting greater attention are more likely to be early maturers who have less growth potential.

Brustad discovered that many of the top 20 players in today's game were drafted as 17-year-olds. 

In general, Brustad's research shows that teams overvalue players' current ability. "It's a tendency we see across all sports that we make some fundamental errors in the talent evaluation process because we neglect the importance of age, maturity and practice," Brustad says. "We're missing a lot in terms of bringing in the maturational, learning characteristics into our projection system." 

Brustad wants to expand the draft analysis another five to 10 years and explore other related factors in a player's development. Specifically, he intends to focus on sport specialization and maturity. 

Already a consultant with the U.S. Olympic Committee and the Real Sociedad professional soccer team in Spain, Brustad could be helping an MLB team in the near future with his Moneyball 2.0 Approach.

What players will outperform their talent projection?

During his presentation at the major league baseball conference, Brustad said these are variables to consider based on the data he analyzed:

Physical Growth

"Players who are going to grow the most from the time they get drafted until they play at their major-league age," Brustad says. When a player reaches maximum rate of growth tells you a lot about growth potential past that point. Body type is also helpful in predicting ultimate growth. 

Learning

"Some players are simply going to learn more than others," Brustad says. "Learning corresponds a lot to practice history so the more quality practice a person has had, the less learning potential they have. The less specialized the athlete was at a younger age, the steeper the learning trajectory would logically be."

Growth Characteristics

"For pitchers what we want to see is...the physical development and change in the limb length in particular," Brustad says. "Players who have the greatest growth would be the ones who would seem to have the greatest potential for change over time." As for position players, "we're looking at power more than anything else...we're looking at strength"

Psychological Maturation 

"Some athletes are more capable of psychological regulation, in terms of emotion control, self-regulation, etc. than others," Brustad says. "That's going to play a role because baseball is a game of frustration...it's a very psychologically demanding process.