Examples Of Bias In Sports

Sports are rooted in tradition and many fans develop their beliefs based off their own biases and preconceived notions. Examples of bias exist in each sport: Bud Selig has called the Oakland A’s success “an aberration”, walks were an irrelevant statistic in baseball for over 100 years because of one statistician’s opinion, and an ESPN author once ran an article titled “Wisconsin: The Most Boring Team in America.” Throughout the history of sports, coaches and managers have been trying to find inefficiencies and rethink the way their game is played. When resources run low or tradition doesn’t exist, those in charge need to have a willingness to reconsider their sport: how it is managed, how it is played, who is best suited to play it, and why.

In 1977, Bill James wrote his first of multiple books devoted towards baseball history and statistics.

James’ approach was to develop a statistical scientific method that would analyze and study why teams win and lose. Eventually, James would create Sabermetrics. James defined Sabermetrics as “the search for objective knowledge in baseball.” In other words, Sabermetrics tries to answer objective questions about baseball, such as “which player on the Brewers contributed the most to the team’s offense?” Sabremetrics does not deal with subjective judgments, such as “Who is your favorite player?” (Lahman). Through the development of Sabermetrics, James’ found that there were numerous miscalculations of a person's value in

baseball.
In 1999, the Oakland A’s were the second poorest team in baseball, and the margin between the A’s and the big market teams such as the Yankees was continuing to grow. Billy Beane understood that the Oakland A’s would never have the money or appeal that the New York Yankees had, and he proceeded to look for new ways to compete. Paul Depotesta a Harvard graduate with a degree in economics was brought in by Billy Beane to contradict old fashioned scouts with Sabermetrics. Depotesta wanted to find statistics that allowed you to look past the observation-based scouting practices that were currently in use. Observation-based scouting led to prejudices against players with certain body types or playing styles.
In 2002, the Oakland A’s payroll was around $40 million. While big market teams such as the Yankees had over $100 million to sign all-star players in free agency, Billy Beane had to look for undervalued players in order to stay competitive. Many of these players had physical or performance flaws such as Jeremy Brown, a catcher from the University of Alabama. Brown was the only player in the history of the SEC with three hundred hits and two hundred walks, yet because he was overweight, conventional wisdom told every other general manager not to take him anywhere before the 20th round. Billy Beane selected Brown with a first round pick- 35th overall in the 2002 draft.
Relying on Sabremetrics, Billy Beane took players such as Brown in earlier rounds to get them at a fraction of their actual worth and stay within his budget. In order to say competitive now and in the future, Beane orchestrated a system of producing young star players and retaining them until the end of their contracts. When Johnny Damon, Jason Giambi and Barry Zito left, the A’s would get several high draft picks to restock their farm system. In the meantime, Beane would use Sabermetrics to find players past their prime like David Justice or no-name players such as Scott Hatteburg to fill the statistical void left behind. After losing Jason Giambi to the Yankees, in 2002 the A’s had another outstanding season and won one more game than the previous year with nearly one-fourth of the Yankees budget. Billy Beane’s outside of the box approach paid off in a way that many never could’ve even imagined.
Wisconsin Basketballs recent success draws a lot of parallels with both the Oakland A’s and Sabermetrics. In between 1947-1994, the Badgers did not make the NCAA tournament. The program arguably became relevant again in 2000, when Dick Bennett coached the Badgers to the Final Four. Bennet however, only coached another year before stepping down. One season later, Bo Ryan took over the helm for the Wisconsin Badgers and has since accomplished many feats.
When Ryan came to Wisconsin for the 2001 season, he adopted sets of basketball analytics and applied them each year. Ryan’s system relied on points per possession and limiting turnovers. For years, commentators used their observation-based viewpoint to call Wisconsin Basketball “boring.” However, Ryan was actually just ahead of the game when it came to Basketball offensive efficiency. In an interview with Big Ten Network’s Dave Revsine, Ryan said “Just so you know, I was using this when I coached in high school in the '70s, the points per possession and offensive efficiency. So I've used that stat for 40-something years.” With Ryan’s focus on offensive efficiency ratings, his teams have been able to have continuous success because of their systems ability to limit mistakes and work for smart, high percentage shots.
Recruiting has always been expensive in college sports. For most of Bo Ryan’s tenure and in 2013-14, the Wisconsin Badgers had by far the lowest recruiting expenses in the Big Ten conference at just $62,082. Ultimately, Bo Ryan just hasn’t been able to convince many four or five stars recruits to come to Wisconsin. Instead, Bo has had to find players who were often overlooked or underrated to fit into his meticulous “Swing” offense such as Frank Kaminsky; a three star recruit with only a handful of offers who would later become the Naismith Award winner in 2015. In 2014-2015, Bo defied a lot of critics who accused Wisconsin’s style of play as “boring” when they also became the most efficient offense in college basketball history.
Within sports, many coaches and managers have had to find inefficiencies and rethink the way their game is played. While subjective judgements may be more interesting or easier for fans to understand, objective judgements provide a clear correlation between winning and statistics in many sports. In the end, Moneyball exhibits that observation-based judgements often lead to biases against players or playing styles with little or no sound reasoning.