Sports Analytics: What It Is, How It’s Used

For a long time in sports, data analysts were kept at arm’s length by coaches and front offices. But today, it’s not uncommon for data analysts to populate sports staffs. As athletes and managers seek any statistical edge they can find, the role of sports analytics only seems to be growing.

The sports analytics industry is on track to surpass $31 billion by 2034, and for good reason. Professional sports leagues and sports betting companies have bought into the sports analytics hype, forever altering the experiences of professional athletes and casual fans alike. 

What Is Sports Analytics?

Sports analytics uses data to measure areas like athletic performance and business health to optimize the processes and success of a sports organization as a whole. On-field data metrics help teams decide how to improve in-game strategies, nutrition plans and other methods for raising their athletes’ level of performance. Off the field, organizations can leverage data to monitor ticket sales, craft marketing campaigns and reduce operational costs.

Besides professional teams, betting companies and fans have also joined the action. Sports betting analytics groups rely on data to determine the odds of certain game results happening. Fans then consider these odds when placing bets, selecting players for a fantasy team and making other decisions that depend on statistical data. 

How Is Sports Analytics Useful?

Data and statistics play a huge role in both collegiate and professional sports. From historical data and fundamental scorekeeping to algorithmic performance forecasting and extremely specific player statistics, big data is the industry’s most valuable player.

Data lets teams and organizations track performance, make predictions and make smarter decisions on the field. Want to figure out what play is best to run on fourth down in a football game? Check the analytics. Wondering whether or not your pitcher should throw another inning? Check the analytics. Players still win games, but data allows coaches to put them in the best position to succeed.

Analytics influences how fans consume sports, too. Sports analysts, commentators and fans use data constantly — whether it’s to provide play-by-play explanations, discuss predictions or power fantasy league decisions.

The Role of Analytics in Sports

General managers and coaches have long evaluated players based on a mix of stats — things like points, batting average or yards thrown — as well as their own instincts and subjective judgment. When it came to deeper data analysis, however, they were more skeptical. Until recently.

Early statisticians, like Bill James, challenged those subjective assumptions with data in the 1980s. James came up with a mathematical system to evaluate baseball players called sabermetrics, which he released to the public in a book titled The Bill James Historical Baseball Abstract. In it, he created equations like “runs created” that factored in a baseball team’s offensive stats to predict how many runs they’d likely score. It was his first stab at a way to objectively analyze players and help general managers optimize their teams, according to the Society for American Baseball Research.  

Sports analytics didn’t truly take off until 2002, when Oakland Athletics general Billy Beane relied on it to put together a team of lesser-known players that nearly won a World Series. His strategy of optimizing a team through statistical analysis became known as “Moneyball” and quickly became the way other teams operated.

Tracking software and machine learning have taken sports analytics to the next level. Companies are able to generate statistical breakdowns from video footage to help coaches optimize their play calling during games or generate post-game takeaways. Others use cameras and machine learning software to track things like ball speeds, spin rates and player movement, which regularly factor into both broadcasts and team decisions. Baseball players, for example, are regularly seen using tablets to review data like pitch distributions to make adjustments mid-game. 

Analytics have also shaped the way fans consume sports. Fans can hop over to websites for data-based sports coverage and their favorite team’s odds to win a championship. Broadcast announcers regularly break down a player’s breakaway speed in football or launch angle after a home run in baseball. It’s even a staple in projecting the best players in fantasy sports.

Sports analytics’ move from the bench to a starting role was a long time coming, and it doesn’t look to be relinquishing its spot anytime soon.

How Is Sports Analytics Used in Different Sports?

Each major sport has had its own analytics evolution, with teams hiring data scientists and seeking ways to objectively analyze players and gain a statistical edge. Here are a few examples of how sports analytics continues to reshape professional sports.

Baseball

The rise of sabermetrics and Moneyball has forced baseball clubs to address tough questions like, “What makes a player valuable to his team?” In response, teams have begun to track a wider range of statistics, including batting average, weighted on-base average and weighted runs created plus. These categories help determine how players can make the biggest impact on a game, influencing in-game strategies and how baseball managers construct entire rosters.  

Basketball

National Basketball Association (NBA) teams use a slate of data points collected from wearables, saliva samples and other methods. This data delivers a detailed profile of each player, informing coaches when it’s best to rest players and keep them healthy for the postseason. The NBA also experienced its own Moneyball in the form of “Moreyball,” which has led teams to optimize their offenses for three-pointers and layups because shot chart analysis showed them to be the most efficient shots in the game.

Football

As of 2021, all 32 National Football League (NFL) teams have partnered with Catapult, a provider of athlete management solutions. The company’s wearable vests enable teams to better evaluate player performance, track fatigue and take proactive measures to avoid injuries and wear and tear. In addition, Catapult’s video analysis platform lets a coaching staff view games from a bird’s-eye view, so they can further assess players and inform their strategies moving forward.

Soccer

Soccer analytics took a leap forward with the introduction of possession value, a stat that gauges how a player’s actions increase or decrease their team’s chances of scoring. As a result, a midfielder completing a dangerous pass through the defensive backline carries much more weight than a defender simply making a short pass to another defender. Leagues like Major League Soccer (MLS) have since refined the ways they measure player performance, taking into account other variables like player expected goals and goalkeeper expected goals.

What Does a Sports Analyst Do?

The term ‘sports analyst’ applies to a broad category of professionals, from more traditional sports commentators to more data-heavy analysts.  

Sports commentators sit in the booth at sports events and serve as the voices fans hear on TV or the radio. These professionals keep track of the action and quickly analyze stats and visuals, providing play-by-play commentary, scrutinizing coaching strategies, assessing player performances and delivering other thoughtful insights. This way, fans can gain more context and feel more engaged without being at the game.

Another form of sports analysts is sports journalists and writers. As members of the media, these professionals conduct interviews with coaches and players, compile statistics and write reports and articles using these statistics and their own observations at sporting events. These sports analysts often break the latest news to fans who weren’t able to attend or watch the game, keeping fans and stakeholders updated. 

More recently, the field has expanded to include data-focused sports analysts. These types of analysts leverage techniques like machine learning and data mining to analyze player performances and gather other advanced statistics. Sports organizations can then use these data points to adjust their strategies, tweak their rosters and make any coaching changes. Sports betting companies may also employ these individuals to improve the accuracy of their predictions and help bettors make more informed decisions.

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