Difference between revisions of "Sports analytics"

Revision as of 16:51, 24 January 2023

Sports analytics are a collection of statistics or biometric data that can provide a team or individual a competitive advantage. Through the collection, refinement, and analysis of data, coaches and other staff members are able to inform athletes about their performance in order to assist decision making both during and prior to sporting events. The term "sports analytics" was popularized by the 2011 film, Moneyball, in which Oakland Athletics General Manager Billy Beane (played by Brad Pitt) relies heavily on the use of player analytics to build a competitive MLB team on a limited budget.

There are two main types of sports analytics - on-field analytics and off-field analytics. On-field analytics involves tracking key on-field metrics that may influence an athlete's methodologies and in-game strategy. It also involves tracking an athlete's biometric data and vitals to influence their training or performance levels. Off-field analytics deals with the business side of sports. It handles monitoring key off-field metrics like ticket sales, merchandise sales, and fan engagement. Essentially, it provides shareholders with information that would lead to higher growth and profits.

Sports analytics have also had a significant impact on Online Sports Betting as bettors now have access to more information to aid decision making. New avenues of gambling, like parlays and fantasy leagues have lead to the rise of new analytical tools. For example, companies and webpages can now provide fans with up to the minute information for their betting needs.

Sport-specific analytics

Major League Baseball (MLB)

Sports analytics in baseball, also known as sabermetrics, is the application of statistical analysis to baseball in order to measure in-game activity. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research, founded in 1971. The field was popularized by Bill James in the 1980s and has since been used by many major league baseball teams to assist in decision making. Sabermetrics can be used to measure a player's performance, a team's performance, and even the performance of individual pitches. It can also be used to make predictions about future performance and to identify undervalued players. Some common statistics that have become vital to the game include:

• Batting average, also known as "average," is a statistic in baseball that measures a batter's performance by dividing the number of hits by the number of at-bats. It is typically expressed as a decimal to three decimal places (e.g. .300). A high batting average is considered an indicator of a good batter, as it means they are getting a hit more often than not. However, it doesn't take into account other important aspects of hitting such as power and plate discipline.

• On-base percentage (OBP) is a statistic that measures how often a batter reaches base safely, regardless of how they reached base. It is calculated by adding the number of times a batter gets a hit, walks, or is hit by a pitch and dividing by the number of plate appearances. OBP is considered a more comprehensive measure of a batter's performance than batting average as it takes into account walks and hit by pitches, which are important indicators of a batter's plate discipline.

• Slugging average (SLG) is a statistic that measures the power of a batter. It is calculated by dividing the total number of bases (singles, doubles, triples, and home runs) by the number of at-bats. SLG is considered a more comprehensive measure of a batter's power than home runs alone, as it takes into account extra base hits like doubles and triples.

• Walks plus Hits per Inning Pitched (WHIP) is a statistic that measures the number of baserunners allowed by a pitcher per inning pitched. It is calculated by adding the number of walks and hits allowed and dividing by the number of innings pitched. WHIP is considered a measure of a pitcher's ability to limit baserunners and prevent runs from scoring. A low WHIP is generally considered a good indicator of a strong pitcher.

Some traditional analysts believe that teams are becoming too reliant on statistics, but many teams continue to use these statistics in combination to evaluate the performance of players and make decisions about lineup construction, player acquisition, and contract negotiations.

National Basketball Association (NBA)

The field of basketball analytics has grown in popularity in recent years, with many teams in the NBA utilizing advanced statistical methods to assist in decision making. The use of analytics in basketball is based on the idea that traditional basketball statistics, such as points, assists, and rebounds, do not fully capture a player's or team's performance. Analytical metrics such as player efficiency rating (PER), win shares, and plus-minus are used to measure a player's or team's overall performance and contributions to winning.

One of the most well-known and widely used analytical metrics in the NBA is player efficiency rating (PER), which was developed by John Hollinger. PER is a per-minute statistic that adjusts for pace and measures a player's overall efficiency by combining several different statistics such as points, rebounds, assists, steals, and blocks. Another popular metric is win shares, which is used to estimate the number of wins contributed by a player. Plus-minus, which measures the point differential when a player is on the court, is also commonly used in the NBA to evaluate player performance.

The use of analytics in the NBA has sparked debate among traditional basketball analysts and coaches. Some argue that advanced metrics do not fully capture the nuances of the game and that they are over-relied upon. However, many teams have found that incorporating analytics into their decision-making process has been beneficial in player evaluation and strategy. The NBA has also embraced this trend by creating a player tracking system that captures data on the players' movements on the court, which can be used for analysis.

National Football League (NFL)

National Hockey League (NHL)

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