While many are quick to exclude the Sports industry from the category of ‘business’, sports provide a steady revenue for this country which comes from many businesses that have been established in an effort to economize and gain profit from games. Businesses surrounding the industry include betting and gambling businesses, as well as the major businesses such as Major League Baseball or National Football League. The major leagues, clubs, betting houses, as well as TV and Media companies are all driven by money, and a large part of the revenue is made is from televised sports. These businesses rely on Decision Support systems in order to continue to thrive. Decision Support Systems are useful when “the amount of available information is prohibitive for the intuition of an unaided human decision maker and in which precision and optimally are of importance” [3]. In sports, revenue is made when the right decisions are made. This includes using computer models to determine the weather or what type of referee would be optimal for the specific game.
One example of a using DSS in the sports industry is deciding if weather conditions are safe to play in or not. According to the Journal of Computing, “DSS can be implemented through a number of algorithms based on the attributes…attributes that include outlook, temperature, humidity and wind” [1]. These attributes are important to note in a game when taking into account if a ball can fly through the air, if the players can run from base to base freely, or if rain will potentially cause injuries to the players. These factors are all important for the MLB or NFL when determine if games can be continued or played at all, factors that could cause major lawsuits or injuries if the wrong call is made. In addition, if you are in the booking business, knowing how the weather affects a players or teams ability to play is an important factor when making bets. A major DSS used to determine weather interference is the ID3 algorithm, which uses example weather and field conditions. The user inputs the current weather situation and based on previous instances, the program determines if the game should be played or not. This provides leagues and clubs to determine if the games can be played. It is important for this program to be accurate because its accuracy determines the safety and well-being of the players, as well as the onlookers.
Another very important aspect of the sports industry that involved DSS is deciding the ideal way to referee a game. This can be very important to businesses because a bad call can cost a better his or her money, or the major corporations could lose money if referee decision accuracy is off. In a thesis written by colleagues at George Mason University, it estimated that “on average there are 627 decisions made by a referee per a 90 minute game…an analysis of 143 rules of the game was categorized by importance to the outcome of the game and frequency” [2]. With teams and players playing faster and harder than ever before, the need for better referees is required to continue to fulfill the requirements of the games. Three decision systems are typically used for up to date referees, which includes SkyCams which hover around the filed, two official referees on the field, and Segways which allow referees to increase their speed. The three decision systems are chosen based on accuracy ratings based on game simulations. A decision system is picked based on its ability to satisfy the needs of the game. This is an important task based on the importance of sportsmanship and fairness, two imperative aspects to games.