Team Sports Economics - Essay Example

TEAM SPORT ECONOMICS By (fore and then sur Essay Question: Critically evaluate the application of variants of ‘saber-metrics’ in professional ‘invasion’ sports. Illustrate your answer with reference to its uses in these sports? Seminar tutor Name: I confirm that this submission is all my own work. Any quotations are properly cited using the Harvard referencing method. All errors and omission are my responsibility alone.” Name ________________________­_Dated__________________ Word Count Figure:1550 Sabermetrics is the use of statistics in measuring the in-game activity of the players (Gallian, 2010). The term sabermetrics originates from the acronym SABR which stands for Society for American Baseball Research. SABR is the one that pioneered the use of statistics in evaluating a game and its players. Traditionally the baseball players were gauged in terms of the battling average, the number of strikeouts and the opinions of the scouts, who spend most time with these players. This resulted to a highly inaccurate and inefficient system of determining player performance. This led to the innovation of sabermetrics and its usage. It has been applied to various invasion sports, more so the baseball. In other sports, the Sabermetrics analysis has encountered many problems. However, Sabermetrics is a good thing since it has many applications in this world of invasion sport (Costa and Huber et al., 2008). Sabermetrics has contributed positively not only to the baseball games but also to other invasion team sports. For example, years ago baseball on of the invasion sport was treated as an art and a romantic sport. It wasn’t a sport that was supposed to have statistical analysis and mathematical computation. That is, until 2002 when Oakland Athletics started winning games. The Athletics had found out that it could be more efficient by having players that know how to get on base. This would lead to runs that would make them win. The sabermetrics help in determining the On-base-percentage, which measures how often a player gets on the base (Costa and Huber et al., 2009). The use of sabermetrics has been also employed in other sports, as well. For example, in basketball it has been used in determining the player development process. It has developed APBRmetrics that are similar to Sabermetrics that focuses on the analysis of basketball through objective evidence. To analyze the plays of basketball, a network analysis is done which turns teammates into nodes and exchanges passes into paths. After which a flowchart is created that shows the ball movement as passes are made (Fewell and Armbruster et al., 2012, p. e47445). From the analysis done, teams then improve on their distribution of the ball and takes paths that can ensure that they win. Sabermetrics assists in determining advanced basketball statics which include: offensive rating, effective field-goal percentage, true shooting percentage, rebound rate, player efficiency rating, possession analysis and Pythagorean record. This has enabled teams to use sabermetrics to help them in winning games. Fans have also appreciated the game on different levels. This has resulted to them praising the contribution of even the undervalued players. Sabermetrics gives information that the traditional methods did not give to the coach. For example, in baseball the coach missed statistics such as Defense Independent Pitching Statistics (DIPS) which help in measuring a pitcher’s effectiveness based on only plays. In addition, it also measures the Value Over Replacement Player (VORP) which determines how much a player contributes to the team in comparison to a fictitious replacement player. Coaches have now more information about players that can help them in making right decisions that can help the team win. In football, sabermetrics has received huge criticism that has made it difficult for clubs to use them fully. This is due to the many variables that exist in football. In addition, there are many styles of play and many cultures involved. This has made it difficult to rate players merely on statistics. Moreover, it is difficult to use statistical analysis to evaluate a player’s character. However, sabermetrics is slowly being adopted into football. For instance, field position analysis helps in determining the best place that a player can easily score from. In cricket, has adopted the use of sabermetrics. Traditionally it relied on the player’s percentage of the team runs alone to measure the player value. However, sabermetrics has enabled teams to measure scoring-shot percentage, batsman’s length footwork analysis and the player’s percentage of the team runs. They give more information about a player that will help a manager choose the best team. Sabermetrics has offered many benefits to the teams that use them. It has enabled the teams to determine the knowledge and skills of their opponents, and use the information to devise ways of overcoming them. In addition, it has helped the teams in selecting the best teams that can win any game based on the statistics carried out. Sabermetrics is used in forecasting the future performance of a player from past performances. While battling average and the average earned run were traditionally used, sabermetrics has better predictors of the player’s future contribution to the overall team performance. With sabermetrics in place, certain in-game decisions are discouraged. The managers now can make right decisions based on various analysis conducted on of the players. This allows the manager to choose the best team that can win the match based on the strengths each one has. In addition, it helps the manager in retaining the players he deems to be still valuable in the future. Through the use of metric analysis projections can be made, to determine the best players in the future. This allows the manager to retain the players who have experience and skills that can make the team succeed in the future. This offers additional features that are more accurate than the traditional way of evaluating the performance of players. Consequently, sabermetrics is used by the human resource (HR) managers of this teams. For example, in the baseball game it has been used by managers to make strategic decisions in terms of human capital management. First, it has enabled firms to develop a competitive strategy. Having a competitive strategy is one way of having an edge over the competitors. Second, it has enabled the firms to hire individuals who can execute the team’s strategy. The individual should possess certain knowledge, skills and abilities. Sabermetrics pays attention to the knowledge, skills and abilities and then assesses those characteristics. It enables the HR to achieve a higher team performance. The use of sabermetrics provides a team ability to attract quality players at a lower cost compared to that of the market. This provides the team a competitive advantage over its competitors. The HR managers have a detailed database at their disposal, thanks to the innovation of the sabermetrics in invasion sports. This database contains information about many players that also has analysis of their past records. This helps the human resource managers to make right hiring decisions. It helps them determine the best players they can introduce into the team that has the experience and skills that they need in the team. Team performance is improved by introducing a player that has skills and attributes that the team does not currently have. The success of the team is assured when managers use sabermetrics when hiring players. Moreover, it has helped teams save money. The human resource managers traditionally spent a lot of money when it comes to hiring players. But with the introduction of the sabermetrics to the invasion sports, it has helped them to choose relatively best players who are lowly priced in the market. Consequently, sabermetrics has provided a market for players’ salaries. For instance, the Major League Baseball (MLB) has turned out to be a market for player salaries. The price theory establishes a strong correlation between the player attributes and the salary they get, in a perfect market information and competition. MLB contains a database of various metrics about various players. It has both the player’s contract data and the player’s statistics using Stata. This has resulted in players not willing not to sign for long term contracts in their teams, hoping to get a salary increase by changing teams. A player whose performance increases may want to change teams to attract high salaries. This is because his value in the market has changed and by changing teams his salary will be raised to match his skills and experience. This has made the free agents learn sabermetrics so that they can negotiate well for their clients (Costa and Huber et al., 2008). However, managers have realized on how to retain the players. They use the metric analysis to determine the progression of players, and award the players a price increase as they improve. Players feel they are appreciated and they remain in the team. The team can sustain its good performance if it retains its best players. Sabermetrics has also shaped the way players are priced in the market. The players with strong skills and experience attract a higher price since many teams want to hire them. This market also demonstrates the demand theory that states that when demand is too high price increases. Teams always would want to go for the best players. Therefore, the demand for high performance players makes their price compared to low performance players. Sabermetrics has contributed to the success of other invasion team sports other than the intended baseball sport. They have been adopted by basketball teams, cricket teams and even football teams. They have enabled teams to hire high performance players. In addition, they have enabled team managers to pick out the best teams that can win a particular game. Moreover, they have enabled teams to save by hiring high performance players at a low cost. References Costa, G. B., Huber, M. R. and Saccoman, J. T. 2008. Understanding sabermetrics. Jefferson, N.C.: McFarland & Co. Costa, G. B., Huber, M. R. and Saccoman, J. T. 2009. Practicing sabermetrics. Jefferson, N.C.: McFarland & Co. Estes, B. C. and Shaheen, N. A. 2010. Determinants of value and productivity in a complex labor market: How sabermetrics and statistical innovation changed the business of professional baseball. BUS. STUD. J.(SPECIAL ISSUE), 2 pp. 27--31. Gallian, J. A. 2010. Mathematics and sports. [Washington, DC]: Mathematical Association of America. Mcgarry, T., Odonoghue, P. and Sampaio, A. J. D. E. 2013. Routledge handbook of sports performance analysis. Abingdon, Oxon: Taylor and Francis. Fewell, J., Armbruster, D., Ingraham, J., Petersen, A. and Waters, J. 2012. Basketball Teams as Strategic Networks. 7 (11), p. e47445. Available from: doi: 10.1371/journal.pone.0047445. Read More