How Analytics is Influencing Player and Game Performance

We all know that analytics is playing a very big role in making correct decisions by taking data into consideration. Here we will discuss how analytics is playing a role in sports. Analytics in sports is divided into three broad areas. They are:

1. Analytics in player and game performance
2. Business Analytics in sports
3. Player health and injury analytics

These three areas are very broad in terms of their applications.  When it comes to analytics in player and game performance, focus will be on three crucial decisions that a team needs to take which are selecting the best possible players for a team, fielding the best possible teams on a given day and taking the best possible decisions on the court. Second major type of application in sports will revolve around business applications. They are analytics for ticket pricing, fan loyalty analysis, social media, and fan engagement. The third and final major type of application in sports deals with predicting the injury of the players in advance so that substitutes can be planned in advance.

So, in this blog, I want to touch upon how analytics is playing a role in analysing the player and game performance. I will take three major games where this type of analytics is implemented and will discuss how they are implementing. So, three major games that I want to touch upon in this blog are:

1. Baseball
2. Football
3. Cricket

Player and game performance analytics in Baseball: 

Baseball is a game where lot of stats and data are produced for each game. There is a separate field of study called “Sabermetrics” exclusively for studying baseball and for development of analytical tools and techniques.  If you have seen the movie ‘Moneyball”  you would get an idea how Oakland A’s team in Major League Baseball (MLB) has used analytics to draft players on the basis of proven performance particularly how players are getting on base. In baseball, analytics employs recently developed individual hitting metrics like on-base percentage, sluggish percentage, runs created etc. It also employs individual pitching metrics like true runs allowed, value over replacement pitcher etc and fielding metrics like number of defensive runs saved.

Most of the baseball teams in MLB (Major League Baseball) in U.S.A are using these techniques but the differentiating factor among all these teams is that how these teams would come up with new approaches and insights. In most of the cases, teams use widely available data that is provided by their league or by commercial firms that produce or sell the data. But one of the teams in MLB went one-step head to collect the proprietary data about its players. The San Fransisco giants MLB team was the first team to adopt the video data from sports vision and it has gathered its own proprietary data about its own players for several years before other teams has developed the tools to follow this approach. It has also developed the metric where it can measure the expected value of each player.

Player and game performance analytics in football:

Player and game performance analytics in football is less sophisticated when compared to baseball. This is because of the complex interaction of players while playing the football and also it is difficult to rate each player who is playing in different positions in each game. Also, football coaching is conservative which means that there is a little demand for player and game performance analytics. If you take professional soccer, their primary focus is on descriptive statistics with emphasis on diagnosis or prediction. Teams are mainly focussing on what has happened instead of why it has happened or what might happen next.

For example in U.S.A, Major League soccer (MLS) league is mainly focussing on business and marketing analytics while player and game performance analytics is left to participating teams. Some European teams such as Manchester united are advanced in terms of performance analysis and they have also made available the data to the fans so that they can analyse the data. In Soccer, evaluating the player’s propensity to score is difficult because of the low scoring in most of the matches. Tactical factors such as possession, number of passes, and the territory played, which lead to the scoring of goals, are considered while evaluating the team’s performance.

Now a days, teams are also using devices like GPS, Accelometers, RFID’s in order to evaluate the total activity like miles or Kilo-meters run, average speed etc. Even recently, Adidas has come up with its Micoach cell where it is inserted into the shoes of the players to assess the fitness levels of the players.The feedback from MiCoach is the most vital tool since team physicians can sit sideline to monitor players’ stamina and evaluate if they are getting fatigued in order to plan a substitute.

Player and game performance analytics in cricket:

Analytics is playing a very big role and also has a very big role to play in cricket. Cricket is a game where lot of data is generated per game. So, Analysts can play with that data and can come up with many insights. I will discuss an example here to show the importance of player and game performance analytics in cricket. This involves the rise of England cricket team to number one position in test rankings when they were languishing just above Bangladesh (rank 8) in test rankings.

When Andrew Strauss took England’s captaincy he has a vision to make the England team number one in test rankings. Data has played a key role in achieving their vision. They had analysed the teams that they need to play with and analysed opposition team’s strengths and weaknesses through rigorous analysis of their scoring patterns, how they scored their runs, when they were vulnerable during innings. They identify the players who are having the skills to defeat those opponents in different conditions. They made sure that they had a clear plan for each day, each session. All these things have been done with the help of data and its analysis. This one example is enough to show the power of analytics in cricket.

Now Analytics is also being employed in IPL. Recently, KKR has taken the help of SAP during player auctions to select the best player for its team.