Below is a final paper submitted and revised by Jonathan Safir for his Approaches to Media Studies class at Vassar College. Thought it was applicable enough to post.
Media and Technology Transforming Sports: The Statistical Revolution in Basketball and the Change in Spectatorship
The way in which humans view sporting events has changed drastically over the course of time. More specifically, Generation Y watches a game differently than the Baby Boomers. At its core, how we use the phrase “watching the game” means the same today as it did 50 years ago. However, as it is more critically analyzed, many different people can be watching for many different parts or subtleties of the game. As a diehard fan, one can watch hours on hours of games for pure entertainment. As a coach, one can break down each part of the game and create endless hours of film to watch and learn from. As more and more information becomes available, coaches can watch games to track various statistics that are used to create a more sophisticated and enhanced scouting report. This has created a rift in which watching games is no longer a necessity. With access to websites like www.kenpom.com and www.mysynergysports.com, basketball coaches have alternative ways of analyzing film, footage, and accessing statistical data. Advancements in media and technological capabilities have played a monumental role in how statistics are not only measured but also utilized in the game of basketball.
Dean Oliver is a basketball analytics pioneer. His book, Basketball on Paper (2004), is considered the Holy Grail of the statistical revolution that has recently occurred in basketball. Oliver was the first person to attempt to use statistics and analytics in the most beneficial and efficient way possible for all interested parties. He saw the success baseball teams had achieved using statistical analysis as dramatized in Michael Lewis’ work of creative fiction in Moneyball (2003), and was determined to bring these transferable concepts to basketball. In 2004, he released his book, which has revolutionized basketball in every measure imaginable. He created a term, the four factors, and emphasized them as the fundamental components to winning a basketball game. Those four factors are: Effective Field Goal Percentage (EFG), Offensive Rebounding Percentage (Oreb%), Turnovers per Possession, and Free Throws Made per Field Goal Attempted. Oliver summarizes his thought process, leaving no room for interpretation through his narration:
There really is nothing else in the game. These four responsibilities on the offensive side and these four responsibilities on the defensive side are it. If you aren’t shooting from the field, you better be doing a few of the other three things. If you don’t have the size to get defensive rebounds, you better force turnovers. If you can’t take care of the ball very well, you better get shots up before you turn it over, then go after the boards (Oliver, 63).
Oliver discovered that teams which excel at these four aspects of the game have a much higher likelihood of being a successful basketball team. Oliver’s work also focused on possession-based analysis utilizing offensive and defensive ratings. Oliver led to the creation of statistics such as: the four factors, ORtg (extremely complex offensive rating), DRtg (extremely complex defensive rating), and TS% (True Shooting percentage). His book also touches on performance analysis and how statistical variance and regression play a role in the win-loss record of a team, and the difficulty that is judging an individual player’s value to their respective team. Basketball on Paper was a decisive intervention in creating the power and appreciation of statistics that the prominent figures in college basketball currently employ.Inspired by Oliver, Ken Pomeroy decided to construct his own website tracking advanced statistics. Pomeroy created a website called www.kenpom.com. KenPom has become the go-to place for all tempo-free statistics. Pomeroy’s computer program creates an objective ranking system that avoids human bias and is able to “watch” every game. College basketball coaches across the country use his website to aid with their scouting reports. In my phone interview last week with Adam Cohen, previously Head Video Coordinator and Director of Basketball Operations at the University of Southern California and now Assistant Coach at Rice University, he discussed in great detail how his staff uses the technology and resources that are available. He remarked that “we start every scouting report on a website created by some meteorologist in the middle of nowhere (the running joke on Pomeroy since his day job is a meteorologist), we use this information to devise a basic plan of what defensive strategy to employ and if we want to push the pace or slow the game down.” Cohen and Southern California certainly aren’t the only coaches who try and get ahead of the competition by taking advantage of the available resources as they know that KenPom’s statistical analysis exceeds human perception by finding stats not previously detected/utilized. As a popular New York Times article demonstrates, the prevalence of KenPom continues to rise. For the average person, take one glance at www.kenpom.com and the information there will seem illegible. The website has data dating back to the 2003 season (2003 was done retroactively and there are no individual statistics for players, the first full season was 2004). The home page ranks the teams with the complicated Pythagorean Rating (using a log5 formula), adjusted offensive and defensive efficiency, adjusted tempo, and strength of schedule statistics. With just one click, a user can access an entire team’s year long schedule, a scouting report both offensively and defensively with statistics ranging from the four factors to the average height of the starting five. Scroll down that page and there are individual statistics for every noteworthy contributor. From how many fouls a player draws per 40 minutes, to their percentage of minutes played. With a second click, a person can find specific game by game breakdowns of how the team did in the four factors offensively and defensively.
The ability to track and synthesize this data seemed unimaginable ten years ago, now coaches constantly seek these breakthrough statistics to help their teams win. However, it is not just coaches who have been affected by this statistical revolution. As Pomeroy’s site tracks and utilizes information from every game being played, it is essentially “watching” the games for the coaches who just need a quick synopsis of a certain game. The work of Oliver and Pomeroy have changed how humans watch all sporting events, but the algorithmic nature of their work transcends fields in the workplace. As Manovich says in his Database article:
Any process or task is reduced to an algorithm, a final sequence of simple operations from which a computer can execute to accomplish a simple task. and any object in the world- be it the population of a city, or the weather over the course of a century, a chair, a human brain- is modeled as a data structure (Manovich, The Database Logic).
This fascinating insight leads to a question that seemingly sounded ridiculous, but now is frequently echoed: are watching games even necessary anymore? The term “watching” can be different to everyone. A fan watches games for different reasons than a coach looking to scout opposing tendencies. Spectatorship has changed accordingly. Other than being a loyal fan or for pure entertainment purposes, there are no reasons for coaches or scouts to watch full games. During the time it takes to watch a full game in which a player will only be involved in part of the action, scouts can access Synergy and chop up hundreds of clips of specific moves a player makes. Coaches who are scouting potential players for their team may want to view an entire game to try and detect certain intangibles. However, in this new era, intangibles are becoming more and more like null sets in databases. With the rise of agents, advertisements and marketing expertise, it is difficult to gauge a player’s character and intangibles without actually knowing that individual player. Unless a player has noted off-court incidents, all a team seemingly cares about is their basketball ability because their character cannot be quantified.
With social media interactions, the NBA has created a successful strategy to increase the marketability of their star athletes by capitalizing on the immediacy of today’s era. The unique nature of this concept enables fans to identify with that player, generating more revenue for the team. This star power has also led to others trying to emulate and failing miserably. As a recent Grantland article discusses, time will only tell how accomplished Harrison Barnes becomes at the NBA level. However, as the nation’s top ranked recruit coming into college and attending the University of North Carolina at Chapel Hill, Barnes set the standards too high for himself leading to be described by the media as a failure at the college level. In a video conference to announce his college decision, Barnes began the statement by saying “The place where I will leave my legacy...,” as Barnes never got to a Final Four nor won a Player of the Year award, those words will forever live in infamy. Barnes has attempted to create a brand for himself before his basketball career has ever gone anywhere, taking the opposite approach than the likes of Kobe Bryant and LeBron James, both of which have created an astonishingly successful off court brand after achieving tremendous on court success. For basketball players approximately 25 years old and under, they are entering an era that is entirely different than any that has preceded them. This unknown will make players like Harrison Barnes and Kevin Durant pioneers, but will also put them constantly in the spotlight, potentially before they have achieved any basketball acumen.
The statistical revolution has created a meta gaming effect on the game of basketball. Similar to Moneyball, more and more decisions are being made from an objective standpoint compared to earlier days where likability and less efficient measures of production played a more prominent role, proving the merits of these newer statistics that were once considered unconventional. As Manovich writes, “In computer programming, data structures and algorithms need each other; they are equally important for a program to work” (Manovich, The Database Logic). In discussing computer programming, Manovich perfectly summarizes what must occur in the front office of professional sports teams when a General Manager and a coach have business decisions to make. It is imperative to have someone who has watched all the games and has a feel for the chemistry and camaraderie, and also someone from afar who observes some games but mostly looks and makes decisions off the numbers. General Managers and coaches must examine and come to an agreement on both the expendability and fungibility of a player before making a decision on that individual. I believe society is at a crucial point in its fundamental views on watching sports and this next decade will determine how far statistics can take us compared to, and instead of, watching the actual games.
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