By: Jeremy Bullock
In the near future basketball players wont be limited to height, weight, and speed measurements. They will play wherever their skill set allows them to play, regardless of their physical measurements. In this article, I will discuss how analytics will aid in the evolution of basketball into a positionless game.
1) Using the power of analytics to help further the development of positionless basketball We witnessed positionless basketball during the 2015 NBA Finals, when Coach Kerr of the Golden State Warriors decided to bench his starting center, Andrew Bogut (7’0), and inserted Andre Iguodala (6’6) into the starting lineup. In the near future, there will be no more point guards or power forwards, only basketball players. Titles of positions as we know them are likely to still exist; however owners, general mangers and coaches are more likely to acquire players who can play interchangeably. When referring to “positionless” basketball, it is about all five players having the ability to successfully do multiple things. For example, one player being able to grab a rebound, bring it up court, and then initiate the team’s offense without having to pass the ball to the team’s point guard. Having an offense that can be initiated by any of the five players on the court will significantly increase the pace with which a team can play. As positionless basketball becomes the norm, players in the draft and/or free agents who may not fit the traditional height, weight, speed requirements for a particular position, rather they are simply basketball players who have a variety of contributory skills. These players become extremely valuable due to their ability to contribute in a variety of ways. Making players like Draymond Green, Kyle Anderson, and Josh Smith inherently more valuable. As a result, analytics may be used to redefine the “positions” of basketball. Once a franchise has established the style of play best suited for them, they can then look to the analytical data to determine which player best fits their needs.
2) Examples of Positionless Basketball
To illustrate how analytics has the potential to provide example of positionless basketball, here are a few examples of what the “new” positions could be referred to, and which areas of analytical data could support this position. The titles and analytical categories listed below are not intended to be all-inclusive, rather to provide an overview of the analytical potential.
Instead of a traditional point guard they may elect to have a “Utility” player who is able to contribute to the team in a multitude of ways. To determine what this player looks like teams may evaluate this position based on assist percentage, rebound percentage, Player Impact Estimate (PIE), adjusted plus/minus, defensive rating, true shooting percentage, offensive rating, and effective field goal percentage. Josh Smith of the Rockets is a great example of a utility player.
Instead of a shooting guard, a team could decide that having “Scorers” on the floor is more valuable to their style of play. A scorer is someone who regardless of position has the ability to score points effectively and efficiently. The analytical data that could be used to support theory is usage percentage, percentage of points in the paint, percentage of points that are three pointers, percentage of three point field goals attempted, free throw percentage, and true shooting percentage. An example of a scorer is James Harden or Kevin Durant.
Rather than have a traditional small forward, a team could utilize a “Glue Guy.” This player is valuable because they are able to keep everyone on one accord defensively, while contributing when necessary offensively. Typically, a coach will not run specific plays for this player instead the guy will generate his offense organically. Draymond Green is a perfect example of a glue guy. The statistical categories that may determine this position are based on one’s activity, effort, energy, defensive rating, rebound percentage, effective field goal percentage, percentage of 50/50 balls a players is able to secure per available 50/50 balls, deflections, and anything else that could be classified as “hard play.” This player’s talents may not be solely measured in statistical data, but the use of Synergy or other NBA statistical tools may be necessary to further this evaluation.
As an alternative to the power forward position, a team may call this position “Blue Collar,” which is similar to the glue guy in the sense that their game isn’t predicated primarily on offensive contributions. Their game is based on contributing to the team in any possible fashion. And it is done by hard work, and bringing the proverbial lunch pail to work daily. Theoretically, many of the same stats used to evaluate the “glue guy” could be applied to the “blue collar” player as well. An example of this player in today’s NBA is Taj Gibson or Omar Asik.
As a replacement for centers teams may refer to this position as “Defensive Presence.” Defensive plus/minus, blocks, deflections, steals, rebounding percentage, and defensive rating could determine this player’s game impact. In the NBA today Tony Allen and Patrick Beverly are great examples of players who provide a defensive presence.
All of these titles are interchangeable, your scorer or defensive presence could be any of the five players on the floor at any given time. Furthermore, a coach may elect to have any combination or amount of these individual players on the floor at any given time, dependent upon what the analytical data suggest is best for the team. Teams simply need to look at the statistical categories that define the particular “position” and it’s impact on the game, both positively and negatively. Furthermore, the aforementioned positions, if formulated correctly, should provide the team with a well balanced and cohesive unit on the floor at all times. As we continue to see the evolution of basketball it can be expected that within the next few years’ basketball will be a positionless game.