Motion, Movement and Identity

Last Summer, during the Sloan MIT conference in Boston, someone made the mistake of informing Stan Van Gundy that Paul George led the league in distance traveled. His response was this: “of what possible use is this information?” It was classic Van Gundy, equal parts serious and sarcastic. Van Gundy was all at once dismissing the statistic as valid in and of itself and asking wether there is any pertinent information to be gained from how far a player runs. The answer to his question might simply be: nothing. It’s a stat that means nothing. Stats in and of themselves rarely provide answers as much as they provide a lens for which to ask more interesting and informative questions.

One question that this data has led me to ask is which teams move around the most per possession. NBA.com doesn’t have this data available but with a little bit of digging, we are able to get a rough idea. But first, let’s walk through the steps.

1. Determining the distance ran per possession

The first step is to take the total distance a team runs per 48 minutes and divide that by the number of possessions per 48. The reason this is important is because a team that has 7 or 8 more possessions per game is more likely to run further overall. Since the number we are looking for is distance per possession, we can begin by looking at Distance/Pace.

Distance (ft) / Pace gives us our first step: the average number of feet a team runs per possession.

Distance (ft) / Pace gives us our first step: the average number of feet a team runs per possession.

2. Discovering the expected distance given the trend

The first thing that this graph reveals is that there is a very obvious correlation between the teams with a slower Pace and the teams with a higher distance per possession. The reason for this is because teams that have a lower pace tend to have much fewer fast breaks, fewer FGA early in the shot clock and therefore are in half court settings for longer. Longer possessions would mean further distances per possession. Ideally, we would be able to break every play down and calculate how far each team moves per second on offense. Unfortunately, that data isn’t available to the general public. However, we can get an estimate of the correlation between a team’s up and down pace, and the distance per possession that would be expected of them given their pace. That regression looks like this.

The trendline shows the expected distance a team would run given their pace.

The trendline shows the expected distance a team would run given their pace.

3. Adjusting for the regression

Once we discover the expected distance a team should run, we can compare that with the distance they actually run to see if they are running further than the expected average. In short, we make that downward sloping line the baseline and measure how far off each team is from the baseline.

Most teams fall within +/- 10 feet of their expected distance per possession.

Most teams fall within +/- 10 feet of their expected distance per possession.

The thing that immediately jumps out are those two towering columns on the left: the San Antonio Spurs and the Philadelphia 76ers. Both teams run significantly more than expected, especially when compared to every other team in the league. So much so, that they actually weigh the data so that only 8 teams are in the positive. The second thing that jumps out is how spread out the “good” teams are. By this metric alone, the 76ers most closely resemble the Spurs yet one is the defending champion and the other is one of the worst teams in NBA history. Likewise, great offenses like the Warriors and Trail Blazers perform above expected while other great offenses like the Clippers, Raptors and Cavaliers run much less than average. Per the chart below, there is hardly a correlation between half court pace and offensive rating, and what correlation there is, is a negative one.

There relationship between the distance against expected and Offensive rating.

There relationship between the distance against expected and Offensive rating.

4. Takeaways

The first takeaway is that Half Court Pace reveals an offensive style more than an offensive quality. Teams like the Cavs and Clippers position shooters in the corners who are usually uninvolved on most plays, while the ball handler runs a pick and roll looking to collapse the defense. Other teams, like the Spurs and Trailblazers, whip the ball around the perimeter and rely on all five guys to make plays and create motion. In those offenses, few players are used as stand still floor spacers. The ball movement and constant motion that the Spurs have refined over the years has become en vogue this season and lots of teams are trying to replicate it. Yet the data shows that few teams are successful at it.

Another takeaway is that the stylistic differences between teams like the Spurs and Clippers is extremely noticeable. In this case, the differences aren’t random or the result of a failed attempt for the Clippers to replicate the Spurs. The differences are deliberate. The Clippers like having the ball in Chris Paul’s hand because he has a unique talent for getting the offense to score efficiently when he is at the helm. But it is interesting that the Warriors also have a point guard with a knack for getting his team efficient possessions yet the Warriors move much more in half court settings. David Blatt entered the season with hints that the team would be running a high motion, princeton style offense yet so far the Cavaliers have relied on Lebron and Kyrie to probe the defense while role players spot up, stand still, and space the floor.

There are certainly more variables at play and a lot of noise in the data. One obvious flaw is that in this data provided by SportsVu, one possession equals one offensive and defensive possession. However, there is enough in the data here to provide a lens with which to begin asking more questions.

@Adam_Mares

About @Adam_Mares

Adam Mares is a Colorado native and an NBA mega fan.

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