“Born to Run”: Searching for a New “Pace” Statistic

Fast-break basketball is, at times, an easy way to score points. How can we measure its effect?

Here at ‘Cats Stats, along with giving our readers some interesting new ways to think about how basketball is played, we also aid Davidson Basketball (and many other Davidson Varsity sports), in pre-game preparation. This means it is our job to find ways to increase Davidson’s knowledge of both its opponents and own team. Coaches and players then use this knowledge to design and execute a gameplan, offensively and defensively.

In basketball, scoring points comes in a variety of forms.  The University of Wisconsin, for example, historically has played at one of the slowest rates in college basketball. Using a slow, methodical offensive attack, the Badgers often use the full shot clock to probe a defense in order to find a quality shot. On the other end of the spectrum, the North Carolina Tar Heels historically prefer to get up and down the floor quickly, attempting to score before the opposing defense has time to get set. Each of these offensive strategies has the capacity to be effective, as both of these teams ranked in the Top 30 in Points Scored Per Possession in the 2014-2015 college basketball season.  

Since teams vary in their offensive pace, quantifying this allows for numerical comparison of teams’ offenses. The value of such comparisons depends, of course, on the underlying metric. One of the most widely accepted measures of pace is simply the number of possessions that a team creates per 40 minutes. This statistic certainly does give viewers an indication of how fast a given team plays on offense, as more possessions per game mean a shorter, quicker time of possession. But what about defense?

Possessions per 40 minutes statistics give no indication of how well or how poorly a team may defend its opponents pace of play. Winning games is a combination of offense and defense; a team must be efficient in scoring points with its own possessions while using its defense to stop the other team from scoring points. NylonCalculus.com recently unveiled a way to quantify both offensive and defensive pace measures.

Nylon Calculus, for those who don’t know, is one of the most prominent basketball blogs on the web. Seth Partnow, editor of Nylon Calculus, explained his feelings regarding possessions per game in an October 9th article:

“I’ve never been particularly happy with ‘pace’ as a statistic, at least not as a measurement of anything with much meaning beyond simple possessions counts. So many things can cause the pace statistic to diverge from what we are really looking for the stat to measure, which is speed of play. Offensive rebounds, particularly good or bad defense, or even something crazy like the employment of a ‘hack-a’ strategy can cause the number of possessions to expand or shrink in ways that don’t readily reflect the quickness of a team’s offense.”

In response to these concerns, Partnow created a couple of new statistics that we believe are an effective way of measuring pace: Offensive Transition Percentage, Defensive Transition Percentage, and a team’s Speed Index. Offensive Transition Percentage is calculated simply by taking a team’s number of Transition Opportunities per game (a statistic measure by Synergy) and dividing it by the sum of a team’s Defensive Rebounds and Steals per game. 

off_transition This sum represents the total opportunities of a team to convert a possession into a transition opportunity. Defensive Transition Percentage is calculated the same way, except Transition Opportunities allowed, Defensive Rebounds allowed, and Steals allowed per game are the statistics used.

def_transitionThese two statistics allow the viewer to see the percentage of live-ball, offensive opportunities that a team converts into transition opportunities, and, on defense, how effective a team is at restricting their opportunities from those same transition opportunities. Finally, a team’s speed index is its Defensive Transition Percentage subtracted from its Offensive Transition Percentage.

This value represents how much faster or slower a given team plays in comparison to its average opponent.

Partnow then took these statistics and applied them to each and every NBA team for the 2014-2015 season. The results are shown in the graph below:

As we can see, teams near the bottom right of the graph, such as our hometown Charlotte Hornets, don’t often get out in transition, but are very successful in stopping their opponents from creating transition chances. Conversely, the quick-paced Houston Rockets, located at the top-left of the graph, are very good at creating transition chances, but also poor at eliminating their opponent’s transition chances. The Golden State Warriors, led by former Wildcat Stephen Curry, were quite adept at both creating their own transition chances and restricting their opponents transition possessions, as shown by their top-right location on the graph. Not surprisingly, this high level of transition efficiency resulted in the Warriors having the fastest Speed Index in the entire NBA, a quality that helped them capture the 2014-2015 NBA Championship in June.

After seeing Partnow’s work with these pace statistics and its application to NBA teams [1], we had the idea to try to apply that same work to NCAA teams. Below is a graph displaying the average offensive and defensive efficiency of each NCAA Division I Men’s Basketball Conference:

On the side bar, each conference’s Normalized Speed Index is listed. Speed Index needs to be normalized because the average NCAA speed score is actually negative. This effect is caused by outlying teams in each NCAA conference with poor speed scores, forcing the average speed score to be pulled down. As a result, the Normalized Speed Score is the percentage that a conference is above or below the NCAA average Speed Score.

As one can see, conferences that are significantly above the best fit line on the graph are “faster” conferences, while teams far below the best fit line are “slower” conferences, on average. The conference to which the Davidson Wildcats belong, the Atlantic 10, was the fastest conference in the country last year, in terms of Normalized Speed. Davidson’s former conference, the Southern Conference, can be seen near the lower confidence interval line, indicating the SoCon’s slower pace of play. In retrospect, Davidson’s move the the Atlantic 10 in 2014 represented a jump from last year’s 3rd-slowest Division I conference to the the fastest conference in America.

Information like this is crucial to coaches, players, and even fans. Preparing for a fast-paced team can differ from preparing for a slower paced team, as a coach’s scheme may differ depending on the opponent’s pace preferences. For example, against a team that likes to get out in transition, a coach may be wary of crashing the offensive glass, and opt to send players back on defense instead. Here we see that conference play can result in such differences, which can be especially important if a team’s style varies or struggles against faster or slower paced teams.  

Interestingly, if we look at both the Big Ten conference and the Atlantic Coast Conference, homes of the Wisconsin Badgers and North Carolina Tarheels, respectively, we will see that both of these conferences actually play a similar, fairly average pace. Both teams are significant outliers in their respective conferences, with Wisconsin being on the slower end of the spectrum and UNC being on the faster side. That being said, just because a conference plays at a seemingly average pace, teams must still be able to account for each and every individual team they face, as pace of play within each conference varies at different degrees

This type of metric can give teams an idea of which opponents they should attempt to create more or less transition opportunities against, as well as in which games they need to be wary of a specifically successful offensive transition team. What about team-by-team analysis? After all, we did just explain how individual team-by-team match-ups could be much more important than a conference level statistic. Well, we’re keeping those numbers behind closed doors for now. We can’t give out all of our secrets right away, but if you keep checking the site, we might just quench your thirst for more ‘Cats Stats.

[1] http://nyloncalculus.com/2015/10/09/nba-speed-index-team-transition-chances/

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