By John McCool
The NBA is in the midst of a statistical revolution. In 2014, the league introduced SportsVu software which not only captures statistics, but tracks player movement and shot selection as well. With this technology, anyone can see exactly how many dribbles Chris Paul takes before shooting a three, or the Dallas Mavericks’ average number of touches per possession.
Even before SportsVu tracking, however, teams like the Houston Rockets were using data analytics to gain an advantage over their competitors. At the forefront of the data analytics charge was Darryl Morey, the general manager of the Rockets. One of Morey’s main goals was to increase the number of possessions per game (also known as PACE). He figured that maximizing the number of shot opportunities would lead to higher points totals for the Rockets.
Recently, Morey has not been alone in adopting a PACE-first philosophy. The league’s PACE average has steadily increased from 93.76 (2011-2012) to 96.31 (2014-2015). Staying ahead of the curve, the Rockets placed in the top 5 in PACE among all NBA teams once again, averaging 96.3 last season.
In large part, Morey’s trade for James Harden in 2013 was a turning point for Rockets not only because Harden is an All-Star caliber guard, but also because of his ability to run the floor at an up-tempo pace. After the Harden trade, Morey continued to bring in quicker players, such as guards Corey Brewer, Marcus Thornton, and most recently, Ty Lawson. Similarly, 2015 draft pick Montrezl Harrell has brought high energy (in short spurts) to the Rockets by way of his 103.12 PACE.
Morey has also encouraged the Rockets to shoot more three-pointers in an attempt to squeeze out more points per possession. In fact, since 2012-2013, the Rockets have either placed 1st or tied for 1st in three-point attempts among all teams. The Rockets’ three-point philosophy does hold some merit; last season, teams that averaged more three-point attempts tended to score more points per game (correlation of 0.54). Moreover, FiveThirtyEight sports columnist Benjamin Morris notes that, thus far into the 2015-2016 season, three point attempts and winning percentage has yielded a correlation coefficient of 0.47.
Based on the Rockets’ fast-paced offense, I was interested in researching the effect, if any, that NBA teams’ PACE has on offensive and defensive statistics. From the 2014-2015 season, I distributed all 30 NBA teams into three PACE categories, ranging from 100.7 (Golden State) to 92.8 (Utah).
|Group||PACE||AVG PACE||# of teams|
For each PACE level, I compared statistics ranging from assists per game (APG) to efficient field goal percentage (EFF FG%). The ultimate goal was to determine how PACE is correlated with teams’ offensive or defensive numbers.
Figure 1 (PACE spread for all 30 NBA teams in 2014-2015)
Unfortunately, I found very few differences between the statistics of fast, medium, and slow PACE teams. One explanation for the low correlation between PACE and offensive/defensive statistics is that each NBA team plays a different style of game. For instance, the Golden State Warriors led the league in PACE during the 2014-2015 season, with 100.7 possessions per game, while the San Antonio Spurs hovered around the league average, with a PACE of just 95.9. Yet, despite their noticeably different offensive tempos, the Warriors and Spurs both finished last season as two of the top teams in the league.
Based on offensive and defensive efficiency alone, the middle-tier PACE teams (Group 2) were more successful than higher- and lower-PACE teams last season. In fact, Group 2 posted a +1.28 differential between offensive (OFF EFF) and defensive efficiency (DEF EFF). In comparison, Groups 1 and 3 recorded -0.1 and -1.4 differentials, respectively. Furthermore, the middle PACE group had better assist-to-turnover ratios (A/T) and true shooting percentages (TS%) than either the top or bottom PACE groups.
Interestingly enough, teams’ PACE had little to no influence on most key offensive categories. The highest correlation was .191 between PACE and EFF FG%. Similarly, there was a correlation of .165 between PACE and TS%. In terms of passing, there was a weak linear relationship between assists and PACE, exhibited by an r-value of .150.
Furthermore, the correlation between rebounds and PACE was -.14, which makes sense intuitively, given that a fast break or quick shot typically does not allow the offensive team to get into position to grab an offensive rebound. In addition, teams with higher PACE values tend to give up more baskets, which means less rebound opportunities on defense. Finally, teams’ PACE did not appear to have a significant impact on offensive and defensive efficiency. Teams with higher PACE values tend to score more points and give up more points on defense.
(Statistics from 2014-2015 Season)
Overall, it is difficult to identify how much PACE influences a team’s success. While top tier teams like the Golden State Warriors and the Los Angeles Clippers are regularly among the leaders in PACE, they also feature stars such as Stephen Curry and Chris Paul, whose talents would make any low- or high-PACE team significantly better.
The one conclusive result of my analysis is that high PACE teams need to minimize the number of points allowed. I found that teams with higher PACE values tended to have better point differentials (OFF EFF-DEF EFF). The 16 teams that scored more points than allowed last season averaged a PACE of 96.3, which qualifies for the top tier PACE group.
Most importantly, there was a moderately strong, positive correlation of .608 between these teams’ point differentials and PACE. This suggests that PACE may in fact play a role in teams’ overall success. Along these lines, the top 8 teams in PACE on this list averaged a +4.71 point differential, while the bottom 8 averaged a point differential of just +2.85.
Figure 2 (Pace vs. Offensive – Defensive Efficiency)
Here is a quick look at how PACE correlates with NBA teams’ statistics this season. It is important to note that Golden State’s 11.5 point differential (located in the top right corner of the graph) is an outlier in this linear model.
(Statistics from 2015-2016 Season as of 2/5/16)
A quick comparison reveals that, so far, PACE has had less of an effect on teams’ offensive and defensive efficiency than in the 2014-2015 season. More notably, there is a stronger correlation between PACE and rebounds/game and assists/game. However, it is still difficult to separate PACE from player skill level.
Overall, teams that maximize their possession counts may have a slight advantage over slower-tempo teams. The reasoning is simple: more possessions yields more shot attempts and higher point totals. This season, teams are playing at a faster PACE than ever before. So far, six teams including Boston and Sacramento have exceeded the 100 PACE threshold compared to just one team (Golden State) in 2014-2015. Moreover, the average PACE in the NBA is 97.8, continuing the trend of fast play. Whether increased PACE is a byproduct of front office analytics, rising athleticism, or a combination of the two, teams are readily adopting high tempo offenses, which is gradually changing the style of play in the NBA.
* Note: these statistics are dated from February 16, 2016
 Pace Factor-the number of possessions a team uses per game
 Offensive Efficiency: the number of points a team scores per 100 possessions
 Defensive Efficiency: the number of points a team allows per 100 possessions
 Curry and Paul currently have 103.60 and 101.68 PACE values, respectively during the 2015-2016 season
 All statistics are courtesy of NBA.com, 538.com, and ESPN.co