Over the course of the 169 day 2013-14 NBA regular season, each franchise will play a game about every other day. Add cross-country travel and inevitable injuries to the already grueling 82-game schedule and it is an almost certainty that each team will experience nights where they perform significantly above and below their true talent level.

For instance, consider the January 8th contest between the Warriors and Nets. The Warriors had played the previous day and were concluding a 10-day, 7-game east coast road trip. Meanwhile, the Nets arrived at the Barclays Center rested and in the midst of a 4-game home stand.

Bottom line, the NBA schedule is littered with games where one team holds a situational edge over another. With these factors in mind, I examined how consistently each team has performed to date this season.

Standard deviation is a statistical measure that quantifies the degree to which data points deviate from the mean. In basketball terms, standard deviation measures the variability of each team’s individual game results relative to their average level of performance.

Because points for and points allowed tend to be normally distributed, standard deviation can also tell us what percentage of games will fall within a particular score differential; roughly 68% of game results will fall within one standard deviation from the mean, 95% within two standard deviations, and just about every final score will land within three standard deviations from average.

For example, the Miami Heat has an average margin of victory (MOV) of 5.4 points per game with a standard deviation 11.0. In other words, LeBron & Co.’s performance to date indicates that they defeat their opponents, on average, by 5.4 points per game and about 68% of their contests fall within the range of a 16.4 point victory and a 5.6 point defeat.



Above average teams like the Heat – those with a positive MOV – benefit from playing consistently night in and night out. At the time of this writing, the Warriors and Timberwolves both have a MOV of 4.1, but the former has played a more consistent brand of basketball than the latter (see table below). As a result, Golden State sits comfortably ahead of Minnesota in the ultra-competitive Western Conference.



Conversely, below average teams are rewarded for playing a high variance brand of basketball. Given two teams with equal, negative MOV’s, the more inconsistent team will win more games. Overall, the relationship between winning and consistency is fairly simple: the more inconsistently a team performs, the closer its winning percentage approaches .500.

With these concepts in mind, below is table illustrating each team’s level of performance and consistency this season.



The Knicks have performed the most inconsistently by a considerable margin. New York’s relationship with the three-point shot probably contributes to a standard deviation of 16.0. 27.5% of the Knicks scoring comes via the long ball, per NBA.com, a percentage that is only surpassed by Mike D’Antoni’s three-point happy offense in L.A. Meanwhile, Mike Woodson’s club also allows the 5th most three-point attempts per game (22.9).

Contests with a disproportionate amount of three-point attempts produce more erratic outcomes because of the high risk, high reward nature of shots from beyond the arc. It may sound counter-intuitive, but given the team’s negative MOV, the Knicks erratic performance has actually been beneficial; if a lower standard deviation accompanied a -2.3 MOV, the team would have won fewer games. I take caution with this conclusion, however, because it is grounded in the assumption that MOV remains constant.

On the opposite end of the spectrum, the Mavericks have played the most consistent basketball to date. The Mavs boast a veteran-laden rotation led by reliable veteran Dirk Nowitzki. Jose Calderon orchestrates an offense that turns the ball over on just 14.1% of possessions, per NBA.com, good for 5th in the league.

Lastly, it’s important to highlight that the Heat – despite Dwyane Wade being in and out of the lineup – have played more consistently than 25 other teams. For a team with a lower MOV relative to the consensus of their true ability, it appears that the Heat may be taking their foot off the gas for a prolonged period rather than playing the more erratic, try hard here-and-there strategy that the media may portray.

So what does this all mean moving forward? Honestly, my first analysis of NBA team-by-team consistency breeds more questions than answers. Are these standard deviation numbers indicative of how consistently teams will perform the rest of the way? What metrics correlate best with a team’s standard deviation? Teams would also benefit from this information; large underdogs should embrace high variance strategies while big favorites should employ an approach that minimizes score variation.

Extracting predictive value is often the ultimate prize and while this article may not offer all the answers, I suggest that those who are interested in projecting NBA outcomes incorporate variance analysis in their work. The smaller a team’s standard deviation, the greater a bettor’s confidence level should be when determining its expected level of performance.