Blew it All on Luol? Turned off by Mozgov?: Statistical Analysis of 2016 NBA Free Agency
By Kunal Dutta, Liam Grah, Riley Henderson | October 30, 2019
Looking back on the 2016 NBA summer free agency, it is obvious that there were some ridiculous contractual overvaluations of average and below-average players. However, there were also some additions and extensions that proved to be amazing bargains for their teams. In trying to analyze this relatively subjective and complex set of data, I tasked myself with devising a metric that could compare the LeBrons and KDs of the world to the Bobans. Seeking to quantify the biggest steals and busts, or equivalently, the best and worst General Manager decisions of the summer, I computed a ratio for each signee that represented the Win Shares that they contributed to their team divided by the number of millions of dollars in their contract. For example, Russell Westbrook contributed a total of 30 Win Shares to the Thunder during the 2016-2017, 2017-2018, and 2018-2019 seasons. The extension he signed in the 2016 offseason was for 3 years and $85 million. So, his calculated ratio was 30 WS/$85 Million = 0.35 WS/$ Million. Irrespective of playoff woes, this was a solid re-signing by GM Sam Presti. Nevertheless, Westbrook’s ratio was not high enough to crack the top 10, even despite his 2017 MVP campaign.
While computing these ratios, it became clear to me that it would be prudent to impose a minimum contract qualification, as players signing for $1 million for a single season only needed to amass 1 Win Share to shoot all the way up to the top of the list, something I discovered was actually quite common. Thus, I set this contract minimum at a cumulative total of at least $10 million to narrow the scope of reference to players that are at least somewhat recognizable to the average NBA fan. Of the 137 signees, 71 met this criteria. The distribution of the ratios of these eligible players is shown below and something that is immediately noticeable is that the curve is skewed to the left, showing that a significant percentage of signees underperformed their salary. Moreover, the mean ratio of Win Shares/$ million in the summer of 2016 was 0.24 and the median was 0.21.
As seen in the bar graph below, the top 10 encompassed Hall of Famers (Harden, Durant, James) as well as a number of undervalued role players.
Looking at the bottom 10, we see a different trend with the worst calls being made on players ranging from aging veterans to inexperienced prospects. Along with expected names (Deng, Parsons, Mozgov), the busts on this list reflect a general sense of unwarranted optimism, likely due to the financial surplus and urgency in claiming players before competitors could.
In 2016, the amount of spending for NBA teams was astronomical compared to the preceding seasons, coming with a $24 million increase in the salary cap.
Some individual players definitely underachieved following their payday. However, did the teams who spent grandly fare better than those who didn’t?
Here were the 10 largest contracts given that season and the teams that signed the (quite massive) checks.
And here are the win percentage of those 10 teams that season.
With a wide range and an average of only 56.21% (compared to the average win percentage for a playoff team of 60.06%), higher spending clearly did not equate to better team performance in the 2016-17 season.
However, many of these top contracts were in the interest of long-term development (with the notable exceptions of LeBron James and Kevin Durant). Let’s see how those teams fared in the 2018-19 season, compared to the rest of the league (teams highlighted in yellow).
Yikes. With a combined 48.78% win percentage, the performance of the big spenders was slightly below average only 3 years later, with just 3 playoff teams remaining out of the crop. Even then, the Toronto Raptors won the 2019 title after trading their 2016 resigning of DeMar DeRozan, for the individually cheaper contracts of Kawhi Leonard ($18.8 million yearly) and Danny Green ($11.25 million yearly).
Why did these teams perform relatively poorly, given their large financial commitments? If we compare the actual salary of the players to the projected using the CARMELO player projections by FiveThirtyEight, here’s what we get.
As shown, there is no obvious correlation with the data, although ideally, there should be a rough trend present between a player performance metric and salary.
However, if the players who did not re-sign with their original team (Horford, Durant, Batum), there is a more clear trend, with the exception of LeBron James.
Under the NBA salary cap rules, players can re-sign with a team for a higher price and duration than other teams. This rule may be to protect smaller or less successful teams from losing talent, but based on the 2016 contracts, the rule may cripple teams that do not sign generational superstars like LeBron James or Kevin Durant, as it pays them to the same scale with a clearly worse result.
Similarly, in 2015, the top 5 largest annual contracts awarded were to returning players (Anthony Davis - Pelicans, LeBron James - Cavaliers, Kawhi Leonard - Spurs, Damian Lillard - Trailblazers, Kevin Love - Cavaliers). A brief look into contract history shows that this is the case for the majority of recent years - a display of how returning players can leverage the NBA rules to earn bigger, sometimes-undeserved paydays.
Through these trends, the 2016 offseason will go down in history as a goldmine for players with expiring contracts, but with the high number of regrettable deals, a shot in the chest for overall team performance.
Now that we’ve looked at some of the questionable decisions made during this fateful summer on a macro-level, is there anything that we can gleam from a micro-level analysis of a single decision made by a team? In this pursuit, I have chosen one of the most infamous and unreasonable contracts produced by the cap spike: Timofey Mozgov’s four-year, $64 million deal with the Los Angeles Lakers.
To begin, we should first compare who the Lakers were replacing with Mozgov, Roy Hibbert. A two-time All-Star with the Indiana Pacers, Hibbert distinguished himself as a defensive presence, anchoring the Indiana frontcourt during his tenure. On the last year of his deal, he was traded to the Lakers, and went on to have a middling season, providing little of note for the 17-win squad. Despite having one of his worst statistical seasons of his career in 2015-16, his numbers hold up well to Mozgov’s.
Outpacing Mozgov in assists, rebounds, and blocks, there seems to be little reason for why the Lakers would cast Hibbert aside for a similarly performing player. Why would the Lakers dish out $64 million for a horizontal move? The discrepancy in win shares seems to indicate something that Mozgov offers in the way of team success, but you must remember that Hibbert played with one of the worst teams in NBA history, which prioritized the fanfare of Kobe’s last run rather than actual winning, explaining his lack of win shares. Mozgov, on the other hand, enjoyed riding along with the 57-win Cavaliers, playing alongside the likes of Kyrie Irving and a resurgent LeBron.
So, is there something about playing in Cleveland that contributed to Mozgov’s façade as a legitimate NBA center? A look into the distribution of assists on Mozgov’s made field goals reveals an interesting answer.
Huh. Who would’ve guessed that having one of the greatest playmakers of all time feeding you passes and creating plays boosts your value? 30% of all Mozgov’s field goals were dished out by LeBron, and his reliance on LeBron’s passing did not translate well to a Lakers team bereft of strong passers. Additionally, only 12.7% of Mozgov’s makes were unassisted. Although it’s not necessarily a mark for a player to rely on assists to generate points, it does show cracks in Mozgov’s ability to function outside of the system in Cleveland. In comparison, Hibbert scored 38.2% of his shots on unassisted plays, demonstrating some ability to create for himself.
For our final exploration, let’s compare the shot distribution of Mozgov and Hibbert by distance from the hoop.
Although the chart seems to show more similarities than not between these two players, the importance is in the subtlety. The majority of Mozgov’s shots were made within 3 feet of the basket, illustrating his heavy reliance on dunks and layups to touch the ball in around the paint. Hibbert also relied on the traditional scoring distribution, with a healthy portion of his makes placed within the paint as well. However, unlike Mozgov’s distribution, Hibbert shows aptitudes for hitting midrange jumpers, stretching the floor to some degree. I am in no way suggesting that Hibbert was a sniper for the Lakers, or even that he should be considered a stretch-five. However, as Marc Gasol and Joel Embiid have displayed in recent seasons, even the slight ability to make distance jumpers forces defenses to stray out from the paint. Hibbert’s jumpers were far from a potent scoring force, but he provided spacing for cutters and drivers. In this respect, Hibbert’s game fared better for the future of the league than Mozgov, making the Lakers look even dumber.
There are certainly other factors that went into the Laker’s decision to exchange Hibbert for Mozgov during the 2016 offseason. Schematic fit, performance projections for multiple years out, and differences in demeanor all could have pushed the Lakers to sign Mozgov to that monstrous deal. Who knows? However, in retrospect, the data shows that moving from Mozgov to Hibbert was a statistical horizontal move, and the Lakers now regret their decision.
Sources:
- 2018-19 NBA Standings
- 2016-17 CARMELO NBA Player Projections
- 2016-17 NBA Standings
- Largest NBA Free Agent Contracts of 2016
- Lebron Estimated Career Earnings
- Roundup: 2015 NBA Free Agent Grades