In this win the Rockets were able to produce 27 more points, while only taking 3 more shots than the Spurs.

However, this brings us to the limitations of Moreyball. The Spurs were able to adjust throughout the series to better defend the James Harden-led squad, and moved on to the Western Conference Finals after 6 games.

The fate of Moreyball still remains to be seen, without a Houston championship it will be hard to convince the old guard of basketball that analytics can win championships. However, with the Rockets currently sitting on the best record in the league, and the philosophy’s poster boy James Harden looking primed to win the MVP award, they seem confident. We encourage you to join us in the future as we follow the journey of Moreyball, especially come playoff time when defense strengthens and every move will be analyzed under a microscope.

Intro to Advanced Basketball Analytics Metrics

Effective Field Goal Percentage (eFG%): Effective Field Goal percentage is a metric that you may have occasionally encountered. eFG% is a pretty easy concept to understand as it simply takes into account the fact that three point shots are worth 50% more than two point shots. Looking at this numerically, shooting 50% from three is equal to shooting 33.33% from two (remind you of Moreyball?). This is an important statistic to acknowledge when looking at a given players field goal percentage as it will give you a better understanding of their true efficiency in scoring the basketball. An example of this is shown when looking at Demar Derozan and James Harden. This season, Derozan’s field goal percentage (46.1%) is higher than Hardens (45.1%), but his effective field goal percentage is lower, Derozan at 49.4% while Harden’s eFG% is 54.6%. This can be attributed to the fact that Harden shoots (and scores) a lot more three point shots than Derozan does, resulting in a higher eFG%.

Value Added (VA) = (Minutes * (PER - PRL)) / 67. This is the estimated number of points a player adds to a team’s season total above what ‘replacement player’ (for instance, the 12th man on the roster) would produce. More on PER later (it needs its own section), so circle back here. The PRL (Position Replacement Level) = 11.5 for power forwards, 11.0 for point guards, 10.6 for centers, 10.5 for shooting guards and small forwards.

Estimated Wins Added = Value Added (VA)/30

Usage Rate (USG) = [(FGA + (FTA * 0.44) + (Assists * 0.33) + TO) * 40 * League Pace] /(Minutes x Team Pace). Don't worry, someone else does all of the calculations. What all these calculations lead to, is the number of possessions a player uses per 40 minutes.

This statistic aims to point out certain players on teams which rely on him more often to create something on offence. Russell Westbrook in the 2016-17 season, was able to break the season record of triple-doubles in a season. To numerically show how much of a workload he had, can be exemplified with the highest usage rate in the NBA at 40.8%. This means that almost half the game the team would rely on him to create scoring, as this translated to 31 points per game and 10 assists (roughly 25 points per game) to bring a grand total of around 56 points production per game. The total for the team was 106.6 PPG. To say he was heavily relied on would be an understatement.

Player Efficiency Rating (PER):

The most popular advanced metric commonly used today in basketball is player efficiency rating or PER for short. If you are familiar with baseball statistics, then this is comparable to WAR to determine a player’s efficiency compared to others. This metric involves one of the most complex formulas known within the analytics of all major sports.

What PER tries to accomplish is evaluating how productive a player performs on a per minute basis. It adds up positive contributions a player makes on the court while subtracting negative contributions in a statistical point value system. Things like points, rebounds assists would obviously be positive additions while turnovers would be negative. This stat is adjusted for pace and playing time which makes it easily comparable player to player.

The shortcoming with this stat is that there are not many stats in basketball that can back up how efficient a player is on defense. Sure, there are blocks and steals but this only tells so much and can be mostly a result of good team defense instead of individual. Where this deficiency becomes truly evident is that in 2013, Paul George, one of the NBA’s best two-way players had a lower PER than Jamal Crawford and Jr. Smith. For those of you who don’t know much about Jr Smith, he is one of the best bad shot takers and makers in the NBA. Take a look at the video below and you’ll get a good idea of why his shot selection should rank him much lower.