By Eurohoops team / info@eurohoops.net
The growth of the EuroLeague website to include live game stats along with comprehensive editorial and video coverage, the rise of the EuroLeague.TV platform, and the virtually real-time updates pouring in from the EuroLeague’s social media platforms allow fans to leverage technology to keep up with their favorite teams and players like never before.
The use of technology has also changed the way coaches and managers across the globe perform their day-to-day duties. Video indexing and player tracking information simplified the scouting process and allowed clubs to operate more efficiently, both in their offices when making personnel decisions and on the floor when running plays. More and more of the data that teams use has become available to the public, giving fans yet another lens through which they can follow their team, better understand the game, and engage with the EuroLeague.
Efficiency in the 2017-18 regular season
One of the most visible metrics of the new wave of statistics available to fans and relied on by professionals within the basketball industry is points per possession, which simply combines all of the ways a team scores points and divides it by the number of opportunities that team had to score. Unlike some statistics that require complex equations, points and possessions are the result of simple counting. It does not matter if a basket came on an unassisted Nando De Colo pull-up three-point jump shot out of a pick-and-roll to beat the third-quarter buzzer, a transition layup for Luka Doncic off a first-quarter steal, or a late-game free throw from Vassilis Spanoulis. Points are points and possessions are the sum of shot attempts, turnovers and fouls drawn resulting in free throws.
Points per possession is among the purest measures of basketball efficiency, and efficiency can say a lot about what drives a team’s success. That is especially true in the EuroLeague, which has risen in rank to become the most efficient offensive league in the world among major competitions this season. The graph below shows how far above or below each EuroLeague team has performed, both offensively and defensively, compared to the EuroLeague average of 0.99 points per possession.
This Offensive and Defensive Efficiency diagram paints a similar picture as the EuroLeague’s current standings, but also reveals that some teams have suffered from bad luck or bad timing relative to their actual level of play. CSKA Moscow‘s offensive efficiency has stood out all season, which explains why they have a two-game advantage over the teams vying for second place in the win column. Of the two teams sitting just below CSKA at 16-7, Olympiacos Piraeus has been this season’s gold standard defensively, while Fenerbahce Dogus Istanbul has been one of only three teams to rank substantially above average in efficiency on both ends of the floor. All the other teams currently in playoff positions have been significantly more efficient offensively than defensively or vice versa. At this stage of the season, metrics like points per possession can tell a story.
The strength of modern game tracking, like play type statistics, is the insight it offers into what
makes players and teams tick. For example, play type statistics reveal that a driving factor behind the offensive renaissance taking place in the EuroLeague this season has been the steady rise of pick-and-roll play over the last decade. In 2012-13, 35% of all half-court possessions in the EuroLeague were created out of a pick-and-roll, up from 25% during the 2007-2008 season. Those possessions resulted in 0.90 points per possession five years ago. This season, 42% of all half-court possessions were created out of a pick-and-roll, resulting in a remarkable 1.00 points per possession. These levels of usage and efficiency on pick-and-roll possessions are second to none across the world’s best competitions as the creativity of EuroLeague coaches and players has led to a rapid evolution in offensive strategy. The graph below shows the teams that created the most possessions out of pick-and-roll actions and which teams converted those opportunities most efficiently.
Examples like this are just a small sample of what can be learned from game tracking data. There are many more layers to peel back, including how each team attacks and defends individual actions, the contributions and tendencies of individual players, and what adjustments coaches make to gain an advantage and win more games.