IN THE GAME

Hello readers, I’m currently updating [it will take a few days] Euroleague player profiles, adding advanced statistics to the pages. These statistics examine play-by-play data, not just the usual boxscore data. In case you are not used to these stats, read my short guide later in this post.

This is clearly inspired by 82games.com and other excellent NBA-related statistics sites, and although I cannot offer as much data as some of those, I think this still provides some interesting data on Euroleague players you cannot get elsewhere. Anyhow, the statistics are limited to Euroleague only.

Some of the profiles that have already been updated [basically only players from Barcelona, Real, Olympiacos and Panathinaikos]: Dimitris Diamantidis, Ricky Rubio, Theodoros Papaloukas, Vassilis Spanoulis, Josh Childress, Jorge Garbajosa, Novica Velickovic, Erazem Lorbek, Juan Carlos Navarro, Rimantas Kaukenas, Travis Hansen, Terence Morris, Felipe Reyes, Nikola Pekovic, Mike Batiste …

How to read the stats: I’m going to show you by the example of Real Madrid’s Sergio Llull, who is playing an excellent Euroleague season so far.

What you see above are just basic statistics as you all know them.

These are per individual possession statistics. Individual possessions per game [IPOS/G] is trying to measure how often a player is used by his team, how large a role he plays within the offense. The other categories basically mirror what he does with the ball. For example, a pass first player will have comparably few shot attempts and a comparably large number of assists.

Per team possession is a pace-adjusted version of the basic stats. When comparing players that are on the same team, this is similar to a per-minute adjustment, but it is quite helpful when you compare players from different teams, since it adjusts to game pace. Which per minute or per game don’t. A faster team will have more shot attempts and hence more opportunities in a game to score for each player. You know the drill.

Basic stats on a per 28 minutes basis. Why 28 minutes? Because it is a number that Euroleague key players might play, it gives you a better feeling for what the numbers are worth, than a per 40 minutes comparison

Basic shooting statistics as you all know them.

eFG% adjusts simply to the fact that a three pointer is worth one more point than a two pointer. For example, if a player has six shot attempts, he can score six points by either shooting 3/6 from two point range, or 2/6 from three point range. In one case there is a field goal percentage of 50 percent, in the other case 33,3%. Unfair, isn’t it? TS% goes one step further, taking free throws into account as well.

What we’ve had so far were rather basic stats, but now it really gets to the interesting play by play data. Assisted field goals, in other words: How big is the percentage of the player’s shots that were created by an assist? In Llull’s case, he has obviously taken the majority of his three pointers off the dribble, but has been assisted on 40% of his two pointers. Overall: 31.8% of his field goals were created by an assist.

Passing metrics: The common A/TO ratio, as well as assists per field goal attempts. A high number in the second category suggests that a player is a pass-first type point guard.

This is another very interesting catergory. We all know assists per game, but what type of basket does the assist lead to? We have three categories: Layups/Dunks/Close range shots, Midrange shots, Three pointers. As far as I have examined the statistics yet, Theodoros Papaloukas is creating 4.0 Layups/Dunks per game, which should be enough to lead the league in this category. There are differet type of passers: Some, like Papaloukas, Sarunas Jasikevicius for example, like to play the bullet pass to the rolling big man, others are more penetration & kickout players, which is why they assist on three point shots more frequently.

Rebounding percentages are extremely interesting as well, since they are a lot more accurate than offensive and defensive rebounds per game. The rebounding percentages are pace and playing time adjusted, so it examines how many rebounds a player collects in relation to the shots that were actually missed.

This is arguably the most interesting part: Floor time stats. What you see is basically oncourt [when the player is on the court] and offcourt [when the player doesn't play] comparisons in several statistical categories [points for, opponent points, field goal percentage for, opponent field goal percentage]. It examines how the team plays when a player is on the court, and how it plays when he isn’t. In points for in the oncourt column, you see the raw number of points the team scored while the player was on the court. In points for in the offcourt column, there is the raw number of points the team scored while the player was off the court. The same goes for opponent’s points.

However, since playing time [between all players] and game pace [between players from different teams] differs significantly, the raw numbers don’t allow conclusions. That’s why I adjusted them to game pace and the minutes [which you see in row 1] a player is on the court. Don’t be irritated by the per 70 possessions, it is the just about the average number of possessions for a Euroleague team in one game. So, we can say that it is is similar to a per 40 minutes calculation, with pace adjustment.

This is how you have to read Llull’s floor time statistics: In 70 possessions [about 40 minutes] that he is on the court, his team scores in average 86.3 points, and concedes 65.08 points [the row below]. In 70 possessions [again, about 40 minutes] that he is not on the court, his team scores 76.57 points and concedes 72.5 points. These are very positive values for him. A negative value in the points against per 70 possessions row/difference column means that the team concedes more points when he is not on the floor, so it is a positive thing. The difference between team production while he’s on the floor and team prodcution while he’s off the floor, is, projected onto the 70 possessions, 17.15 points.

Below that you see how his team’s and the opponent’s field goal percentages are when he’s on vs. off court.

Important: These numbers can provide valuable information, however, when the sample size is small [7 games that have been played so far in the Euroleague, that's a very small sample size] you should take everything with a grain of salt. The numbers are clearly at their most telling at the end of the season, anyway, if you want to draw conclusions earlier than that, feel free to do so.