Green Grove Project. 2017/18 Season Analysis

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1 2017/18 Season Analysis

2 Company Overview We help the young athletes to accelerate their sport-specific growth through the statistical analysis. Our services are based on a Decision Management Tool which integrates and analyses the Athletic and Bio-Athletic data creating valuable insights for the athletes and the teams. International Award: Top-15 Rising Sports Analytics Startups in Europe (KPMG, 04/2018) Presenters: National Statistical Conference (Lamia GR, 05/2018) World Series Sports Analytics Conference (Amsterdam - NL, 05/2018) Our website: statathlon.com Address: contact@statathlon.com Our website: statathlon.com Address: contact@statathlon.com

The case study used for this project is the Lithuanian club BC Zalgiris Kaunas. The selection was based on the following criteria: A highly reputed and ambitious professional club from Europe.

3 Introduction focuses on the individual and team performance of a basketball club, using various data analysis methods. Insights of this project can be used by the clubs and all relevant stakeholders (coaching and medical staff, players etc.) in order to track its performance in different categories. The case study used for this project is the Lithuanian club BC Zalgiris Kaunas. The selection was based on the following criteria: A highly reputed and ambitious professional club from Europe. The club would participate in a major continental competition with adequate number of matches to be led to fair conclusions. In addition, a few non - playing criteria were set such as team location (more specifically, coming from a country with high interest in basketball) and strong business profile. The data has been extracted from Euroleague Basketball Regular Season ( ), where all 16 teams faced each other twice in 15 home and 15 away games. 01

AIMS & OBJECTIVES Aims and Objectives To understand better the impact that various statistical indexes have and find the correlation between them.

4 AIMS & OBJECTIVES Aims and Objectives To understand better the impact that various statistical indexes have and find the correlation between them. To assess each player s performance in order to find his strengths and weaknesses, as well as his overall progress throughout season. To provide useful recommendations to coaching staff regarding team s actual strengths and weaknesses. Analysis outcomes can be used to determine if there are any fields where team should pay more attention in training or during pre - game preparation. To help coaching staff identify the exact roles that are missing from the current squad and look for players with similar skills in transfer market. To find out how certain players perform in games against teams with different characteristics, in order to adjust defensive and offensive tactics accordingly in the future. To explore team s performance during specific phases of a game (early minutes, clutch time etc.). These results help the coaching staff to manage players more efficiently in relevant situations. 02

5 Indexes Interpretation For the purposes of this project, more than 30 performance indexes have been used. They have split into 4 main categories, according to their complexity (basic & advanced) and content (individual & team). Basic individual and team performance indexes are being used by Euroleague Basketball and everyone can have free access to them through its official website or other partners websites. Advanced indexes are a mixture of indexes used in NBA, indexes that Euroleague Basketball does not directly provide and therefore their calculation is made through the official available data, and unique performance indexes which have been created by the research team of Statathlon. In the following pages all advanced indexes are explained. Their interpretation includes specific comments on what could be considered as a good performance in each of them, as well as a few conclusions and recommendations that can be extracted out of them. 03 5

6 Current Squad of Zalgiris Kaunas NAME POSITION HEIGHT (cm) AGE NATIONALITY JOINED Brandon Davies C USA 2017 Kevin Pangos PG CAN/SVN 2016 Axel Toupane SF/SG FRA 2017 Beno Udrih PG/SG SVN 2017 Paulius Jankunas PF/C LTU 2010 Martynas Sajus C LTU 2017 Gytis Masiulis PF LTU 2014 Arturas Milaknis SG/SF LTU 2016 Vasilije Micic SG/PG SRB 2017 Martynas Arlauskas SG LTU 2017 Aaron White PF USA 2017 Antanas Kavaliauskas C LTU 2016 Paulius Valinskas PG/SG LTU 2016 Edgaras Ulanovas SF/PF LTU 2014 Dee Bost PG USA

7 2017/18 Zalgiris Kaunas Fixtures Game Date Opponent Home/Away 1 13/10/2017 Crvena Zvezda Belgrade Home 2 20/10/2017 Khimki Moscow Region Away 3 24/10/2017 FC Barcelona Away 4 26/10/2017 Real Madrid Home 5 3/11/2017 CSKA Moscow Away 6 9/11/2017 AX Armani Exchange Olimpia Milan Away 7 14/11/2017 Unicaja Malaga Away 8 16/11/2017 Baskonia Vitoria Gasteiz Home 9 23/11/2017 Anadolu Efes Istanbul Home 10 30/11/2017 Maccabi Tel Aviv Away 11 7/12/2017 Panathinaikos Athens Home 12 14/12/2017 Fenerbahce Istanbul Away 13 19/12/2017 Brose Bamberg Home 14 21/12/2017 Valencia Basket Away 15 28/12/2017 Olympiacos Piraeus Home Game Date Opponent Home/Away 16 5/1/2018 Crvena Zvezda Belgrade Away 17 12/1/2018 Unicaja Malaga Home 18 16/1/2018 Brose Baskets Away 19 18/1/2018 Valencia Basket Home 20 25/1/2018 Panhinaikos Athens Away 21 1/2/2018 Maccabi Tel Aviv Home 22 9/2/2018 Khimki Moscow Region Home 23 23/2/2018 Anadolu Efes Istanbul Away 24 1/3/2018 FC Barcelona Home 25 9/3/2018 Fenerbahce Istanbul Home 26 15/3/2018 Baskonia Vitoria Gasteiz Away 27 20/3/2018 AX Armani Exchange Olimpia Milan Home 28 22/3/2018 Real Madrid Away 29 30/3/2018 CSKA Moscow Home 30 6/4/2018 Olympiacos Piraeus Away 05

8 Individual Performance

7 players perform better than team s season average (4.4).

9 Individual Performance - GSI Game Score Index (GSI) Kevin Pangos & Paulius Jankunas appear to be the most productive players during the year. 7 players perform better than team s season average (4.4). Game Score Index presents the overall performance of an athlete. It is more accurate than Euroleague s PIR index, since it emphasizes more to categories that have bigger impact on the game. 07

Players with good performance in this category are usually those who should run the offence.

10 Individual Performance Assists & Turnovers Assist Percentage - 3 players perform better than team s index (25.33). Despite his position, Edgaras Ulanovas shows high assisting ability. An effective index that evaluates playmaking and passing skills of a player. Players with good performance in this category are usually those who should run the offence. Turnover Percentage - Vasilije Micic has very poor performance on ball handling, by committing approximately 1 turnover every 4 attempts. Usually higher in guards than forwards or centers. Players with high turnover percentage should not be heavily involved in actions that have to do with ball handling as they are quite prone to turning the ball over. 08

11 Individual Performance Blocks & Steals Block Percentage Despite his position, Beno Udrih shows high blocking ability. In addition, Ulanovas has the highest blocking percentage despite his height (1,98m) and position. Good indicator of defensive (and particularly blocking) skills of a player. Quite useful especially for power forwards or centers, who are the ones that are usually more likely to block a shot. More than 2 blocks/game is considered good value. Steal Percentage 4 players perform better than team s season average (1.69). Despite his position, Brandon Davies appears to be the most effective stealer. Players with high steal percentage values are considered good defenders and could be a good suggestion to guard opponent point guards for instance or be on floor when teams want to pressure. 09

Individual Performance Free throws & Rebounds Free Throw Rate (%) Despite his impact on Zalgiris game, Kevin Pangos has the 2 nd worse rate among his teammates.

Players with high free throw rate (especially if they also have high number of field goal attempts) are very efficient at drawing shooting fouls.

12 Individual Performance Free throws & Rebounds Free Throw Rate (%) Despite his impact on Zalgiris game, Kevin Pangos has the 2 nd worse rate among his teammates. Moreover, Paulius Jankunas has the 5th best Free Throw Rate and FT% above 80%. Players with high free throw rate (especially if they also have high number of field goal attempts) are very efficient at drawing shooting fouls. Rebound Rate (%) Arturas Milaknis & Vasilije Micic are the least effective players on the rebounding sector It is probably the best index to compare rebounding ability of two or more players because it takes into account both playing time and total rebounds contested. 10

In general, values greater than 1 are considered good. Assisted Field Goal Made (FGM) Paulius Jankunas is the most efficient executioner.

13 Individual Performance Assisting Efficiency Assist to Turnover Ratio Despite his impact on Zalgiris game, Brandon Davies has the 4 th worst rate among his teammates. It is used to evaluate ball handling and passing skills of a player. In general, values greater than 1 are considered good. Assisted Field Goal Made (FGM) Paulius Jankunas is the most efficient executioner. Players with high value in this category can be considered good spot shooters or finishers from close range, since the majority of assists end up in those kind of field goals. 11

Similar to Field Goal Percentage, but adjusts for the fact that 3 - point field goals are worth 50% more than 2 - point field goals. Ideal to use to compare the FG% of two or more players.

14 Individual Performance Shooting Efficiency EFG% (Effective Field Goal Percentage) - 7 players perform better than team s season average (56.9). Arturas Milaknis is a great scorer beyond 3 point line, thus increasing his performance in this category. Similar to Field Goal Percentage, but adjusts for the fact that 3 - point field goals are worth 50% more than 2 - point field goals. Ideal to use to compare the FG% of two or more players. 2PA/3PA Ratio Antanas Kavaliauskas & Paulius Jankunas are more efficient than their guard teammates. Brandon Davies did not try any 3P shot during regular season. It could be used though together with FG%, EFG% or TS% to find out whether a low value in any of those 3 indexes could be a result of increased number of 3PA instead of 2PA. 12

Individual Performance Field Goal Efficiency FG% After 25 Minutes of Playing Time - Despite his possible fatigue, Aaron White is very efficient in making field goals after 25 min of playing time.

Close/Shots/Lay - up/other FG% - Paulius Jankunas appears to be the most productive player in FG%.

15 Individual Performance Field Goal Efficiency FG% After 25 Minutes of Playing Time - Despite his possible fatigue, Aaron White is very efficient in making field goals after 25 min of playing time. This index is a way to measure impact of fatigue on a player. After a certain amount of playing time (set to 25 minutes), most of them show signs of fatigue. Close/Shots/Lay - up/other FG% - Paulius Jankunas appears to be the most productive player in FG%. The aim of this index is to provide useful insight regarding the efficiency of a player in all above shooting categories. Therefore, coaching staff could plan accordingly to increase or reduce his attempts in order to maximize his potential FG%. Other FG represents alley oops and put-backs., and Shots is shots beyond 3 meters from the basket and 3 pointers. 13

Individual Performance Fouls Drawn Fouls Drawn /Free Throws Made - Paulius Jankunas is the player who draws the most fouls during the year, followed by

Players with high value, should be point of reference for team s offensive plays.

16 Individual Performance Fouls Drawn Fouls Drawn /Free Throws Made - Paulius Jankunas is the player who draws the most fouls during the year, followed by Pangos and Ulanovas. This index indicates player s free throw efficiency, considering fouls drawn. Players with high value, should be point of reference for team s offensive plays. Charges Drawn Kevin Pangos appear to be the most efficient player in drawing charges (4 times more that the average player) This index indicates the defensive ability of each player. Players with high value of charges drawn, have a proper position & spacing on the court. 14

17 Individual Performance Efficiency of +/- Index +/- Index Paulius Jankunas & Kevin Pangos have the biggest impact on Zalgiris game. The only 2 players who perform better than teams season average. Equal to total team points scored minus opponent team points scored while a player was on floor. It can give a rough indication of his overall impact on team success. Positive values are considered good. +/- Index During Clutch Time - Paulius Jankunas & Aaron White have the biggest impact on Zalgiris clutch time game. Kevin Pangos, despite his overall high +/- index performance, appears less efficient during clutch time. This index counts the overall efficiency of a player during clutch time, as it takes into account both offensive and defensive awareness. Positive values are considered above average. 15

Individual Performance Clutch Time Player Efficiency Clutch Time Percentage - Despite his impact on Zalgiris game, Brandon Davies rarely participate in

18 Individual Performance Clutch Time Player Efficiency Clutch Time Percentage - Despite his impact on Zalgiris game, Brandon Davies rarely participate in clutch conditions This index indicates if coaching staff trusts this player during clutch time, and if so, if an increase in his playing time leads to ending up winning that game. Clutch Time FG% - Aaron White appear to be the most efficient player during clutch conditions (not including outliers) This index indicates FG% players efficiency during clutch time. Players with high FGM% or +/- during clutch time, should spend more time on floor during clutch time 16

19 Team Performance

20 Team Performance Opponent s Difference Opponent s difference from average In the majority of the categories, Zalgiris performs worse that its opponents. Strong point for Zalgiris is rebounding & weak point appears to be assists. This index demonstrates the difference between opponent s performance and Zalgiris Kaunas in a series of statistical categories. For most of categories, this index should have a negative value. This way the coaching staff could know if team succeeded in keeping opponent below its average and moreover, which are its strengths and weaknesses. 18

21 Team Performance Index +/- considering different heights +/- Index when Taller/Shorter/Same Height Zalgiris performs better when its line-up is at the same height with the opponent. When its line-up is taller than the opponent, then it faces difficulties to get a positive result. Overall, shorter line-ups work better for Zalgiris. Team +/- index when average height lineup on floor is greater, less or same as opponent s. This index can help to determine if team is expected to perform better or worse when any of the previous conditions is going to occur. Negative values in any of those 3 categories could mean that a higher or shorter lineup should maybe be deployed. 19

Team Performance Offensive vs Defensive Efficiency (1) Defense vs G/SF/PF and C Zalgiris weakest point in defense was its SF (extracted by season average) This index indicates FG% of opponent s

Second Chance Points and Offensive Efficiency - Zalgiris scored approximately 1.02 points per possession, but only 0.83 points per second chance possession.

22 Team Performance Offensive vs Defensive Efficiency (1) Defense vs G/SF/PF and C Zalgiris weakest point in defense was its SF (extracted by season average) This index indicates FG% of opponent s players playing in each of those positions. By analyzing the relevant results, coaching staff can get useful insight about the strongest position in terms of defense. Second Chance Points and Offensive Efficiency - Zalgiris scored approximately 1.02 points per possession, but only 0.83 points per second chance possession. This index indicates teams scoring efficiency after grabbing an offensive rebound. Zalgiris scored 244 second chance points in total from 293 offensive rebounds, and its average offensive efficiency was If you mean zero value for offensive efficiency, it means 0 points scored per 100 possessions. 20

Team Performance Offensive vs Defensive Efficiency (2) Opponent s difference from average, 2FG% and 3FG% - Zalgiris kept each opponent below its 3FG% average just in 12 games.

Taking into consideration that the relevant value for 2FG% was -0.76% and that Zalgiris won only half of the games that opponent shot above its average beyond the arc.

23 Team Performance Offensive vs Defensive Efficiency (2) Opponent s difference from average, 2FG% and 3FG% - Zalgiris kept each opponent below its 3FG% average just in 12 games. At first look, its defence in 3-point range could not be considered amongst team s strengths. This is also underlined by the season average value (+1.04%). Taking into consideration that the relevant value for 2FG% was -0.76% and that Zalgiris won only half of the games that opponent shot above its average beyond the arc. Offensive/Defensive Efficiency Zalgiris averaged more than 1 point per possession in 16 out of 30 games. Respectively, it conceded more than 1 point per possession only in 11 out of 30 games. An estimation of total points scored per 100 possessions. It is very useful for preparation when compared with opponent s average defensive/offensive efficiency. 21

Team Performance Fast Breaks from Steals & Turnovers Steals Conversion Rate In 16 games, Zalgiris perform better than team s season average (steal conversion rate = 59) This

Turnovers - Zalgiris averaged 13.4 turnovers per game, leading the league this year. However, in terms of turnovers ending up to opponent s steals Zalgiris is ranked 8 th.

24 Team Performance Fast Breaks from Steals & Turnovers Steals Conversion Rate In 16 games, Zalgiris perform better than team s season average (steal conversion rate = 59) This index indicates FG% of fast-break attempts coming from steals. High values (usually above 50-60%) reveal that team is quite efficient at converting steals into points. Turnovers - Zalgiris averaged 13.4 turnovers per game, leading the league this year. However, in terms of turnovers ending up to opponent s steals Zalgiris is ranked 8 th. This index indicates team s level of concentration during the game. High values (usually above 10) reveal that players are not concentrated and potentially give easy baskets to their opponents. 22

Team Performance Team Pace & Lead Percentage Team Pace - Zalgiris team pace ranges from 64 to 80, with an average of 69.

25 Team Performance Team Pace & Lead Percentage Team Pace - Zalgiris team pace ranges from 64 to 80, with an average of It is evident therefore that Zalgiris is expected to perform better in slow paced games. Total number of possessions. A possession ends when a field goal/free throw is made or a turnover is committed. The most useful conclusion that can be extracted from this index is whether slow, normal or fast pace is better for the team to win a game. Lead Percentage - Zalgiris led the score in 45.03% of total playing time. Although, this number is lower than 50%, it managed to win 18 out of 30 games. Total percentage of playing time that team was leading the score. It indicates whether team is able to maintain the lead it has and eventually win a game, or if it can also do a comeback and win a game where it was not leading for many minutes. 23

Team Performance Clutch Time Player Selection +/- Index During Clutch Time, Combination of 2 Players K.Pangos & P.Jankunas was the best 2-player combination during clutch time. A.Milaknis & E.

This way, coaching staff could know which players form a better combination and can cover each other s weaknesses.

26 Team Performance Clutch Time Player Selection +/- Index During Clutch Time, Combination of 2 Players K.Pangos & P.Jankunas was the best 2-player combination during clutch time. A.Milaknis & E.Ulanovas, had the worst +/- clutch time index The purpose of this index is to provide a clear idea about the best combinations in 2 different positions that can be deployed during clutch time (e.g. PG and C). This way, coaching staff could know which players form a better combination and can cover each other s weaknesses. +/- Index During Clutch Time, Combination of 5 Players Clutch time line-up should consist of Pangos-Micic-Ulanovas- White-Jankunas This is the most advanced and useful +/- index during clutch time. It is a direct way to determine which lineup has the best team chemistry and is more likely to perform better. 24

27 Conclusion This report was exclusively focused to in-game season performance analysis of Zalgiris Kaunas. Our Data science team can also handle various other advanced requests in order to satisfy the needs of every team which strives to success. Those services include, but are not limited to: Thorough analysis of specific player with his strengths and weaknesses. In-Game Performance in various conditions (e.g. home/away games, during different time periods etc.). Parametrization of indexes (using various filters such as game quarter or scoring margin). Correlation between indexes and different sources. Analyzing opponent's performance and creating tactical and athletic scouting reports. Analyzing the full potential of the current squad and prepare specific transfer consulting services

Intelligence as a service to identify the future stars!

Project Bundesliga Season Analysis Sample

Project Bundesliga Season Analysis Sample Project 04 2017-18 Bundesliga Season Analysis Sample Company Overview Statathlon provide coaches with Strategic, Tactical and Technical Performance Analysis pre- and post-game. We also assist young athletes