5.3 Compare Players

Eindhoven University of Technology MASTER Finding "Memphis" a rating-based player comparison visualisation Wang, Y. Award date: 2016 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain Department of Mathematics and Computer Science Visualization Group Finding "Memphis" - a rating-based player comparison visualization Master Thesis Yujie Wang Supervisors: dr.ir. Huub van de Wetering Eindhoven, October 2016 Abstract With the development of sensor and camera tracking systems, it becomes easier to track player events in a football match. With these match events, post-match analysis on players can be con- ducted to compare the performance of players. Comparing football players is not an easy task, there are many attributes to be covered. Typ- ical attributes are player positions and statistics. For instance, common statistics are number of goals, number of assists, etcetera. There are many tools that can compare football players by listing all the statistics side by side for all players. Imagine we want to compare 10 different statistics for over 500 players simultaneously, and we also want to find out the 10 best players. Or sometimes, the user may want to find players that are similar to a target player, for instance, Memphis Depay. Simply listing the statistics is not the solution to such problems. To solve such problems, we designed a prototype visualization tool, called PureSoccerFX. In our tool, we give the user the flexibility to define the key attributes of interest by introducing a so called interactive weighted attribute tree. This tree allows the user to create abstraction levels from real statistics and interactively build their own rating system by manipulating the hierarchical weighted attribute tree. With this tree, each player will get a rating and the user can simply compare this rating to find top players. We also apply a modified strip treemap to visualize the rating of these players based on the weighted attribute tree, which provides the user with an overview of all players in the league. To help the user find similar players, We designed a player similarity graph that can compare player similarity and rating simultaneously. At last, we designed a player comparison view for the user to easily compare players from different attributes and make the final conclusion on who are the most wanted players. Finding "Memphis" - a rating-based player comparison visualization iii Acknowledgements First of all, I would like to thank my supervisor, dr.ir Huub van de Wetering for providing me the opportunity to do a football related thesis project. His insightful comments have helped me all the way through the project, I would not be able to finish this thesis project without his guidance. I would also like to thank my thesis committee members: prof.dr.ir. Jack van Wijk and dr. Natalia Sidorova. Without their help, I would not be able to make the defense in time. I want to thank my family and all my friends who always encourage and support me. I enjoy the moments sharing joy and happiness with you. Last but not least, special credits to football! Football is my passion. "Football, bloody hell." - Sir Alex Ferugson Finding "Memphis" - a rating-based player comparison visualization v Contents Contents vii List of Figures ix List of Tables xiii 1 Introduction 1 1.1 Motivation and goal...................................1 1.2 Problem formulation...................................2 1.2.1 Visualize comparison...............................2 1.2.2 Related questions.................................3 1.3 Methodology and contribution.............................4 1.4 Organization of this thesis................................4 2 Background and related work5 2.1 Football data analysis..................................5 2.1.1 Statistic......................................5 2.1.2 Rating.......................................7 2.2 Football specific visualization techniques........................9 2.2.1 Formation.....................................9 2.2.2 Attacking sides.................................. 10 2.2.3 Event frequency................................. 11 2.3 High-dimensional data visualization techniques.................... 12 2.3.1 Non-hierarchical data.............................. 12 2.3.2 Hierarchical data................................. 14 2.4 Comparison specific visualization techniques...................... 17 2.4.1 Juxtaposition................................... 17 2.4.2 Superposition................................... 18 2.4.3 Explicit encoding................................. 18 3 Data processing 19 3.1 Data description..................................... 19 3.1.1 Feature description................................ 19 3.1.2 Identify statistics from events.......................... 19 3.2 Data model........................................ 21 3.3 Generate statistic..................................... 23 3.3.1 Accumulated statistic.............................. 23 3.3.2 Averaged statistic................................ 23 3.4 Generate single statistic rating............................. 24 3.5 Weighted attribute tree................................. 25 3.5.1 Compute rating with a weighted attribute tree................ 26 3.5.2 Generate player specific weights......................... 27 Finding "Memphis" - a rating-based player comparison visualization vii CONTENTS 4 System design 29 4.1 Dashboard......................................... 29 4.2 Select player........................................ 29 4.3 Interactive weighted attribute tree........................... 31 4.3.1 Tree view - detail control............................ 32 4.3.2 Icicle plot - weight control............................ 34 4.4 Player performance treemap............................... 35 4.4.1 Interaction.................................... 36 4.4.2 Color encoding.................................. 37 4.4.3 Compare players in treemap........................... 38 4.5 Player similarity graph.................................. 40 4.5.1 Visual design of player similarity graph.................... 41 4.5.2 Interaction with player similarity graph.................... 42 4.6 Player detail view..................................... 46 4.7 Player comparison view................................. 46 5 Results and evaluation 49 5.1 Find best players..................................... 49 5.2 Find similar players to a target player......................... 50 5.3 Compare Players..................................... 54 5.3.1 Compare players in player performance treemap............... 54 5.3.2 Compare players in player comparison view.................. 54 6 Conclusions 59 6.1 Main conclusion..................................... 59 6.2 Limitation......................................... 59 6.3 Future work........................................ 60 Bibliography 61 Appendix 63 A Details on filter 63 A.1 Filter........................................... 63 A.1.1 Range slider.................................... 64 A.1.2 Scatter plot matrix................................ 64 A.1.3 Position zone filter................................ 65 B Player statistics table 66 B.1 Player statistics table.................................. 66 C Compute stacked bar width 67 D Heatmap design 69 D.0.1 Event heatmap vs average position graph................... 69 viii Finding "Memphis" - a rating-based player comparison visualization List of Figures 1.1 MLB team salaries [27]..................................2 1.2 Process graph on visualizing football data.......................3 2.1 Shooting statistics shown with visualization [23]....................5 2.2 Football statistics shown textually [20].........................6 2.3 Top 10 goal scorer ranking of Eredivisie for the season 2014-2015 [24]........6 2.4 Top 20 players of the English Premiere League for the season 2008-2009 [12]....9 2.5 Initial formation for match Manchester United vs Crystal Palace (numbers inside the circles are player ratings, which are not related to formation) [23]........ 10 2.6 Average position for match Manchester United vs Crystal Palace [23]........ 10 2.7 Attacking sides for match Manchester United vs Crystal Palace [23]........ 10 2.8 Heat map example.................................... 11 2.9 Color map example.................................... 11 2.10 Example ball occupancy map over a match half for a team attacking left to right [2] 12 2.11 Percentage of the population living in urban areas in the world and in different continents [13]....................................... 12 2.12 An example of a stacked bar chart............................ 13 2.13 An example

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