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E-grāmata: Match Analysis: How to Use Data in Professional Sport [Taylor & Francis e-book]

Edited by (German Sport University Cologne, Germany)
  • Formāts: 282 pages, 5 Tables, black and white; 23 Line drawings, black and white; 6 Halftones, black and white; 29 Illustrations, black and white
  • Izdošanas datums: 15-Nov-2021
  • Izdevniecība: Routledge
  • ISBN-13: 9781003160953
  • Taylor & Francis e-book
  • Cena: 155,64 €*
  • * this price gives unlimited concurrent access for unlimited time
  • Standarta cena: 222,34 €
  • Ietaupiet 30%
  • Formāts: 282 pages, 5 Tables, black and white; 23 Line drawings, black and white; 6 Halftones, black and white; 29 Illustrations, black and white
  • Izdošanas datums: 15-Nov-2021
  • Izdevniecība: Routledge
  • ISBN-13: 9781003160953

Match Analysis is the first book to examine this topic through three types of data sets; video, event, and position data and show how to interpret this data and apply the findings for better team and individual sport performance.



Match analysis is a performance diagnostic procedure, which can be used to carry out systematic gaming analysis during competition and training. The analysis of team and racket sports, whether in competition, for opponent preparation (match plan), follow-up, or training is nowadays indispensable in many sports games at different levels.

This analysis nevertheless presents many open questions and problem areas; which data should be used? who manages the data? Who provides whom with which information? How is this information presented, digested, and applied? The more complex and anonymous the data management is, the more commercial, expensive, and uncontrollable information management and provision becomes.

Match Analysis: How to Use Data in Professional Sport

is the first book to examine this topic through three types of data sets; video, event, and position data and show how to interpret this data and apply the findings for better team and individual sport performance.

This innovative new volume is key reading for researchers, students, and practitioners alike in the fields of Coaching, Performance Analysis, Sport Management and related specific sport disciplines.

List of Figures
viii
List of Tables
x
List of Contributors
xi
PART I Introduction
1(42)
1 Match Analysis in 2020
3(11)
Daniel Memmert
2 History of Match Analysis
14(9)
Jurgen Buschtnann
3 Match Analysis in Practice: Football
23(10)
Stepkan Nopp
4 Match Analysis in Practice: Beach Volleyball
33(10)
Daniel Link
PART II Match Analysis on the Basis of Video Data
43(114)
5 Match Analysis in American Football
45(8)
Peter Anderson
6 Match Analysis in Basketball
53(8)
Stefan Konig
Jan Heckel
7 Match Analysis in Cricket
61(7)
Saumya Mehta
John van der Kamp
8 Match Analysis in Field Hockey
68(9)
Anne Krause
Wolfgang Hillmann
9 Opponent Analysis in Football
77(10)
Lukas Plener
10 Visual Scanning in Football
87(8)
Marius Pokolm
11 Match Analysis in Ice Hockey
95(7)
Karl Schwarzenbrunner
12 Match Analysis in Rugby
102(10)
Sharief Hendricks
13 Match Analysis in Squash
112(8)
Eric Zillmer
Nyree Dardarian
14 Match Analysis in Table Tennis
120(9)
Timo Klein-Soetebter
Gunter Straub
15 Match Analysis in Team Handball
129(7)
Frowin Fasold
16 Match Analysis in Tennis
136(10)
Philipp Born
Tobias Vogt
17 Match Analysis in Volleyball
146(11)
Stefanie Klatt
PART III Match Analysis on the Basis of Event Data
157(30)
18 KPIs on the Basis of Match Events Data
159(9)
Marc Garnica-Caparros
19 Scouting
168(10)
Markus Brunnschneider
Maximilian Hahn
20 Normalizing KPIs Based on Possession
178(9)
Ashwin Phatak
PART IV Match Analysis on the Basis of Position Data
187(60)
21 Model-Based Performance Analysis in Football
189(8)
Jurgen Perl
22 Collective Tactical Behaviours in Football
197(16)
Benedict Low
23 KPIs in the German Bundesliga
213(8)
Dominik Raabe
24 Collective Behavior in Football
221(9)
Rui Marcelino
Jaime Sampaio
Guy Amichay
Bruno Goncalves
Iain D. Couzin
Mate Nagy
25 Applying Machine Learning in Football: The Identification of Counterpressing in Football
230(8)
Gabriel Anzer
Pascal Bauer
Oliver Hbner
26 Physical KPIs
238(9)
Maximilian Klemp
PART V Outlook
247(32)
27 Communication of Match Analysis
249(10)
Philip Furley
28 Limits of Match Analysis
259(9)
Fabian Wunderlich
29 Match Analysis in 2030
268(11)
Robert Rein
Index 279
Daniel Memmert is Professor and Executive Head of the Institute of Exercise Training and Sport Informatics at the German Sport University Cologne, Germany, with a visiting assistant professorship 2014 at the University of Vienna (Austria). His awarded research is focused on human movement science, sport psychology, and computer science in sports. According to a publicly accessible database of the world's top 100,000 scientists (https://data.mendeley.com/datasets/btchxktzyw/2), he ranks first in Germany in the field of "Sport Science". He has received more than 7 million in external funding from research councils, has an H-index of 51 (i10-Index 149), has authored or co-authored more than 200 peer-reviewed publications, 20 books, and 30 book chapters, and has given more than 100 invited talks, 100 scientific talks on conferences, and more than 200 teaching courses for PE teachers and trainers.