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Special Issue: Selected papers presented at the 12th Symposium of the Section Computer Science in Sport of the German Association of Sport Science (September 4.-7., 2018)

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Volume 15 (2016): Issue 2 (December 2016)

Volume 15 (2016): Issue 1 (July 2016)

Journal Details
Format
Journal
eISSN
1684-4769
First Published
16 Apr 2016
Publication timeframe
2 times per year
Languages
English

Search

Volume 15 (2016): Issue 1 (July 2016)

Journal Details
Format
Journal
eISSN
1684-4769
First Published
16 Apr 2016
Publication timeframe
2 times per year
Languages
English

Search

4 Articles
Open Access

Intra-seasonal Variability of Ball Speed and Coordination of Two Team-Handball Throwing Techniques in Elite Male Adolescent Players.

Published Online: 27 Jul 2016
Page range: 1 - 21

Abstract

Abstract

In sports biomechanics and motor control, a thorough study of coordination variability is important to understanding how the human movement system is organized. From a more applied sport science perspective, knowledge about performance variability is essential regarding the evaluation of true sport specific effects of any intervention. While there are many reports of intervention studies in team-handball, no description of the amount of normal variability is available. This study investigated variability of two important throwing techniques in team-handball within elite junior players over a 4-month period during a competitive season. To evaluate ball speed variability, the intra-individual coefficient of variation was calculated. The 95th percentile of ball speed variability over all players was 7%, which can be used as an effect size estimate in future research. For coordination variability, a qualitative description based on the output of neural networks was used. All participants presented multiple coordination patterns, representing multi-stability on a month-to-month timescale and switched between stable states without the manipulation of any control variable. Some limitations in the methodology and applications of neural networks in the present study and in biomechanics and motor control in general are highlighted. When more researchers adopt these methodologies, a more coherent framework for their application can emerge.

Keywords

  • TEAM-HANDBALL
  • BIOMECHANICS
  • COORDINATION DYNAMICS
  • ATTRACTOR DIAGRAM
  • SELF-ORGANIZING MAPS
Open Access

Performance Analysis in Table Tennis - Stochastic Simulation by Numerical Derivation

Published Online: 27 Jul 2016
Page range: 22 - 36

Abstract

Abstract

The aim of this study was to identify the impact of different tactical behaviors on the winning probability in table tennis. The performance analysis was done by mathematical simulation using a Markov chain model. 259 high-level table tennis games were evaluated by means of a new simulation approach using numerical derivation to remove the necessity to perform a second modeling step in order to determine the difficulty of tactical behaviors. Based on the derivation, several mathematical constructs like directional derivations and the gradient are examined for application in table tennis. Results reveal errors and long rallies as the most influencing game situations, together with the positive effect of risky play on the winning probability of losing players.

Keywords

  • MARKOV CHAIN
  • PERFORMANCE ANALYSIS
  • TABLE TENNIS
  • SIMULATION
  • NUMERICAL ANALYSIS
Open Access

Predictive models of the 2015 Rugby World Cup: accuracy and application

Published Online: 27 Jul 2016
Page range: 37 - 58

Abstract

Abstract

The current investigation compared 12 models of outcomes of international rugby union matches and then used the most accurate model to investigate performances within the 2015 Rugby World Cup. The underlying linear regression models were used within a simulation package that introduced random variability about performance evidenced by the residual distribution of the regression analyses. Each model was used within 10,000 simulations of the 2015 Rugby World Cup from which match outcome and team progression statistics were recorded. The most accurate model with respect to the actual 2015 tournament was developed using data from all seven previous tournaments rather than restricting cases to the most recent three tournaments. The model was more accurate when the data used violated the assumptions of linear regression rather than transforming variables to satisfy the assumptions. The model included World ranking points as a predictor variable and was more accurate than corresponding models that represented relative home advantage as well. The most accurate model used separate models for the pool and knockout stage matches although the 9 models that separating these match types were less accurate on average than when the two match types were considered together. This model was used to investigate properties of the 2015 Rugby World Cup. The tournament disadvantaged three teams in the World’s top 5 who were drawn in the same pool. Teams ranked in the World’s top 7 did not perform as well as predicted while teams ranked 16th and below performed better than predicted suggesting that the strength in depth in international rugby union is increasing. There was a small effect of having additional recovery days from the previous match compared to the opponents which was worth 4.1 points. The information produced by this research should be considered by those design tournaments such as the Rugby World Cup.

Keywords

  • VENUE EFFECTS
  • RECOVERY
  • REGRESSION
  • SIMULATION
Open Access

Computer Science in Sport – Research and Practice: A book review

Published Online: 27 Jul 2016
Page range: 59 - 63

Abstract

Abstract

Sports informatics and computer science in sport are perhaps the most exciting and fast-moving disciplines across all of sports science. The tremendous parallel growth in digital technology, non-invasive sensor devices, computer vision and machine learning have empowered sports analytics in ways perhaps never seen before. This growth provides great challenges for new entrants and seasoned veterans of sports analytics alike. Keeping pace with new technological innovations requires a thorough and systematic understanding of many diverse topics from computer programming, to database design, machine learning algorithms and sensor technology. Nevertheless, as quickly as the state of the art technology changes, the foundation skills and knowledge about computer science in sport are lasting. Furthermore, resources for students and practitioners across this range of areas are scarce, and the new-release textbook Computer Science in Sport: Research and Practice edited by Professor Arnold Baca, provides much of the foundation knowledge required for working in sports informatics. This is certainly a comprehensive text that will be a valuable resource for many readers.

Keywords

  • COMPUTER SCIENCE
  • INFORMATICS
  • REVIEW
  • ANALYTICS
4 Articles
Open Access

Intra-seasonal Variability of Ball Speed and Coordination of Two Team-Handball Throwing Techniques in Elite Male Adolescent Players.

Published Online: 27 Jul 2016
Page range: 1 - 21

Abstract

Abstract

In sports biomechanics and motor control, a thorough study of coordination variability is important to understanding how the human movement system is organized. From a more applied sport science perspective, knowledge about performance variability is essential regarding the evaluation of true sport specific effects of any intervention. While there are many reports of intervention studies in team-handball, no description of the amount of normal variability is available. This study investigated variability of two important throwing techniques in team-handball within elite junior players over a 4-month period during a competitive season. To evaluate ball speed variability, the intra-individual coefficient of variation was calculated. The 95th percentile of ball speed variability over all players was 7%, which can be used as an effect size estimate in future research. For coordination variability, a qualitative description based on the output of neural networks was used. All participants presented multiple coordination patterns, representing multi-stability on a month-to-month timescale and switched between stable states without the manipulation of any control variable. Some limitations in the methodology and applications of neural networks in the present study and in biomechanics and motor control in general are highlighted. When more researchers adopt these methodologies, a more coherent framework for their application can emerge.

Keywords

  • TEAM-HANDBALL
  • BIOMECHANICS
  • COORDINATION DYNAMICS
  • ATTRACTOR DIAGRAM
  • SELF-ORGANIZING MAPS
Open Access

Performance Analysis in Table Tennis - Stochastic Simulation by Numerical Derivation

Published Online: 27 Jul 2016
Page range: 22 - 36

Abstract

Abstract

The aim of this study was to identify the impact of different tactical behaviors on the winning probability in table tennis. The performance analysis was done by mathematical simulation using a Markov chain model. 259 high-level table tennis games were evaluated by means of a new simulation approach using numerical derivation to remove the necessity to perform a second modeling step in order to determine the difficulty of tactical behaviors. Based on the derivation, several mathematical constructs like directional derivations and the gradient are examined for application in table tennis. Results reveal errors and long rallies as the most influencing game situations, together with the positive effect of risky play on the winning probability of losing players.

Keywords

  • MARKOV CHAIN
  • PERFORMANCE ANALYSIS
  • TABLE TENNIS
  • SIMULATION
  • NUMERICAL ANALYSIS
Open Access

Predictive models of the 2015 Rugby World Cup: accuracy and application

Published Online: 27 Jul 2016
Page range: 37 - 58

Abstract

Abstract

The current investigation compared 12 models of outcomes of international rugby union matches and then used the most accurate model to investigate performances within the 2015 Rugby World Cup. The underlying linear regression models were used within a simulation package that introduced random variability about performance evidenced by the residual distribution of the regression analyses. Each model was used within 10,000 simulations of the 2015 Rugby World Cup from which match outcome and team progression statistics were recorded. The most accurate model with respect to the actual 2015 tournament was developed using data from all seven previous tournaments rather than restricting cases to the most recent three tournaments. The model was more accurate when the data used violated the assumptions of linear regression rather than transforming variables to satisfy the assumptions. The model included World ranking points as a predictor variable and was more accurate than corresponding models that represented relative home advantage as well. The most accurate model used separate models for the pool and knockout stage matches although the 9 models that separating these match types were less accurate on average than when the two match types were considered together. This model was used to investigate properties of the 2015 Rugby World Cup. The tournament disadvantaged three teams in the World’s top 5 who were drawn in the same pool. Teams ranked in the World’s top 7 did not perform as well as predicted while teams ranked 16th and below performed better than predicted suggesting that the strength in depth in international rugby union is increasing. There was a small effect of having additional recovery days from the previous match compared to the opponents which was worth 4.1 points. The information produced by this research should be considered by those design tournaments such as the Rugby World Cup.

Keywords

  • VENUE EFFECTS
  • RECOVERY
  • REGRESSION
  • SIMULATION
Open Access

Computer Science in Sport – Research and Practice: A book review

Published Online: 27 Jul 2016
Page range: 59 - 63

Abstract

Abstract

Sports informatics and computer science in sport are perhaps the most exciting and fast-moving disciplines across all of sports science. The tremendous parallel growth in digital technology, non-invasive sensor devices, computer vision and machine learning have empowered sports analytics in ways perhaps never seen before. This growth provides great challenges for new entrants and seasoned veterans of sports analytics alike. Keeping pace with new technological innovations requires a thorough and systematic understanding of many diverse topics from computer programming, to database design, machine learning algorithms and sensor technology. Nevertheless, as quickly as the state of the art technology changes, the foundation skills and knowledge about computer science in sport are lasting. Furthermore, resources for students and practitioners across this range of areas are scarce, and the new-release textbook Computer Science in Sport: Research and Practice edited by Professor Arnold Baca, provides much of the foundation knowledge required for working in sports informatics. This is certainly a comprehensive text that will be a valuable resource for many readers.

Keywords

  • COMPUTER SCIENCE
  • INFORMATICS
  • REVIEW
  • ANALYTICS

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