Validity and reliability of a player-tracking device to identify movement orientation in team sports

Author(s):  
Justin H.Y. Tan ◽  
Ted Polglaze ◽  
Peter Peeling
PLoS ONE ◽  
2018 ◽  
Vol 13 (2) ◽  
pp. e0191823 ◽  
Author(s):  
Daniel P. Nicolella ◽  
Lorena Torres-Ronda ◽  
Kase J. Saylor ◽  
Xavi Schelling

2018 ◽  
Vol 6 (8) ◽  
pp. 149 ◽  
Author(s):  
Şehmus Aslan

The purpose of this study was to compare the level of cognitive flexibility of individual and team athletes who are students. The study included a total of 237 volunteer athletes, comprising 140 males (59.1%) and 97 females (40.9%) with a mean age of 18.98 ± 2.18 years (range, 16-26 years) who were licensed to participate in individual and team sports. Study data were collected using the Cognitive Flexibility Scale developed by Martin and Rubin (1995), which consists of 12 items in total. International validity and reliability studies were conducted by Martin and Rubin, and Turkish validity and reliability studies were conducted by Çelikkaleli on high school students (Çelikkaleli, 2014). The scores of the Cognitive Flexibility Scale were found to be higher in the team sports athletes compared with the individual sports athletes (p<0.05). No difference was determined between the levels of cognitive flexibility in male and female athletes. The results indicated that the cognitive flexibility levels of team athletes are higher than those of individual athletes.


2012 ◽  
Vol 44 (4) ◽  
pp. 1108-1114 ◽  
Author(s):  
Thuraiappah Sathyan ◽  
Richard Shuttleworth ◽  
Mark Hedley ◽  
Keith Davids

2020 ◽  
Vol 23 (1) ◽  
pp. 7-14 ◽  
Author(s):  
Curtis L. Tomasevicz ◽  
Ryan M. Hasenkamp ◽  
Daniel T. Ridenour ◽  
Christopher W. Bach

2020 ◽  
Author(s):  
José Pino-Ortega ◽  
Markel Rico-González

The use of valid, accurate and reliable systems is fundamental to warrant a high-quality data collection and interpretation. In 2015, FIFA created a department of Electronic Performance and Tracking systems, collecting under this name the more used tracking systems in team sport setting: high-definition cameras, Global Positioning Systems, and Local Positioning Systems. To date, LPS systems proved to be valid and accurate in determining the position and estimating distances and speeds. However, it is hypothesized that between LPS, ultra-wide band (UWB) is the most promising technology for the future. Thus, this chapter was aimed to make an update about UWB technology in sport: the FIFA’s regulation, manufacturer that provide this technology, the research articles that assessed validity and reliability of UWB technology, and the criteria standard for the use of this technology.


2019 ◽  
Vol 10 (1) ◽  
pp. 24 ◽  
Author(s):  
Changjia Tian ◽  
Varuna De Silva ◽  
Michael Caine ◽  
Steve Swanson

The use of machine learning to identify and classify offensive and defensive strategies in team sports through spatio-temporal tracking data has received significant interest recently in the literature and the global sport industry. This paper focuses on data-driven defensive strategy learning in basketball. Most research to date on basketball strategy learning has focused on offensive effectiveness and is based on the interaction between the on-ball player and principle on-ball defender, thereby ignoring the contribution of the remaining players. Furthermore, most sports analytical systems that provide play-by-play data is heavily biased towards offensive metrics such as passes, dribbles, and shots. The aim of the current study was to use machine learning to classify the different defensive strategies basketball players adopt when deviating from their initial defensive action. An analytical model was developed to recognise the one-on-one (matched) relationships of the players, which is utilised to automatically identify any change of defensive strategy. A classification model is developed based on a player and ball tracking dataset from National Basketball Association (NBA) game play to classify the adopted defensive strategy against pick-and-roll play. The methodology described is the first to analyse the defensive strategy of all in-game players (both on-ball players and off-ball players). The cross-validation results indicate that the proposed technique for automatic defensive strategy identification can achieve up to 69% accuracy of classification. Machine learning techniques, such as the one adopted here, have the potential to enable a deeper understanding of player decision making and defensive game strategies in basketball and other sports, by leveraging the player and ball tracking data.


2018 ◽  
Vol 8 (3) ◽  
pp. 139 ◽  
Author(s):  
Recep Gorgulu ◽  
Ender Senel ◽  
İlhan Adilogulları ◽  
Mevlut Yildiz

This multi-study paper reports the translation process and the validity and reliability analysis of the Characteristics of Resilience in Sports Teams Inventory (CREST) for the use of Turkish population. In three related studies, 414 team sports athletes from Turkey were sampled. We adopted Beaton et al.’s (2000) methodology for the translation of self-report measures for cross-cultural adaption studies. The first study provided content validity for an initial item set as the preliminary study. The second study explored the factor analysis of the CREST structure. The third study explored re-testing of the explored structure in a different set of participants and criterion-related validity provided. The analysis of Study 1 revealed that the items were understood by the participants and ready for application for the general Turkish population. The exploratory factor analysis in the Study 2 revealed that the CREST had two sub-dimensions as it was in the original inventory. The Cronbach’s alpha values for the dimensions of demonstrating resilience characteristics and vulnerabilities shown under pressure were 0.94 and 0.90, respectively. The Kaiser-Meyer-Olkin value was 0.94. The confirmatory factor analysis in the third study showed that the structure of the inventory was confirmed in another sports context. Accordingly, the CREST is a valid and reliable tool for use by Turkish athletes and to measure team resilience that is one of the critical determinants of team performance. Further understanding of team resilience as a process can be gain by using the CREST, especially in future process-oriented research for team sports.


2014 ◽  
Vol 32 (17) ◽  
pp. 1639-1647 ◽  
Author(s):  
James Rhodes ◽  
Barry Mason ◽  
Bertrand Perrat ◽  
Martin Smith ◽  
Victoria Goosey-Tolfrey

Author(s):  
José Pino-Ortega ◽  
José M Oliva-Lozano ◽  
Petrus Gantois ◽  
Fábio Yuzo Nakamura ◽  
Markel Rico-González

Given the accuracy in data collection, radar-based local positioning systems (LPS) are a promising technology to monitor training load in team sports. The objective of this study was to systematically review articles that compare the validity and reliability of LPS to other electronic performance and tracking system (EPTS) in team sports. The authors searched three electronic databases (SPORTDiscus, PubMed, and Web of Science) to identify relevant studies published by October 21, 2019. A Boolean search was performed, including sport ( population), search terms related to intervention technology ( intervention technology), and outcome measures of the technology ( outcomes). Seven studies evaluated the validity and reliability of LPS in team sports in comparison with other EPTS, including semi-automatic video technology (VID) and Global Positioning System (GPS). Two articles compared LPS to VID, three articles compared LPS to GPS, and two articles compared LPS to both GPS and VID. LPS is considered a valid and reliable EPTS in the field of load monitoring of team sports, usually resulting in higher accuracy than VID or GPS. However, special care should be taken when analyzing load indicators at high speeds or different trajectories, since the validity and reliability depend on the EPTS itself.


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