Local Positioning Systems in (Game) Sports

Leser, Roland; Baca, Arnold; Ogris, Georg

doi:10.3390/s111009778

Cited by 80 publications

(76 citation statements)

References 76 publications

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“…Tactical analyses of performance, whether at the individual or collective levels, are of interest to coaches and sport researchers [5]. However, the lack of knowledge about advanced methods to analyse the dynamics of football players (space-time series) is responsible for the lack of studies focusing on the tactical performance of football matches [3].…”

Section: Introductionmentioning

confidence: 99%

“…Scientific areas, such as engineering and mathematics, have been interested in providing their insights to further understand this sport in the last few years. The major contribution of mathematical tools resides in the field of human movement analysis with fast and efficient systems, providing quantitative measures to sports coaches [5]. Nevertheless, the technological devices and related methods should always be applied considering the aim of the analysis.…”

Section: Introductionmentioning

confidence: 99%

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Dynamical Stability and Predictability of Football Players: The Study of One Match

Couceiro

Clemente

Martins

et al. 2014

Entropy

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Abstract:The game of football demands new computational approaches to measure individual and collective performance. Understanding the phenomena involved in the game may foster the identification of strengths and weaknesses, not only of each player, but also of the whole team. The development of assertive quantitative methodologies constitutes a key element in sports training. In football, the predictability and stability inherent in the motion of a given player may be seen as one of the most important concepts to fully characterise the variability of the whole team. This paper characterises the predictability and stability levels of players during an official football match. A Fractional Calculus (FC) approach to define a player's trajectory. By applying FC, one can benefit from newly OPEN ACCESSEntropy 2014, 16 646 considered modeling perspectives, such as the fractional coefficient, to estimate a player's predictability and stability. This paper also formulates the concept of attraction domain, related to the tactical region of each player, inspired by stability theory principles. To compare the variability inherent in the player's process variables (e.g., distance covered) and to assess his predictability and stability, entropy measures are considered. Experimental results suggest that the most predictable player is the goalkeeper while, conversely, the most unpredictable players are the midfielders. We also conclude that, despite his predictability, the goalkeeper is the most unstable player, while lateral defenders are the most stable during the match.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamical Stability and Predictability of Football Players: The Study of One Match

Couceiro

Clemente

Martins

et al. 2014

Entropy

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show abstract

“…[6], and SportVU ® [7]. We can also find in the literature examples that explore some aspects of the project, like spatial and spatiotemporal analysis [8], local positioning systems in the game [9], and analysis of football strategies [10], [11] and [12].…”

Section: Introductionmentioning

confidence: 99%

Open Source Technologies Involved in Constructing a Web-Based Football Information System

Rodrigues

Belguinha

Gomes

et al. 2013

Advances in Intelligent Systems and Computing

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Abstract. The current information systems and match analysis software associated to professional football output a huge amount of statistics. Many football professionals are particularly interested in real time information about the tactical plan occurring during the match, and the relations between that information and what was prepared in the training sessions. It is fundamental to have on the bench, and on-the-fly, the most relevant information each time they have to take a decision. In this paper, we present a set of open source technologies involved in building a multi-platform web based integrated football information system, supported in three main modules: user interfaces, databases, and the tactical plan detection and classification. We show that the selected technologies are suitable for those modules, allowing field occurrences to trigger meaningful information.

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“…In many cases, such trajectories are recorded by mobile phones with self-locating functionality [4] or cameras [5], but in specific local scenarios indoor positioning systems are applied [6]. These spatial sensors generate time series of coordinates which were analyzed for activity information [7].…”

Section: Introductionmentioning

confidence: 99%

“…1). It is a local position measurement (LPM) system developed for field sports [6] and can determine the positions of moving objects in real time. This system achieves an accuracy which is superior to GPS and specified by the manufacturer with a standard deviation of 2 cm [22].…”

Section: Introductionmentioning

confidence: 99%

Support Vector machine and duration-aware conditional random field for identification of spatio-temporal activity patterns by combined indoor positioning and heart rate sensors

et al. 2016

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Tracking the spatio-temporal activity is highly relevant for domains like security, health, and quality management. Since animal welfare became a topic in politics and legislation locomotion patterns of livestock have received increasing interest. In contrast to the monitoring of pedestrians cattle activity tracking poses special challenges to both sensors and data analysis. Interesting states are not directly observable by a single sensor. In addition, sensors must be accepted by cattle and need to be robust enough to cope with a rough environment. In this article, we introduce the novel combination of heart rate and positioning sensors. Attached to neck and chest they are less interfering than accelerometers at the ankles. Exploiting the potential of such combined sensor system that records locomotion and nonspatial information from the heart rate sensor however is challenging. We introduce a novel two level method for the activity tracking focused on the duration and sequence of activity states. We combine Support Vector Machine (SVM) with Conditional Random Field (CRF) and extend Conditional Random fields by an explicit representation of duration. The SVM characterizes local activity states, whereas the CRF addresses sequences of local states to sequences incorporating spatial and non-spatial contextual knowledge. This combination provides a reliable and comprehensive identification of defined activity patterns, as well as their chronology and durations, suitable for the integration in an activity data base. This data Geoinformatica (2016) base is used to extract physiological parameters and promises insights into internal states such as fitness, well-being and stress. Interestingly we were able to demonstrate a significant correlation between resting pulse rate and the day of pregnancy.

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Local Positioning Systems in (Game) Sports

Cited by 80 publications

References 76 publications

Dynamical Stability and Predictability of Football Players: The Study of One Match

Dynamical Stability and Predictability of Football Players: The Study of One Match

Open Source Technologies Involved in Constructing a Web-Based Football Information System

Support Vector machine and duration-aware conditional random field for identification of spatio-temporal activity patterns by combined indoor positioning and heart rate sensors

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