A computer vision based web application for tracking soccer players

Soccer is a sport where everyone that is involved with it make all the efforts aiming for excellence. Not only the players need to show their skills on the pitch but also the coach, and the remaining staff, need to have their own tools so that they can perform at higher levels. Footdata is a project to build a new web application product for soccer (football), which integrates two fundamental components of this sport's world: the social and the professional. While the former is an enhanced social platform for soccer professionals and fans, the later can be considered as a Soccer Resource Planning, featuring a system for acquisition and processing information to meet all the soccer management needs. In this paper we focus only in a specific module of the professional component. We will describe the section of the web application that allows to analyse movements and tactics of the players using images directly taken from the pitch or from videos, we will show that it is possible to draw players and ball movements in a web application and detect if those movements occur during a game. © 2014 Springer International Publishing

A visual programming language for soccer

The use of Information Technologies (IT) in high competition sports is an instrument often used. However, the majority of the performers, including technical teams, do not have skills to program those IT tools to their needs. In this paper we present the low level implementation of a visual programming language (VPL) that allows the user without programming expertise to produce relatively complex programs by drawing them on a web application. The VPL tool application is illustrated by applying it to detect programmed situations from a soccer game, using previously obtained tracking data. The tool can be applied to other collective ball sports

Local Positioning Systems in (Game) Sports

Position data of players and athletes are widely used in sports performance analysis for measuring the amounts of physical activities as well as for tactical assessments in game sports. However, positioning sensing systems are applied in sports as tools to gain objective information of sports behavior rather than as components of intelligent spaces (IS). The paper outlines the idea of IS for the sports context with special focus to game sports and how intelligent sports feedback systems can benefit from IS. Henceforth, the most common location sensing techniques used in sports and their practical application are reviewed, as location is among the most important enabling techniques for IS. Furthermore, the article exemplifies the idea of IS in sports on two applications

Team behaviour analysis in sports using the poisson equation

We propose a novel physics-based model for analysing team play- ers’ positions and movements on a sports playing field. The goal is to detect for each frame the region with the highest population of a given team’s players and the region towards which the team is moving as they press for territorial advancement, termed the region of intent. Given the positions of team players from a plan view of the playing field at any given time, we solve a particular Poisson equation to generate a smooth distribution. The proposed distribu- tion provides the likelihood of a point to be occupied by players so that more highly populated regions can be detected by appropriate thresholding. Computing the proposed distribution for each frame provides a sequence of distributions, which we process to detect the region of intent at any time during the game. Our model is evalu- ated on a field hockey dataset, and results show that the proposed approach can provide effective features that could be used to gener- ate team statistics useful for performance evaluation or broadcasting purposes

The role of motion analysis in elite soccer

The optimal physical preparation of elite soccer (association football) players has become an indispensable part of the professional game especially due to the increased physical demands of match-play. The monitoring of players’ work-rate profiles during competition is now feasible through computer-aided motion analysis. Traditional methods of motion analysis were extremely labour intensive and were largely restricted to university- based research projects. Recent technological developments have meant that sophisticated systems, capable of quickly recording and processing the data of all players’ physical contributions throughout an entire match, are now being used in elite club environments. In recognition of the important role motion analysis now plays as a tool for measuring the physical performance of soccer players, this review critically appraises various motion analysis methods currently employed in elite soccer and explores research conducted using these methods. This review therefore aims to increase the awareness of both practitioners and researchers of the various motion analysis systems available, identify practical implications of the established body of knowledge, while highlighting areas that require further exploration

Open source technologies involved in constructing a web-based football information system

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

The Potential of Big Data Analytics for Decision Support in Sports – The Case of Soccer

Compared to other popular sports, soccer is quite a fluid sport with high degrees of freedom, which is why evaluating games or single players\u27 performance is more demanding and complex. Even though the availability of different types of soccer data has increased steadily over the last few years, the process of strategic and tactical decision-making is still traditionally done by single specialists. In this context, the potentials of big data analytics (BDA) provide an advantage in automatically assessing and assembling data from various sources and generating insights that exceed the analytical capability of individual human experts. We focus on this potential by developing a design science research-based BDA artifact, which aims at providing strategic decisional support for managers and experts. In several evaluations with different soccer and sports experts, we are able to show advanced usability of the artifact\u27s instantiation over traditional tools provided by large stats providers