Seminars @ Loughborough

The following seminars within the Sports Informatics Seminar Series @ Loughborough, have been arranged for 2012.

October 19th (Friday), 2012 - Statistical modelling in sport
Prof. Phil Scarf, Professor, (Associate Dean Research and Innovation) University of Salford
Time & Location: @2:00pm, N112, 1st Floor, Haslegrave Building
Abstract: This talk considers how modelling can be used to shed light on a variety of sporting problems. 
We look at:
  1) How the timing of a declaration in the third innings of a test match can be “optimized”. 
  2) Route choice in mountain running events and an empirical basis for Naismith’s rule. 
  3) Actions in a football match which contribute to the final result of the game. 
  4) How we might rank players in test cricket putting batting and bowling contributions on the same scale.
  5) Optimum strategy in the track. 
  6) Tournament design.
BiographyPhil Scarf is a professor at the University of Salford. His research interests are in Replacement Modelling, Reliability and Maintenance Modelling, and OR and Statistics in Sport. He is currently co-editor of the IMA Journal of Management Mathematics which has published a special issues on OR in Sport under his editorship. He has competed in a variety of sports: rugby, cricket, rowing, orienteering, cycling. His current hobby is expedition racing.
September 19th (Wednesday), 2012 - Virtual Rehabilitation in Cerebal Palsy: CAREN and the Goblin Post Office
Dr. Gabor Barton, Reader in Biomechanics, Liverpool John Moores University
Time & Location: @1:00pm, N112, 1st Floor, Haslegrave Building
Abstract: Virtual reality is a computer generated simulation of the real world in which the user can interact with a virtual environment through a human-machine interface (Holden, 2005). There is a growing interest in applying virtual reality in a movement rehabilitation context because a computer based reactive environment provides the key elements of motor learning - repetition, feedback, and motivation (Rizzo et al., 2002). There is evidence that problems resulting from brain damage improve in response to specific exercises. Virtual reality based computer games can focus on control of specific movements, and provide enhanced motivation for continuing these training exercises. This talk presents results of a project in which a series of studies were conducted both with healthy controls and children with CP aiming to improved selective movement control of the core and consequential improvement of movement function. Quantification of game performance ranged from simple methods of movement variability to determination of the maximal settled speed which develops as a result of an adaptive algorithm adjusting forward speed of the games.
Biography: Dr. Gabor Barton graduated in 1993 from the Medical University of Pecs, Hungary with distinction (Summa Cum Laude). Following a three years research programme at LJMU he took up a position at Alder Hey Children's Hospital in Liverpool where he had been running the Clinical Gait Analysis service for five years. After returning to LJMU as Senior Lecturer in Biomechanics he completed his PhD (on decision support in clinical gait analysis using artificial neural networks) and currently he is Reader in Biomechanics. As Leader of the Biomechanics Research Group, he manages the Movement Function Research Laboratory at LJMU's Research Institute for Sport and Exercise Sciences (RISES). This state-of-the-art facility is home to the CAREN system which combines biomechanical movement analysis with virtual reality.

Prof. Arnold Baca, Professor, (Chair of IACSS) University of Vienna, Austria
Time & Location: @10:30am, N112, 1st Floor, Haslegrave Building
Abstract: Technological systems are getting increasingly important for physical activity monitoring and assessment in general and for supervising load and performance in mass and elite sport in particular. Miniature sensors and computing devices are attached to the athletes or integrated into the sports equipment in order to acquire and process performance or load related data. Ubiquitous computing technologies are thus applied to implement systems, which provide athletes with feedback information on the quality of the motion just performed.Due to the rapid progress in hardware capabilities and the potential of data processing methods, it is expected that “the emphasis in the future developments will shift to development of intelligent systems that could not only analyze the data but suggests strategies and interventions” [1]. Moreover, sports equipment will be able to sense new conditions in the environment and adapt accordingly thus showing the behavior of adaptive systems.One main basis of almost any intelligent feedback system or adaptive system is the successful recognition or classification of patterns underlying the human motion just performed. This analysis does not only comprise kinematic parameters, but, moreover, also kinetic and physiological data. Different methods and models have proven to be useful for this kind of analysis.In the presentation, a survey of hard- and software approaches is given. Pros and cons are discussed with regard to their applicability for intelligent devices supporting athletes. Practical applications are presented and experiences reported.[1] Baca, A., Dabnichki, P., Heller, M., and Kornfeind, P. (2009). Ubiquitous computing in sports: A review andanalysis. Journal of Sports Sciences, 27 (12) (2009), 1335-1346.
Biography: Prof. Arnold Baca received the Engineering Diploma in Computer Science in 1984 and the Ph.D. (Thesis: “Variance-reducing techniques for simulation methods in system reliability analysis” in 1986 from the Vienna University of Technology. In 1998 he received the habilitation in “Applied Computer Science in Biomechanics and Kinesiology” from the University of Vienna. Since 2008 he is full professor at the Faculty of Sport Science at this university.Prof. Baca is currently Dean of this faculty. He is the President of the International Association on Computer Science in Sport ( and Editor-in-Chief of the International Journal of Computer Science in Sport.Research interests: Pervasive/Ubiquitous Computing in Sport, Multimedia and E-Learning, Feedback systems, Biomechanics methods.

Dr. Ben Heller, Centre for Sports Engineering Research (CSER), Sheffield Hallam University
Time & Location: @10:15am-11:00pm, N112, 1st Floor, Haslegrave Building
Abstract: The talk will focus on the application of recently available sensing and wireless technologies for collecting unprecedented amounts of data in both sports and medical fields, with experience from Centre for Sports Engineering Research (as Sheffield Hallam) work with UK Sport and a large number of sporting bodies in the build-up to the 2012 Olympics.
Biography: Ben Heller is a Principal Research Fellow at the Centre for Sports Engineering Research (CSER) at Sheffield Hallam University. His background is in Biomedical Engineering: he worked in the Medical Physics Department of Sheffield Teaching Hospitals for 14 years where he ran clinical services in movement analysis and functional electrical stimulation. Since joining Sheffield Hallam University in 2006, he has worked in both the measurement of movement in Sports as well as maintaining his interests in healthcare technologies.

Prof. Martin Lames, Professor, Chair for Training Science and Sport Informatics, Technical University Munich
Time & Location: @11:30am-12:30pm, N112, 1st Floor, Haslegrave Building
Abstract: This talk will be a general introduction into various areas of computer sicence use within sports sciences. Martin will introduce the IACSS (International Association for Computer Science in Sports), where he is the General Secretary. Then, he will proceed to some ideas on interdisciplinary work in Sports and Computer science. After this, some of his work in this area, modelling and simulation in game sports, IT support in top level sports, position detection in football and other sports (technologies, reliability, validity) will be presented in more detail.
Biography: Professor Martin Lames, is currently the Chair for the Training Science and Sport Informatics, at the Faculty of Sports and Health Science, TU Munchen. During the years 1996-2002 he was also the director of Institute for Sports Science, at University of Rostock, and during the years 2002-2009 he was the director of Institute for Sports Science at University of Augsburg.
Dr. Peter O'Donoghue, Reader, Cardiff Metropolitan University & Chair, International Society Performance of Sport
Time & Location: @2pm-3pm, N112, 1st Floor, Haslegrave Building
Abstract: Image processing has been utilised within advanced soccer analysis systems to provide player movement data relating to physiological demands and tactical aspects of play. There are various aspects of play that can potentially be analysed efficiently using player displacement data. These include support, depth, width and penetration in attack (Daniel, 2003), penetration in attack (Hargreaves and Bate, 2010), different types of support run performed during possession (Hughes, 1998), pressure, cover, back up and balance in defence (Tenga, 2010), compactness of defence (Daniel, 2003) and team placement during zonal and man to man defending (Prestigiacomo, 2003). All of these areas can potentially be recognised through automated analysis of player displacement data. For an algorithm to be developed to automatically analyse any aspect of play, there must be (a) an agreed understanding of tactical aspects and their characteristics at a subjective level (b) precise definitions of location and movement patterns that characterise different tactical aspects and (c) a mathematical representation of the tactical aspects of interest. This is illustrated in the current research using two examples; (a) balance of defence (Olsen, 1981) and creating space in attack / denying space in defence (Bangsbo and Peitersen, 2004; Bangsbo and Peitersen, 2002). Olsen (1981) described balanced and unbalanced defences and there is evidence that attacking is more productive against unbalanced defences in international football (Olsen and Larsen, 1997). Tenga (2009) produced operational definitions for the three key aspects of balance; pressure, back up an cover. An algorithm has been developed in Matlab version (The Matworks Inc., Natick, MA) to determine whether a defence is balanced at any point during an opposition attack using Tenga's (2009) definitions. A further algorithm has been developed to determine mean distance variables from nearest opponents for the team in possession. The algorithm do require a second data source to identify times of starts and ends of possessions as well as their classified outcomes. This was done for the forward most 1 to 10 players in the team for the first and last 3s, 4s and 5s of possessions as well as the difference in mean space between the beginning and the end of the possessions. The algorithm was tested for a Bundesliga match using one 45 minute half of football. The most significant variable was the mean space for the 10 outfield players during the final 5s of the possession (p <0.05). The mean distance to the nearest opponent was 7.5+1.4m during the last 5s when the 2 goals were scored 6.4+0.8m when there was a shot on target and 6.1+0.2m when there was a shot off target. This variable may be a useful indicator for one team's ability to create space when in possession and another team's ability to restrict space when defending.

Martin Sykora,
Jul 31, 2012, 3:45 AM
Martin Sykora,
Jun 25, 2012, 3:31 AM
Martin Sykora,
Jun 12, 2012, 10:27 AM
Martin Sykora,
Jun 12, 2012, 10:22 AM