Combat sports analytics: Boxing punch classification using overhead depth imagery

In competitive combat sporting environments like boxing, the statistics on a boxer's performance, including the amount and type of punches thrown, provide a valuable source of data and feedback which is routinely used for coaching and performance improvement purposes. This paper presents a robust framework for the automatic classification of a boxer's punches. Overhead depth imagery is employed to alleviate challenges associated with occlusions, and robust body-part tracking is developed for the noisy time-of-flight sensors. Punch recognition is addressed through both a multi-class SVM and Random Forest classifiers. A coarse-to-fine hierarchical SVM classifier is presented based on prior knowledge of boxing punches. This framework has been applied to shadow boxing image sequences taken at the Australian Institute of Sport with 8 elite boxers. Results demonstrate the effectiveness of the proposed approach, with the hierarchical SVM classifier yielding a 96% accuracy, signifying its suitability for analysing athletes punches in boxing bouts.

The Sports Demonstration Project – An initiative of the Australian Sports Commission: An Evaluation

The Sport Development Project (SDP) was a comprehensive youth strategy for sport in the Northern Territory aimed at diversion from ‘at-risk’ behaviours, improvement of life choices and outcomes, and strengthening youth service infrastructure through engagement in positive (sport) activities. There were five Remote Service Delivery sites that were involved in the trial of this ‘best practice’ model for delivering sport-focused diversion activities. These include: Gapuwiyak, Wadeye, Yuendumu, Gunbalunya and Nguiu.

The impact of Indigenous Community sports programs: The case of surfing

The objective of this research project was to consider the social impact of sport and physical activity on the lives of Indigenous Australians and their communities. There has been strong research interest in the links between sport and recreation programs and various health and social outcomes and a well-established body of literature exists on the use of sport to address social issues in mainstream society (A Thomson, Darcy and Pearce 2010). The consensus is that physical activity is an important contributor to health for all people (Nelson, Abbott and Macdonald 2010). While there is strong research interest, what remains unclear is the value and impact of sport and physical activity on Indigenous communities (Cairnduff 2001). Nelson (2009) drawing on the work of Jonas and Langton (1994) indicates that an ‘Aboriginal person is a descendant of an Indigenous inhabitant of Australia, identifi es as an Aboriginal, and is recognised as Aboriginal by members of the community in which he or she lives’ (p. 97). Even this defi nition has the potential to be politically charged. At a general level, the collective terms ‘Indigenous’ (capitalised) and ‘Aboriginal and Torres Strait Islander’ people (title capitalised) appear to be broadly acceptable terms. Indigenous groups cannot be considered to be homogenous as there is much diversity between and within groups (Nelson et al. 2010; Parker et al. 2006). It is therefore important this report is not viewed as taking an essentialist view of who Indigenous people are and how they develop. Rather, this paper attempts to describe and discuss the experiences of some individuals and their communities in site-specifi c surfi ng programs.

Bayesian estimation of small effects in exercise and sports science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.