Talent Identification and Development in Tennis

Accurately identifying individuals at a young age who are most likely to excel in a given sport remains a pursuit for coaches, parents and national governing bodies worldwide. In a sport such as tennis, the financial investment needed to support a player’s development is substantial, although this is offset by the vast sums of money that are on offer for those few elite players who reach the very top of the game. As such, tennis can be considered to represent a high risk, high reward venture, where the value of being able to better identify those who are likely to ‘make it’ takes on extra emphasis. The debate surrounding the timeless ‘nature versus nurture’ conundrum rumbles on and shows no sign of abating. The relative contribution that deliberate practice (Starkes & Ericsson, 2003) as opposed to genetics (Tucker & Collins, 2011) play in the development of champions remains a contentious issue. Popular texts such as ‘Bounce’ (Syed, 2010) and communications intended specifically for tennis coaches (Roetert, Kovacs & Crespo, 2009) have served to engage a wider community in the debate. It is the intention of this short article to summarize the key points emerging from this body of work and to offer some guidance to coaches moving forward.

Clustering of lifestyle risk behaviours among residents of forty deprived neighbourhoods in London: lessons for targeting public health interventions

Background Clustering of lifestyle risk behaviours is very important in predicting premature mortality. Understanding the extent to which risk behaviours are clustered in deprived communities is vital to most effectively target public health interventions. Methods We examined co-occurrence and associations between risk behaviours (smoking, alcohol consumption, poor diet, low physical activity and high sedentary time) reported by adults living in deprived London neighbourhoods. Associations between sociodemographic characteristics and clustered risk behaviours were examined. Latent class analysis was used to identify underlying clustering of behaviours. Results Over 90% of respondents reported at least one risk behaviour. Reporting specific risk behaviours predicted reporting of further risk behaviours. Latent class analyses revealed four underlying classes. Membership of a maximal risk behaviour class was more likely for young, white males who were unable to work. Conclusions Compared with recent national level analysis, there was a weaker relationship between education and clustering of behaviours and a very high prevalence of clustering of risk behaviours in those unable to work. Young, white men who report difficulty managing on income were at high risk of reporting multiple risk behaviours. These groups may be an important target for interventions to reduce premature mortality caused by multiple risk behaviours.