Talent Identification Using a Game Technical Scoring Chart Within Small-Sided Games in Highly Trained Pre-Pubertal Soccer Players Jonathan Fenner A Thesis submitted in partial fulfilment of the requirements of Staffordshire University for the degree of Doctor of Philosophy November 2015 November

ABSTRACT
Historically, research in talent identification has used a reductionist approach, whereby elements for successful soccer performance have been assessed as discrete components and their predictive power examined in isolation to match performance. To examine attributes that contribute to successful performance, a multidimensional represented task, such as small-sided games (SSG’s), may play a crucial role in achieving this objective. The game technical scoring chart’s (GTSC) reliability and validity was established. This thesis examined and designed an appropriate SSG by examining appropriate pitch size, game duration and surface. Reliability of the SSG design was also established. Utilising this SSG design, a 4 v 4 multiple SSG was used in an attempt to identify the most talented player. The results demonstrated that the more successful players in the SSG’s were rated highly by coaches and played the SSG’s at a higher speed and covered greater distances than their less successful peers. Consequently, multiple SSG’s could be used to identify talented pre-pubertal soccer players. A further study, attempted to examine a possession-based SSG model for talent identification. The results demonstrated highly rated player’s won the most amount of games. Possession-based SSG’s could also be used in a multidimensional represented task talent identification model to determine the most talented players. Finally, the thesis examined the influence of decision-making on player’s performance in both the traditional and possession-based SSG’s and found that there were no significant relationships between decision-making and success in both the traditional and possession-based SSG. In conclusion, this thesis has identified that both a traditional and possession-based SSG could be used within a talent identification model to successfully identify talented players through the recording of players win to loss ratio in multiple SSG’s. This talent identification model could be used to continually assess players’ ability throughout a season to evaluate player development.