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The aim of this experiment was to investigate whether there were differences in decision-making skills between different age groups (Under 16, 18 and 23) of elite academy footballers on a video-based task of real-life football scenarios. It also explored the relationship between individual performance on the task and the performance of the footballers on the pitch, as rated by three independent expert football coaches. This allowed us to examine whether this task is useful in predicting real-world decision-making skills. The results show that there was a significant difference in response times between response time was statistically significantly lower in U23 compared to U18 and U16 and there was no statistically significant difference between the U16 and the U18 groups, but no significant difference between age groups on the accuracy of response. The under 23 age group responded significantly quicker when compared to the under 18 and under 16 age group most quickly, then the U18, and finally, U16 footballers were the slowest on the task. In terms of comparing coaches' opinion about the players' decision-making skills and players performance on the task, there was a positive correlation between accuracy on the task and general decision-making skills rated by the coaches, suggesting that coaches have a good insight on what players can actually do as. However, coaches' ratings of decisionmaking skills and response times on the task did not correlate suggesting that coaches are not aware of the speed of decision-making, and that this is only measurable by a representative task.

Having investigated the effects of videos in the preceding chapter, this chapter assesses 2D animation, a form of presentation used in many coaching situations. The aim of this experiment was to investigate decision-making skills in different age groups (Under 16, 18 and 23) of elite academy footballers using a 2D animation simulation task of real game football scenarios. The work also explored the relationship between individual performance on the task and the actual performance on the pitch, as rated by three independent expert football coaches. This allowed us to examine whether this task is useful in predicting real-world decision-making skills. The results suggested that there was a significant difference between age groups on accuracy, by gaining more experience footballers perform better on the task. Also, the results showed a significant difference between all age groups on the response time. The under 23 age group were fastest, then the under 18 age group and finally the under 16 footballers were the slowest on the task. The correlation between performance on the task and the assessments provided by the coaches showed that 2D animation task is a sensitive measure in assessment of decision-making skills of elite academy players.

This article investigates the effect of using different playing speeds of 2D animation on the decision accuracy and reaction times of elite footballers. Groups of players from different age categories (under 16, under 18 and under 23 years old) elite academy footballers watched 2D animations at five different ratios of real-life speed (0.5, 0.75, 1, 1.25-and 1.5-times real-world speed). Participants responded by choosing, from a number of options, which was the best attacking option in each 2D animation clip. After each clip, players also rated each clip for how "game-like" or realistic the scenario felt. Results showed a significant difference between all groups, whereby participants became faster and more accurate by age. Also, the result of "game-like" perception probing which compared perception in each group to each speed showed that the under 16 age group had statistically lower perception accuracy compared to the under 18 and under 23 age groups. This highlights that the more expertise a player has the faster information is processed.