Individual soccer performance is notoriously difficult to measure due to the many contributing sub-variables and the variety of contexts within which skills must be utilised. Furthermore, performance differs across rather specialised playing positions. In research, soccer performance is often measured using combinations of, or even single, sub-variables. All too often these variables have not been validated against actual performance. Another approach is the use of proxies. In sports research, the age of athletes when winning championship medals has been used as (...) a proxy for determining their age of peak performance. In soccer, studies have used the average age of players in top European leagues or in the Champions League to determine the age of individual peak performance. Such approaches have methodological shortcomings and may underestimate the peak. We explore the use of a new proxy, the age at nomination for major individual awards, to determine the average age at peak individual soccer performance. A total of 1,981 players nominated for major awards from 1956 to 2019 were included, and a subset of 653 retired players was extracted, thus including players’ complete careers. Players’ average ages at nomination, at their first nomination, and at their last ever nomination were calculated, and differences across playing positions were calculated together with changes over time in the average age at peak. Based on our proxy, the age of individual peak soccer performance occurs around 27–28 years, varying across playing positions from 26 to 31 years. A player’s first peak, on average, seems to coincide with known peaks of physiological variables; their last-ever peak occurs long after physiological performance has started to decline, indicating that the decline can be compensated for by other variables. The peak age is higher than previously reported for soccer; however, it is similar to those in other team ball sports. The average age at peak performance has increased over time, especially in the last decade. Our approach of using proxies for unearthing information about hidden features of otherwise immeasurable complex performance appears to be viable, and such proxies may be used to validate sub-variables that measure complex behaviour. (shrink)

We argue that lateralities are not merely a result of phylogenetic processes but reflect probability functions that are influenced by task characteristics and extended practice. We support our argument by empirical findings on lateral biases in early infancy in general, and footedness in particular, and on hand preferences in nonhuman primates.