Deception across pitch zones and team scores.

<p>Dive use by soccer players is expressed as (A) the mean proportion of total falls per match that were dives; (B) the mean frequency of dives per match across pitch zones (corrected for spatial area) ordered by increasing distance from the defensive goal (see insert); and, (C) the mean frequency of dives per match that were signalled when the player was winning, losing or drawing. Standard error bars are presented (<i>n</i> = 60). Asterisks denote significant differences based on post-hoc Tukey-Kramer HSD (<i>P</i><0.05; **<i>P</i><0.01; ***<i>P</i><0.001).</p

Detection of deception across leagues.

<p>(A) The mean proportion of total dives that were rewarded by the referee with a free-kick and the mean dive frequency of 10 matches in each league (<i>n</i> = 6). (B) Separated in to dives or tackles, the mean proportion that were rewarded by the referee across matches (<i>n</i> = 10) within each league. Leagues (A – F) are not identified due to ethical considerations. Standard error bars are presented. Black solid line indicates R² however Spearman's rank correlation coefficient, rho_, was used to calculate significance. Asterisks denote significant differences based on Paired-Wilcoxen signed rank tests (<i>P</i><0.05; **<i>P</i><0.01; ***<i>P</i><0.001).</p

Supplementary Information from Skill not athleticism predicts individual variation in match performance of soccer players

Just as evolutionary biologists endeavour to link phenotypes to fitness, sport scientists try to identify traits that determine athlete success. Both disciplines would benefit from collaboration, and to illustrate this, we used an analytical approach common to evolutionary biology to isolate the phenotypes that promote success in soccer, a complex activity of humans played in nearly every modern society. Using path analysis, we quantified the relationships among morphology, balance, skill, athleticism and performance of soccer players. We focused on performance in two complex motor activities: a simple game of soccer tennis (1 on 1), and a standard soccer match (11 on 11). In both contests, players with greater skill and balance were more likely to perform better. However, maximal athletic ability was not associated with success in a game. A social network analysis revealed that skill also predicted ball movement, as determined using social network analyses. The relationships between phenotypes and success during individual and team sports have potential implications for how selection acts on these phenotypes, in humans and other species, and thus should ultimately interest evolutionary biologists. Hence, we propose a field of evolutionary sports science that lies at the nexus of evolutionary biology and sports science. This would allow biologists to take advantage of the staggering quantity of data on performance in sporting events to answer evolutionary questions that are more difficult to answer for other species. In return, sports scientists could benefit from the theoretical framework developed to study natural selection in non-human species

Data used in Ellis et al. from Daylight savings time can decrease the frequency of wildlife–vehicle collisions

Data from study