Reliability of spatial-temporal metrics used to assess collective behaviours in football: an in-silico experiment.

BACKGROUND: The purpose of this study was to investigate the reliability of spatio-temporal measurements applied within collective behaviour research in football. METHODS: In silico experiments were conducted introducing positional errors (0.5, 2 and 4 m) representative of commercial tracking systems to match data from the 2020 European Championship qualifiers. Ratios of the natural variance ('signal') of spatio-temporal metrics obtained throughout sections of each game relative to the variance created by positional errors ('noise') were taken to calculate reliability. The effects of error magnitude and time of analysis (1, 5 and 15 mins; length of attack: <10, 10-20, >20 s) were assessed and compared using Cohen's f2 effect size. RESULTS: Error magnitude was found to exert greater influence on reliability (f2 = 0.15 to 0.81) compared with both standard time of analysis (f2 = 0.03 to 0.08) and length of attacks (f2 = 0.15 to 0.32). DISCUSSION: The results demonstrate that technologies generating positional errors of 0.5 m or less should be expected to produce spatio-temporal metrics with high reliability. However, technologies that generate errors of 2 m or greater may produce unreliable values, particularly when analyses are conducted over discrete events such as attacks, which although critical, are often short in duration.

The effect of bio-banding on academy soccer player passing networks: Implications of relative pitch size.

The primary aims of this study were to examine the effects of bio-banding players on passing networks created during 4v4 small-sided games (SSGs), while also examining the interaction of pitch size using passing network analysis compared to a coach-based scoring system of player performance. Using a repeated measures design, 32 players from two English Championship soccer clubs contested mixed maturity and bio-banded SSGs. Each week, a different pitch size was used: Week 1) small (36.1 m2 per player); week 2) medium (72.0 m2 per player); week 3) large (108.8 m2 per player); and week 4) expansive (144.50 m2 per player). All players contested 12 maturity (mis)matched and 12 mixed maturity SSGs. Technical-tactical outcome measures were collected automatically using a foot-mounted device containing an inertial measurement unit (IMU) and the Game Technical Scoring Chart (GTSC) was used to subjectively quantify the technical performance of players. Passing data collected from the IMUs were used to construct passing networks. Mixed effect models were used with statistical inferences made using generalized likelihood ratio tests, accompanied by Cohen's local f2 to quantify the effect magnitude of each independent variable (game type, pitch size and maturation). Consistent trends were identified with mean values for all passing network and coach-based scoring metrics indicating better performance and more effective collective behaviours for early compared with late maturation players. Network metrics established differences (f2 = 0.00 to 0.05) primarily for early maturation players indicating that they became more integral to passing and team dynamics when playing in a mixed-maturation team. However, coach-based scoring was unable to identify differences across bio-banding game types (f2 = 0.00 to 0.02). Pitch size had the largest effect on metrics captured at the team level (f2 = 0.24 to 0.27) with smaller pitch areas leading to increased technical actions. The results of this study suggest that the use of passing networks may provide additional insight into the effects of interventions such as bio-banding and that the number of early-maturing players should be considered when using mixed-maturity playing formats to help to minimize late-maturing players over-relying on their early-maturing counterparts during match-play.