Science of synthetic turf surfaces: investigating traction behaviour

The traction forces produced between an athlete’s footwear and the playing surface are a crucial factor influencing a player’s performance. Four primary factors affecting traction have been identified from literature: the sports specific movement, the footwear, the playing surface, and the environment. Many authors have investigated traction behaviour mechanically, using a variety of shoe and surface types, concluding that the traction generated at the shoe–surface interface is dependent on each shoe–surface combination (see work by Gheluwe et al., Cawley et al., and Villwocket et al., details given in main text). There has been little attempt in the literature, however, to try and explain the behaviour of the surface from the traction resistance measurements that were observed, perhaps owing to the complex number of variables involved. Furthermore, the variety of methodologies used in past research makes it difficult directly to compare datasets. This paper presents datasets comparing the traction behaviour of several carefully prepared surface systems and states, using three mechanical test procedures, and investigates the factors influencing traction resistance. Results highlight that properties of synthetic turf carpets (fibres and tuft spacing) and the density state of the crumbed rubber infill component and the stud size and configuration influence the maximum traction forces generated at the shoe–surface interface. The magnitude of stud penetration under controlled vertical loading is also presented. The findings of this study further demonstrate the importance of understanding the detail of the surface system under test, and that the infill state has a measurable effect. The design and operation of mechanical traction measurement equipment also demonstrates influences on the traction values measured, and the largest influence is the normal load applied. The FIFA standard test is shown to be less sensitive to infill state than other tests. Recommendations are made for more robust testing methods for future research.