Early reintegration to training and match play following injury increases the risk of reinjury. However, having key players available benefits the team.1 Practitioners must balance these two components of the return to sport (RTS) process, combining evidence and clinical experience to estimate this risk, then plan and adapt RTS accordingly.1 Quantifying and monitoring training load is key in guiding this process while managing reinjury risk,2–4 and global positioning systems (GPS) provide a valid measure of external running loads.5 However, as practitioners, we should focus on both quantitative aspects of running load progression and qualitative characteristics of movement in competition. This includes highly variable, spontaneous and unanticipated movements (the conditions of ‘chaos’) reflecting the unpredictable nature of the sport.

ACL injuries are among the most severe knee injuries in elite sport, with a high injury burden and re-injury risk. Despite extensive literature on the injury and the higher incidence of injury and re-injury in female athletes, there is limited evidence on the return to sport (RTS) of elite female football players following ACL reconstruction (ACLR). RTS is best viewed on a continuum aligning the recovery and rehabilitation process with the ultimate aim — a return to performance (RTP_erf). We outline the RTS and RTP_erf of an elite female football player following ACLR and her journey to the FIFA Women’s World Cup, including the gym-based physical preparation and the on-pitch/sports-specific reconditioning. We used the ‘control–chaos continuum’ as a framework for RTS, guiding a return above pre-injury training load demands while considering the qualitative nature of movement in competition. We then implemented the ‘RTP_erf pathway’ to facilitate a return to team training, competitive match play and a RTP_erf. Objective information, clinical reasoning and shared decision-making contributed to this process and helped the player to reach her goal of representing her country at the FIFA Women’s World Cup.

The purpose of this study was to determine changes in two tests of lower limb isometric posterior chain force (IPC-F) following 90 min of match-play in elite youth soccer players and the interaction between relative strength and recovery profile. 14 players (age: 16 ± 2 years) performed 3 × 3 second IPC-F tests unilaterally at 30° and 90° of knee and hip flexion pre- and post-match, +24 h, +48 h, and +72 h post-match. Peak force was recorded for both limbs, combined and expressed relative to bodyweight (N/kg). A two-way repeated measures analysis of variance was performed to determine differences in force output between joint angles, time intervals and subjects. As there was no interaction between angle and time (p = 0.260), we report the change between timepoints as mean ∆ in 90° + 30° IPC-F. Relative to pre-match IPC-F, there were significant decreases post (∆ = −18%; p > 0.001) and at +24 h (∆ = −8%; p = 0.040), no significant difference at +48 h (∆ = 0%; p = 0.992) and a significant increase at +72 h (∆ = +12%; p = 0.005). There was a large inter-individual variability in recovery profile at both angles and substantial differences between post-match deficits at 90° (−10.8%) compared to 30° (−20.7%). Higher pre-match IPC-F was correlated with the magnitude of IPC-F deficits at both angles and all time points (r = 0.56 to 0.70, p = < 0.01) except for post-match 90°. Regular IPC-F monitoring to determine the magnitude of match-induced fatigue and track recovery may help inform decision-making regarding modifications to individual players training load, particularly as there is a large inter-individual variability in response to competition. Further research is warranted to better understand and address the finding that stronger players showed larger force deficits and slower recovery following match-play.

Hamstring strain injuries (HSIs) are common injuries in professional sport and the musculotendinous junction the most frequently injured site.1 2 MRI proves that the tendon extends into the muscle belly and has increased awareness of the intramuscular tendon injury.3 Some argue that this subtype of HSI may require surgical repair. Currently, there is no consensus on intramuscular tendon injury management; there is agreement that players are at an increased risk of re-injury on return to play (RTP).3 4 Evidence suggests that clinical decision-making, based on achieving functional goals, is an essential element of successful rehabilitation.4

Purpose: The purpose of this study was to assess the interchangeability of position tracking metrics obtained using global positioning systems (GPS) versus those obtained by a semi-automatic high definition (HD) optical camera system. Methods: Data was collected from a cohort of 29 elite football players (age: 23.1 ± 5.1 years, height: 180.4 ± 5.8 cm, mass: 74.6 ± 6.7 kg) in four matches played in four different stadiums. In two matches 10 Hz GPS (GPS-1, StatSports, Belfast, UK) were used, while in the other two matches augmented 10 Hz GPS (GPS-2, StatSports, Belfast, UK) were used. All four matches were analysed concomitantly using six semi-automated HD motion cameras sampling at 25 Hz (TRACAB, Chyronhego, New York, USA). Results: Mean bias was between 6% and 10% for GPS-1 and 1–4% for GPS-2, respectively. No proportional bias was found (p > 0.184). The SEE within calibration functions (expressed in % to mean) was between 5% and 22% for GPS-1 and 4–14% for GPS-2. While some significant differences existed between GPS-1 and TRACAB (total distance and high-speed), positional tracking variables were highly correlated between GPS-1, GPS-2 and TRACAB (r²> 0.92) with GPS-2 displaying stronger correlations (> r² = 0.96). Conclusion: In the present study augmented GPS technology (GPS-2) and the TRACAB camera system provided interchangeable measures of positional tracking metrics to allow concurrent assessment and monitoring of training and competition in football players. However, we recommend practitioners evaluate their own systems to identify where errors exist, calculate and apply the regression equations to confidently interchange data.