Do Football Managers need to rotate their players?

The purpose of this essay is to review the literature with regards to training/competitive workloads and recovery. It will ignore any tactical reasons a manager may have for changing their team and ask: do they need to rest players to avoid risk of non-contact injury or diminished performance?

Football is characterised by short bouts of high-intensity linear and multidirectional movements, and longer recovery periods of varied lengths (Varley, M. and Aughey, R.; 2013). These movements consist of repeated accelerations and decelerations, multiple short sprints, change of direction and an ability to produce high levels of muscular force quickly (Spencer, M., Bishop, D., Dawson, B. and Goodman, C.; 2005).

The last several years have seen football evolve into a quicker, more intensive game, with greater demands placed on physical and technical abilities. Recent data suggests a trend in increased sprinting distance and high-intensity running distances, with total distances covered during a match remaining constant (Barnes, C., Archer, D., Hogg, B., Bush, M. and Bradley, P.; 2014). Over the last 6 years these high-intensity running distances have increased by 30-35%, and these have been performed despite reduced recovery periods (Barnes et al; 2014). Non-contact injury represents the highest injury risk since the 2002 World Cup (McCall, A., Jones, M., Gelis, L., Duncan, C., Ehrman, F., Dupont, G. and Duffield, R.; 2018), which are potentially avoidable (Gabbett, T.; 2010; Colby, M., Dawson, B., Heasman, J., Rogalski, B. and Gabbett, T.; 2014). The highest-level players are often competing year-round with high match frequencies in a congested competitive schedule, and often play matches with three days recovery (Nedelec, M., Halson, S., Abd-Elbasset, A., Ahmaidi, S. and Dupont, G.; 2015). Player availability has been strongly linked with team success, defined by league ranking and points per match (Hagglund, M., Walden, M., Magnusson, H., Kristenson, K., Bengston, H. and Ekstrand, J.; 2013). This would indicate that keeping first choice players healthy and at their peak would increase the chances of success for a manager.

The amount of high-speed running varies between position; some research has found fullbacks and forwards to complete the most high-speed running (Martin-Garcia, A., Casamichana, D., Diaz, A., Cos, F. and Gabbett, T.; 2018), whereas another study showed it to be greatest in forwards and wide midfielders, and the least distance covered by central defenders (Delaney, J., Thornton, H., Rowell, A., Dascombe, B., Aughey, R. and Duthie, G.; 2017), and midfielders cover the greatest total distance with central defenders the least (Lacome, M., Simpson, B., Cholley, Y., Lambert, P. and Buchheit, M.; 2017).

Gabbett (2016), recently outlined his training-injury paradox which stated that rapid ‘spikes’ in training volume/intensity increase the risk of injury, whereas chronic exposure to higher training loads can help protect against injury. This is measured by comparing the weekly training load (acute), and the rolling average of the previous 3-6 weeks prior (chronic). This is known as the acute to chronic workload ratio (ACWR).

The ACWR can be viewed as a dynamic representation of an athlete’s preparedness, with high chronic workloads developing fitness, and high acute workloads developing fatigue. A rested (low acute workload) athlete with a high level of fitness (through a high chronic workload) will be in a well-prepared state. A very high ACWR in combination with a low chronic workload has demonstrated the highest risk for non-contact injury (Bowen, L., Gross, A., Gimpel, M., Bruce-Low, S. and Li, F.; 2019; McCall, A., Jones, M., Gelis, L., Duncan, C., Ehrman, F., Dupont, G., Duffield, R.; 2018). A reserve player cannot be expected to play at the required intensities for 90 minutes if they have not been doing this regularly in training. Acute: chronic ratios of >1.5 (the current workload was 1.5 times greater than the athlete has been prepared for) have shown the risk of injury to be 2-4 times greater in the following week (Hulin, B., Gabbett, T. and Blanch, P., Chapman, P., Bailey, D. and Orchard, J.; 2014). The ideal range suggested has been an A:C ratio between 0.8-1.3 which can maximise fitness and performance whilst reducing the injury risk (Gabbett, T; 2016), with Malone et al (2017) showing acute: chronic workloads of 1.00-1.25 offers protective effects for the players. Higher levels of fitness (specifically intermittent aerobic fitness) have been shown to reduce risk when players experience higher A:C workloads of >1.25 however (Malone et al; 2017).

Arbitrary units (AU) were initially suggested by Gabbett (2016) as a method of monitoring training load across a variety of training modalities, or for when the standard monitoring tools were unavailable (players away on National team duty for example). AU are calculated by using the individual’s session-rating of perceived exertion (RPE) score of 1-10, multiplied by the session duration in minutes. This score of RPE units x minutes would give typical scores of 300-500AU for lower-intensity sessions, and 700-1000AU for higher-intensity sessions. Players with 3 week chronic workloads of  ³2584 AU along with 701-750m of high speed running (HSR) were protective, whereas those achieving the same amount of HSR with <2584 AU were at an increased risk of injury (McCall, A., Dupont, G., Ekstrand, J.; 2018). Other research (Malone et al; 2017) has shown that loads greater than 3000AU, or weekly increases of 550-1000AU increased the risk of injury, although this appeared to be greater in preseason versus in-season, which suggests that players develop a greater tolerance due to a greater chronic workload.

Players can cover 10,000m during a match (Bowen, L., Gross, A., Gimpel, M. and Li, F.; 2017), and therefore reducing their training workloads below this threshold could result in them being underprepared for matches. Even replicating the average match demands could leave athletes underprepared for the most demanding phases of competitive matches (Gabbett, T., Kennelly, S., Hawkins, R., Milsom, J., King, E., Whiteley, R. and Ekstrand, J.; 2016). Small-sided practise games have been shown to result in higher maximal speeds and greater high-speed distances (Djaoui, L. Chamari, K., Owen, A. and Dellal, A.; 2017), which is an ideal method to attain the intensities required. Players that are regularly exposed to higher workloads develop the physical robustness that reduces the likelihood of injury (Bowen et al, 2019), with higher intermittent-aerobic capacity protecting against rapid increases (spikes) in workloads (Malone, S., Owen, A., Newton, M., Mendes, B., Collins, K. and Gabbett, T.; 2017).

With regards to injury risk and prevention there is a notable difference in the stress imposed regarding different running intensities. High intensity maximal running speed (85-95%) and very high intensity maximal running speed (>95%) have been shown to have an impact (Malone, S., Roe, M., Doran, D., Gabbett, T. and Collins, K.; 2017), with greater than 9m of very-high intensity running per session increasing the risk of injury by 2.7 times (Gabbett, T. and Ullah, S.; 2012), along with training time spent above 85% of HR_max (Owen, A., Forsyth, J, Wong, D., Dellal, A., Connelly, S. and Chamari, K.; (2015). It should be noted however, that most sprint efforts performed are well below the distance required to achieve maximal speeds, with mean sprint distances being less than 10m (Barnes et al; 2014). Higher volumes of mild, moderate and maximal acceleration efforts have been associated with reduced soft-tissue injury rates (Gabbett & Ullah; 2012), as have higher intermittent aerobic fitness levels as demonstrated in Yo-Yo IR1 performance scores (Malone, S., Owen, A., Mendes, B., Hughes, B., Collins, K. and Gabbett, T.; 2018). Coaches may need to carefully monitor HSR versus lower-intensity running in competitive matches and small sided practise games to achieve a consistent level of chronic loading.

The training-injury prevention paradox model (Gabbett, T.; 2016) states that athletes need the optimal loads that deliver higher workloads over a suitable period, whilst avoiding any spikes that the athlete is not physically prepared for. Acute: chronic workloads of 1.00-1.25 have been shown to be protective for players, if they are not acquiring these loads within the matches themselves, then they would need to attain these during practise sessions which may place greater time demands on those involved. Research suggests that players achieving the 701-750m of HSR without the required chronic workloads are at higher risk of non-contact injury, with full backs and forwards the players most likely to achieve the most distances at high speeds.

For the competitive teams playing in multiple competitions, a workload of 1.00-1.25 may require higher chronic workloads, which would mean increasing practise workloads in the weeks where matches are reduced or not scheduled. Small-sided practise games are ideal for attaining the required HSR for any athletes not meeting the required A:C workloads, however these must be monitored to avoid going above the 1.25 for any given week, or an increase of 550-1000AU in a single week.

How consistent the team plays may factor into the equation, with regards to level of possession and playing style. If a team plays in a similar fashion, with a similar amount of HSR each match, then the same players may be able to develop a consistent chronic workload. If some matches increase the workloads above the 1.25 level, then certain players at higher risk (forwards and fullbacks) may require reduced minutes to bring them back to below the threshold. To help minimise spikes in workloads, off-season plans should be implemented to reduce detraining outside of the season, which would minimise the need for excessive pre-season training loads. The players are looking at maintaining their level of intermittent aerobic fitness, and ability to tolerate the required amount of HSR depending upon their position.

If the playing style is similar each week and acute workloads to not go above the 1.25 threshold, then a manager should be able avoid rotating players without putting them at risk of non-contact injury, assuming they are also not dropping below the 1.00 limit for any reason (reduced number of games or weak opposition for example). Should this happen, small-sided games in training should enable the players to reach their required workloads, which should be carefully monitored in these situations.

References:

Barnes, C., Archer, D., Hogg, B., Bush, M. and Bradley, P.; (2014) The evolution of physical and technical performance parameters in the English Premier League. International journal of sports medicine. 35, 1095-1100.

Bowen, L., Gross, A., Gimpel, M., Bruce-Low, S. and Li, F.; (2019). Spikes in acute: chronic workload ratio (ACWR) associated with 5-7 times greater injury rate in English premier league football players: a comprehensive 3-year study.

Bowen, L., Gross, A., Gimpel, M. and Li, F.; (2017). Accumulated workloads and the acute: chronic workload ratio relate to injury risk in elite youth football players. British journal of sports medicine. 51, 452-459.

Colby, M., Dawson, B., Heasman, J., Rogalski, B. and Gabbett, T.; (2014). Accelerometer and GPS-derived running loads and injury risk in elite Australian footballers. Journal of strength and conditioning research. 28(8), 2244-2252.

Delaney, J., Thornton, H., Rowell, A., Dascombe, B., Aughey, R. and Duthie, G.; (2017). Modelling the decrement in running intensity within professional soccer players. Science and medicine in football. 2, 86-92.

Djaoui, L. Chamari, K., Owen, A. and Dellal, A.; (2017). Maximal sprinting speed of elite soccer players during training and matches. Journal of strength and conditioning research. 31(6), 1509-1517.

Gabbett, T.; (2016). The training-injury prevention paradox: should athletes be training smarter and harder? British journal of sports medicine. 50, 273-280.

Gabbett, T., Kennelly, S., Hawkins, R., Milsom, J., King, E., Whiteley, R. and Ekstrand, J.; (2016). If overuse injury is a ‘training load error’, should undertraining be viewed the same way? British journal of sports medicine. 50, 1017-1018.

Gabbett, T. and Ullah, S.; (2012). Relationship between running loads and soft-tissue injury in elite team sport athletes. Journal of strength and conditioning research. 26(4), 953-960.

Gabbett, T.; (2010). The development and application of an injury prediction model for noncontact, soft-tissue injuries in elite collision sport athletes. Journal of strength and conditioning research. 24, 2593-2603.

Hagglund, M., Walden, M., Magnusson, H., Kristenson, K., Bengston, H. and Ekstrand, J.; (2013). Injuries affect team performance negatively in professional football: an 11-year follow-up of the UEFA champions league injury study. British journal of sports medicine. 47, 738-742.

Hulin, B., Gabbett, T. and Blanch, P., Chapman, P., Bailey, D. and Orchard, J.; (2014). Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. British journal of sports medicine. 48, 708-712.

Lacome, M., Simpson, B., Cholley, Y., Lambert, P. and Buchheit, M.; (2017). Small-sided games in elite soccer: does one size fits all? International journal of sports physiology and performance. 13, 1-24.

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Malone, S., Roe, M., Doran, D., Gabbett, T. and Collins, K.; (2017). High chronic training loads and exposure to bouts of maximal velocity running reduce injury risk in elite gaelic football. Journal of science and medicine in sport. 20, 250-254.

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