The use of global positioning systems (GPS) has grown in popularity over the past decade (1). These GPS systems are used to quantify the external load experienced by a player, allowing coaches and supporting staff to manage training stress and identify players who are in danger of injury or non-functional overreaching.

The different metrics that are derived via GPS are plentiful, with high-speed acceleration, decelerations, total running distance, high speed running (HSR) and changes in direction being a few of the recorded metrics available. Generally, within the collection of these differing metrics, thresholds are set by which practitioners will be alerted to an excessive or an insufficient accumulation of external stress. From these thresholds, interventions may take place whereby players do additional training to reach physical goals, or reduced training is an attempt to avoid undesirable outcomes such as injury or non-functional overreaching. These thresholds are often set by GPS manufacturer and sometimes by the sports club themselves. Generally, these thresholds are set based on previous experience, personal observation and peer reviewed research.

In a recent report regarding high-level football clubs around the world (2), high-speed running and acceleration variables were ranked as the most commonly used metric to assess player load in games and training. As such, these GPS-derived metrics are important to professional sports teams and important to understand how to effectively reduce injury risk and “keep players playing”.

At Kitman Labs, we’re fortunate enough to perform GPS data analysis in relation to injury rate from training and competition in a variety of professional sports teams. With injury risk quantification being the cornerstone of Kitman Labs work, we want to know how the key GPS metrics are associated with injury rates within these sports with the aim being to mitigate risk. Below we present just one GPS metric from professional sports teams, high speed running (HSR), and its association with injury risk in three different sports teams. We hope these data has some strong practical applications, helps the reader to ask better questions, and perhaps keep players playing as they approach competitions.

The Data

Figure 1. The correlation coefficient of average injury rate (%) to accumulated high speed running over 7-days in three different professional sports teams. R2 values were converted to r values to use the following adapted criteria to interpret the magnitude of the relationship, where >0.1–0.3 is small, >0.3–0.5 is moderate, >0.5–0.7 is large, >0.7–0.9 is very large and >0.9–1.0 is almost perfect (3). R values are displayed alongside 90% confidence intervals on the top right of each chart. The number associated with each black dot is the number of “exposures” to that running speed for each team. In both cases, these data is for the week of competition only and therefore includes training and competition injuries.

Surprisingly, the relationship between injury rate and HSR is the exact converse to common belief. In that, on all three occasions, there is an increased injury rate when time spent performing HSR over the past 7 days is reduced. So, the less HSR performed over a 7-day period before the competition, the greater the likelihood of an injury occurring.

Possibly mechanisms of effect?

This makes us ask the question as to why we may be seeing this occurring from a mechanistic standpoint?

For this, we can consider the research around muscle stiffness, performance and injury. It has been well established that there is a “sweet spot” in terms of muscle stiffness where injury risk is reduced (3). In other words, too little stiffness, and too much muscle stiffness can be associated with increased injury risk. Elevated muscle and joint stiffness play a positive role in the soft-tissue prevention and rehabilitation (4). With increased stiffness being associated with enhanced functional joint stability, as stiffer structures can resist sudden joint displacements more quickly and effectively (4). As such, ensuring muscles are somewhat stiff, is desirable in team sports such as football, rugby, basketball and soccer which require fast and frequent changes in direction. Furthermore, such changes in direction are likely more prevalent in a typical game (e.g. Soccer, Ruby, Football, Basketball), than in typical training.

As players and athletes taper toward events and HSR is reduced, there may be a decrease in muscle stiffness thereby increasing the risk of injury. In term of HSR, this is indeed one exercise that could possibly have a marked effect on muscle stiffness. First, fast running, when ground contact time is low, has been found to substantially increase vertical stiffness (5), which may translate to some adaptive response at a muscular level (6). Second, the more ballistic nature of HSR means that muscle-preloading of the muscle is higher than when running at slower speeds. Such preloading movements have also been associated with increases in muscle stiffness (7). Although the time course of changes in such muscular stiffness is unknown, the literature is suggestive of fascia being malleable to change over shorter time frames (4, 8).

Practical Application

Whilst acknowledging this simple causative analysis of these data, there is generally a tendency for teams to reduce HSR in the lead up to competition. This is done to freshen players and perhaps reduce the risk of injury. However, these data would suggest the exact converse in that the continuation of HSR running within the training regime may mitigate injury risk and thereby aid performance. This suggests that the quantification of risk is multifaceted and needs to be done so in a manner that links to injury. Simply making assumptions on belief, “gut feel” or prior research may be misleading and at times inaccurate.

We can speculate, that this relationship with HSR is likely U-shaped, and at some point, too much HSR will indeed increase injury risk. However, none of these three teams achieved this within this data set. As such, this threshold is likely higher than expected, and these data would suggest that we can gain greater confidence through monitoring too little HSR rather than too much.

References:

1. Scott, MT, Scott, TJ. Kelly, VG. The Validity and Reliability of Global Positioning Systems in Team Sport: A Brief Review. J Strength Cond Res. 2016 May;30(5):1470-90. 

2. Arkenhead R, Nassis, GP. (2016) Training Load and Player Monitoring in High-Level Football: Current Practice and Perceptions Int J Sports Physiol Perform. 2016 Jul;11(5):587-93.

3. Hopkins WG, Marshall SW, Batterham AM, Hanin J (2009) Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc 41(1):3–1.

4. Butler RJ, Crowell HP, Davis IM. (2003) Lower extremity stiffness: implications for performance and injury. Clin Biomech (Bristol, Avon). 2003 Jul;18(6):511-7.

5. Arampatzis A, Schade F, Walsh M, Brüggemann GP. (2001) Influence of leg stiffness and its effect on myodynamic jumping performance. J Electromyogr Kinesiol. 2001 Oct;11(5):355-64.

6. Kuitunen S1, Komi PV, Kyröläinen H. (2002) Knee and ankle joint stiffness in sprint running Med Sci Sports Exerc. 2002 Jan;34(1):166-73.

7. Spurs et al 2003 EJAP Spurrs RW1, Murphy AJ, Watsford ML. (2003) The effect of plyometric training on distance running performance. Eur J Appl Physiol. 2003 Mar;89(1):1-7.

8. Wilson JM1, Flanagan EP (2008) The role of elastic energy in activities with high force and power requirements: a brief review J Strength Cond Res. 2008 Sep;22(5):1705-15