Hamstring injuries are common in intermittent sprint sports, accounting for the most injuries in rugby and soccer and the second most in American football. Stephen Smith CEO of Kitman Labs explains more… 


While the influence of lower limb parameters (quad:hamstring strength ratio, hip mobility, etc.) have been well documented, other risk factors associated with hamstring injury have received less attention both in research and in applied practice, but can actually be more indicative of risk.


Based on Kitman Labs‘ research into player data collected from our Athlete Optimization System TM, we have noted that there is a distinct pattern of indicators preceding a hamstring injury that can be used to enhance injury monitoring and prevention protocols. 


Teams that can collect, analyse and action data associated with these risk factors on a daily basis can reduce the frequency of, and days lost, to hamstring injuries.


Hamstring Injury Indicators


Prior to the hamstring injury, a number of variables alerted for each player. Across 70% of the injuries a change in both well-being and musculoskeletal variables were noted. More specifically, muscle soreness and fatigue increased and sleep quality decreased in the 2 weeks prior to injury occurrence. Hip internal rotation and groin squeeze also changed in the weeks preceding hamstring injury. Notably, the validated measure of hamstring length (sit & reach) score only varied in two players prior to injury occurrence.


In one study, the direction of the change in groin squeeze and hip rotation varied across athletes i.e. one athlete showed an increase in groin squeeze strength and hip rotation prior to injury. The other player registered a decrease in hip and groin function prior to injury. This emphasises the need to monitor athlete specific changes in any direction, not just team averages.


kitman labs graph (Kitman Labs Hamstrings.png)



Kitman Labs Recommendations


1. Assess multi-factor hamstring risk indicators


Because the hamstrings have double joint functions (knee and hip), injuries can originate from maladapted movements at either joint. While eccentric force production, mobility etc. are related to hamstring injury occurrence, measuring any parameter of hamstring function (strength, mobility, power) in isolation does not reflect the idiosyncratic nature of injury occurrence.


Frequent monitoring of the concomitant changes in the following musculoskeletal and well-being markers – including fatigue, sleep quality, change in groin squeeze, and hip internal rotation – can provide an early (1-3 weeks) indication to coaches of any player who may be at risk of developing a hamstring injury during acceleration/ deceleration running activity during training or game scenarios.


2. Combine player response risk factors with load data


Monitoring and analysing workload in combination with the above risk factors can give coaches additional indicators of potential risk for hamstring injuries. Peer reviewed research suggests that “athletes accustomed to high training loads have fewer injuries than athletes training at lower workloads” (Gabbett, 2015), but also that “excessive overload plus inadequate recovery” can also lead to injury (Gleeson, 2013). As we know, every athlete responds to load differently. As such, monitoring athlete response to fluctuations in load is of the utmost importance.


3. Analyse players as individuals


As mentioned above, each individual player responds to the stresses placed on them differently based on their unique strengths, weaknesses, capabilities and body mechanics. Therefore, changes to the risk factors for any injury should be analysed for each athlete based on their typical individual patterns, not based on team or even position averages.


4. Use data daily, to know when to push athletes forward, when to intervene


Ultimately, the goal is to have a program that optimizes athlete and team performance without increasing injury risk. By collecting and assessing load and response frequently from athletes, wearables, biomechanical screenings, etc., coaching and training staffs can marry data with their expertise to make the best daily decisions on training, treatment and recovery. 


The goal – push forward with training those athletes that the data suggests are capable and ready and intervene only for those showing risk indicators. Restricting an athlete’s workload purely because they have had an increase in load limits any potential increase in performance capacity and may not be necessary. Understanding the individual threshold that increases risk across each individual athlete is needed to maximise any potential performance gains and reduce injury.


With the right data and analysis, coaches can keep more players on the field throughout the season, and reduce the total days lost to hamstring injury, and increase chances of winning.