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Review

A Scoping Review for Hamstring Injury Risk Monitoring in Australian Rules Football

by
Dale Wilson Chapman
,
Sorcha Humphreys
,
Shannon Spencer
,
Nathan Tai
,
Dag Øyen
,
Kevin Netto
* and
Robert Waller
Curtin School of Allied Health, Curtin University, Perth 6102, Australia
*
Author to whom correspondence should be addressed.
Encyclopedia 2025, 5(2), 72; https://doi.org/10.3390/encyclopedia5020072 (registering DOI)
Submission received: 7 February 2025 / Revised: 20 May 2025 / Accepted: 23 May 2025 / Published: 27 May 2025
(This article belongs to the Section Medicine & Pharmacology)
Browse Figure
Versions Notes

Abstract

:
Hamstring strain injuries (HSIs) are the most common time loss injury sustained in male Australian Football League (AFL) athletes, causing significant financial cost, time cost, and impaired team and individual performance. In a squad of 42 players, HSIs accounted for 4.86 new injuries sustained by players per club per AFL season in 2020. This is consistent with injury reporting over the last decade in AFL, despite best efforts to reduce the rate. This scoping review sought to firstly identify the reported hamstring injury prevention risk factors in elite AFL, discern the impact of these factors, and map the gaps in the current literature using a biopsychosocial understanding of injury prevention. The scoping review process was based on the Askey and O’Malley framework. Five relevant online databases (MEDLINE, Proquest, CINAHL, SPORTdiscuss, and EMBASE) were systematically searched using a series of Boolean and operator terms following the PRISMA-ScR protocol using the criteria: (1) assessing male professional/elite athletes in AFL; (2) written in English and peer-reviewed; (3) full text available; and (4) published after 2006. Only manuscripts that fit the search terms and inclusion criteria were retained in the scoping review. Following an initial search, 246 potential studies were identified, with 12 studies meeting the inclusion criteria after full-text screening. The risk factors examined were subclassified into modifiable and non-modifiable categories. Modifiable factors include high-speed running exposure, gluteus medius activation, eccentric hamstring strength, shorter bicep femoris fascicle length, use of interchange, and hamstring stiffness. Non-modifiable factors include previous history of HSI and limb injury, age, and size of injury on MRI. This scoping review highlights the need for continued monitoring of high-speed running volumes as rapid increases in completed distances present as a substantial risk factor. The modifiable mechanistic risk factors of eccentric hamstring strength and hamstring stiffness were identified as important components of player screening to reduce the risk of future HSI. Risk factors identified throughout will help develop comprehensive injury profiling for athletes. Further research is warranted to develop a holistic approach to injury profiling.

1. Introduction

Australian Rules Football is a contact sport involving high-speed running, rapid change of direction, kicking, and ground ball maneuvers [1]. The Australian Football League (AFL) is the pinnacle competition for Australian Rules Football, with 18 teams competing over 23 rounds in-season and up to four games in the final series over seven consecutive months per year to win the grand final. The league also seeks to evolve the rules of the game, with the intent of maximizing commercial revenue through increasing spectator interest and viewership, and balancing these needs with player safety. In 2006 the AFL implemented rule changes aimed at increasing game speed which have the potential to effect historical HSI risk and rates. These changes included a 30-s limit for set shots and a 4.5-m protected area around players taking free kicks or marks. Hamstring strain injuries (HSIs) were the most common time loss injury sustained in male AFL athletes in 2020 [2]. This statistic for time loss is also consistent with injury reporting over the past decade [3,4,5]. In a squad of 42 players, HSIs accounted for 4.86 new injuries sustained per club per AFL season in 2020, with 74% occurring during matches and the remainder occurring during training [2]. The recurrence rate on the ipsilateral side within the same season was the sixth-highest injury, with a 20% recurrence rate [1]. HSIs result in significant financial loss to the AFL clubs, with the average cost of a single HSI increasing by 56%, from AUD 25,603 to AUD 40,021 [2,4]. Therefore, it is critical to identify risk factors that potentially reduce the rate of injury and financial burden within the AFL [6].
Injury literature classifies the risk factors associated with any particular injury as either non-modifiable or modifiable [7]. A non-modifiable risk factor is defined as a factor that is inherent to the individual injured and cannot be modified by intervention or circumstance [7]. In contrast, a modifiable risk factor responds to change or intervention positively or negatively [7]. The two most discussed non-modifiable risk factors for HSIs are increasing player age and previous history of HSI [6,8,9]. Recent research has centered around identifying modifiable risk factors for HSI’s in the AFL that can be targeted through interventions such as eccentric knee flexor strength during the Nordic hamstring exercise or biceps femoris long head fascicle length [6,10,11,12]. This focus aligns with the findings of Bourne et al. [13], who highlighted that hamstring muscle architecture and strength measurements provide valuable insights into HSI risk profiles. They reported that previously injured hamstrings displayed alterations in muscle architecture and reduced eccentric strength, supporting the importance of these modifiable factors in injury prevention strategies. Importantly, if possible, identified modifiable risk factors and the tools for monitoring these factors should reflect the debate on the mechanism of injury i.e., strain vs force [14,15]. The strain-induced model proposes that excessive muscle lengthening during eccentric contractions leads to injury, while the force-induced model suggests that excessive muscle forces, regardless of length changes, are the primary cause. The work of Bourne et al. [13,16] highlights that both architectural factors (related to strain) and strength deficits (related to force capacity) play important roles in reinjury risk, suggesting an integrated approach may be most appropriate. However, a lack of consensus exists around which factors are predictors of injury or how regularly testing should occur, which also reflects the conjecture on the mechanism of injury. Considering the range of modifiable factors in preventing HSI, identifying a comprehensive screening test or tests to monitor HSI risk in AFL players may assist in mitigating the risk of injury.
Anecdotal evidence from allied health professionals recognizes player health as multifactorial, and all elements of the athlete should be considered when identifying risk factors related to HSIs. It has been identified that a stressful family or workplace situation may affect the body’s capacity to recover from training loads that were previously well tolerated, leading to an increased risk of an athlete sustaining a HSI [17]. Considering the interplay between biomechanical and psychosocial factors leading to injury (such as variations in factors influencing external load and internal capacity), exploring these factors holistically may assist in a better understanding of potential contributors around the time of injury.
This study aimed to identify potentially useful HSI risk monitoring tools in elite field team sport athletes, specifically for AFL athletes. In doing so, we sought to discern the impact of these monitoring tools and map the gaps in the current literature using a biopsychosocial understanding of injury prevention. A scoping review was conducted over a systematic review as it is hypothesis-generating in nature, versus a systematic review which is hypothesis-testing. A scoping review allowed us to identify knowledge gaps, scope the literature available, and clarify concepts around HSI risk factors in the AFL. This scoping review may be helpful to a future systematic review to assess the quality of evidence and challenge the hypothesis further [18].

2. Materials and Methods

This scoping review followed the “Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist”. In conjunction with this, the methodological framework as proposed by Arksey and O’Malley was utilised [19]. There is no known review protocol for HSI risk monitoring in AFL. This study was registered at the Center for Open Science/Open Science Framework: https://doi.org/10.17605/OSF.IO/E6H8N, accessed on 22 May 2025.

2.1. Eligibility Criteria

The inclusion and exclusion criteria were guided by the Participants, Intervention/Exposure, Comparators, Outcomes, and Study Design (PICOS/PECOS) framework, and are summarized in Table 1. In more detail, studies were included in this scoping review if they: (1) were written in English and published between 2006 and 2022 to capture the period immediately following pertinent rule changes; (2) included professional or elite Australian Rules Football athletes playing in the Australian Football League; (3) analyzed screening tests for HSI, reported injury risk, or investigated musculoskeletal morphology, functional performance, and biopsychological risk factors in HSIs; and (4) were of any length of follow-up.
Studies were excluded from this scoping review if they were: (1) literature reviews, conference proceedings, or case studies; (2) based on participants competing at non-elite or non-professional level; (3) incorporated participants who were non-Australian Rules Football athletes; or (4) examined the effect of HSI rehabilitation or prevention programs, or reviewing return to play (RTP) criteria post-HSI.

2.2. Search Strategy, Data Collection and Extraction

A consumer advisory group led by the Head of Medical Services of an AFL club was set up to provide input into the study. Initial contact with the consumer advisory group was made in March 2022. A consumer engagement interview with the consumer advisory group was conducted in June 2022 to confirm that the keywords used in the search strategy met the club’s objectives and that they were comfortable with the breadth of inclusion and exclusion criteria to be applied.
An initial search was conducted on 5 August 2022 over five electronic databases: MEDLINE (Biomedical sciences; 1946-present), Proquest, CINAHL (Nursing and allied health; 1961-present), SPORTdiscuss, and EMBASE (Biomedical and pharmacological; 1947-present), encompassing a comprehensive range of literature available relating to hamstring injury risk factors while incorporating all health professions. These databases were searched using the keywords “AFL” OR “Australian football*” OR “Australian rules” OR “Aussie rules” AND “hamstring*” OR “HSI” OR “semitendinosus” OR “semimembranosus” OR “biceps femoris” AND risk* OR “risk factor*” OR “risk management” OR “prevent*” OR “predict*” with “Published after 2005” AND “Full text” AND “English language” filters. A Google Scholar search was performed, targeting any further literature not yet captured within the initial search. Reference lists from the identified literature were screened, and relevant papers were captured if not already included in the search. Following which a customized data extraction sheet was formulated after the screening process with four researchers (S.H., S.S., N.T., and D.Ø.), extracting the data from the eligible studies (Figure 1).
Studies identified in the search were imported into EndNote20 (Clarivate, 20.2 (MacOS)/20.2.1 (Windows)/30 November 2021). Duplicates were screened and removed manually based on title and date. Four independent researchers screened the studies separately based on standardized eligibility criteria. Any disagreements in the selection of papers between the researchers were resolved by discussion. Full-text screening was later conducted by the same researchers for the final study inclusion.

3. Results

The initial search returned a total of 246 potential studies. After duplicates were removed, 238 studies remained to be included in the title and abstract screening (Figure 1). Following the title and abstract screen, 47 papers were identified for full-text screening. Full-text evaluation excluded a further 35 manuscripts, resulting in 12 studies meeting the inclusion criteria.
The risk factors examined by the studies which met the inclusion criteria were subclassified into modifiable (Table 2) and non-modifiable risk factors (Table 2). Modifiable factors are those that can be influenced or altered. Non-modifiable are those that cannot be altered by external influences.

3.1. Modifiable Factors

3.1.1. High-Speed Running Exposure

Two papers identified the role of high-speed running as a risk factor for HSI in AFL. Duhig and associates [21] concluded that the likelihood of HSI increased with greater relative high-speed running distances in the four weeks prior to the time of injury (OR = 1.96, 95% CI 1.54 to 2.51, p < 0.001), and that the largest effect of high-speed running distance on injury risk was observed one week prior to injury (OR = 6.44, 95% CI 2.99 to 14.41, p < 0.001). Ruddy and associates [22] explored this further, concluding that greater than 653 m of running occurring above 24 km/h (RR = 3.4, 95% CI 1.6 to 7.2) had the largest influence on HSI in the following week.

3.1.2. Gluteus Maximus (GMAX) and Medius (GMED) Size and Activation

Franettovich and associates [23] identified increased higher average and peak activation of GMED during running at 12 km/h and 15 km/h (peak p = 0.023, average p = 0.014) and speed (peak p < 0.001, average p < 0.001) as a risk factor for HSI during the playing season. No clinically significant difference was noted in GMAX muscle activity and combined GMED/GMAX muscle size in players who suffered an injury and those who did not.

3.1.3. Eccentric Hamstring Strength

Opar and associates [12] reported AFL players with previous HSI displayed significantly (p = 0.012; d = 0.60) less increase in eccentric hamstring strength bilaterally (absolute change, 13.9 ± 55.0 N; relative change, 1.07 ± 0.20 N) compared with an uninjured group (absolute change, 54.6 ± 78.5 N; relative change, 1.26 ± 0.39 N). Additionally, Opar and associates [10,11,12] demonstrated that decreased Nordic eccentric knee flexion strength increased the risk of future HSI. Values below 256 N at the start of preseason increased risk of future HSI 2.7-fold (RR, 2.7; 95% CI, 1.3 to 5.5; p = 0.006) while values below 279 N at the end of preseason increased risk 4.3-fold (RR, 4.3; 95% CI, 1.7 to 11.0; p = 0.002). Also, an eccentric knee flexor strength imbalance > 9% (RR, 1.81; 95% CI, 1.06–3.08) increased HSI prevalence. Contradicting Opar’s research, Smith and associates [6] revealed that Nordic eccentric knee flexion strength was not significantly associated with a future hamstring injury (415 N. OR: 1.9, 95% CI 1.9 (0.6–6.0, p = 0.30).

3.1.4. Long Head of Biceps Femoris Fascicle Length

Opar and associates [10] measured biceps femoris fascicle length using ultrasound imaging at multiple time points throughout preseason and in-season. Individual athletes with a shorter long head of biceps femoris fascicle length (<10.42 cm) were significantly associated with a higher risk of HSI (RR, 1.89; 95% CI, 1.20–2.99).

3.1.5. Use of Interchanges

In Australian Football League (AFL), a player interchange refers to the system that allows teams to substitute players during a match without limiting the number of rotations. The interchange system allows teams to manage player fatigue, adapt tactical approaches throughout the game, and respond to match conditions. It is a critical aspect of modern AFL strategy, with teams carefully planning rotation schedules to optimize player performance while maintaining tactical structures. Looking specifically at data collected during in-season games, the number of interchanges made per athlete, per game, showed players who were interchanged seven or more times over the last three weeks of play were at less of a risk of HSI with a relative risk of 0.74, (95% CI 0.59–0.93) [4].

3.1.6. Knee and Hip Proprioception

Smith and associates [24] showed that altered joint position sense of the knee and hip did not predict the risk of HSI. No significant differences between uninjured and injured limbs (p > 0.05) were found.

3.1.7. Hamstring Stiffness

A single study investigated hamstring and leg stiffness as risk factors for HSI. High bilateral hamstring stiffness and leg stiffness, 11% (p = 0.04) and 5% (p = 0.03), respectively, compared with the uninjured counterparts was indicative of a higher risk of sustaining a HSI during the season [25].

3.2. Non-Modifiable Factors

3.2.1. History of Injuries

Two papers considered previous HSI injuries as a risk factor for future hamstring injuries, with another considering lower limb injury history. Warren and associates [26] identified that a previous HSI in the last 12 months carried a statistically significant risk of hamstring reinjury (RR = 5.3, 95% CI 1.8–15.4, p = 0.006). Furthermore, Smith and associates [6] concluded that reporting a hamstring injury within the previous year (OR = 3.7, p = 0.01) or greater than 1-year (OR = 3.6, p = 0.01), as well as a previous groin (OR = 8.6, p < 0.01) or calf injury (OR = 4.6, p = 0.01), were factors significantly associated with subsequent hamstring injury. After accounting for team clustering, Orchard et al. reported that significant predictors of hamstring injuries were recent hamstring injury (p = 0.000; RR 4.16, 95% CI 3.19–5.43), history of ACL reconstruction (p = 0.019; RR 1.69, 95% CI 1.09–2.60), and history of calf injury (p = 0.000; RR 1.58, 95% CI 1.37–1.82).

3.2.2. Age

Two papers identified age as a risk factor for HSI. Watsford and associates [25] reported that the injured players (mean = 27 ± 3.4 yrs) were significantly older than the uninjured players (mean = 22.6 ± 3.5) (p < 0.01). Smith and associates [6] found similar results, identifying that player age greater than 25 yrs (OR = 2.9, 95% CI 1.1 to 7.6, p < 0.05) was associated with increased risk of HSI.

3.2.3. Size of a Hamstring Injury on MRI to Predict Recurrence

Verrall and associates [27] discussed the size of initial HSI (as measured by MRI) and if the tear size was a relative risk factor for subsequent or recurrent HSI. A larger size of initial HSI was associated with an increased risk for recurrent injury (p < 0.01). Recurrence of HSI risk was increased if the transverse size of injury was greater than 55% of the muscle by 2.2 times (95% CI, 0.88–5.32) and if the calculated volume of injury was greater than 21.8 cm3, 2.3 times (95% CI, 0.94–5.81) when compared to athletes with hamstring injuries below these measurements.
Table 2. Synthesis of results for modifiable factors.
Table 2. Synthesis of results for modifiable factors.
Risk FactorReferencePredictors of Injury
Results, p-Value, Odds Ratio (OR), Confidence Intervals (CI)
High-speed running[21]
  • Likelihood of HSIs increased (OR = 1.96, 95% CI 1.54 to 2.51, p < 0.001) with greater relative high-speed running distances in the 4 weeks prior to injury.
  • Largest effect of high-speed running distance on injury risk was observed 1 week prior to injury (OR = 6.44, 95% CI 2.99 to 14.41, p < 0.001).
  • Acute high-speed running loads during week −1 had a greater impact on injury risk compared to chronic loads (sum of −2, 03, and −4).
[22]
  • Weekly distance covered above 24 km/h (>653 m, RR = 3.4, 95% CI 1.6 to 7.2, sensitivity = 0.52, specificity = 0.76, area under the curve (AUC) = 0.63) had the largest influence on the risk of HSI in the following week.
  • For the relative running exposure variables, distance covered above 24 km/h as a percentage of distance covered above 10 km/h (>2.5%, RR = 6.3, 95% CI 1.5 to 26.7, sensitivity = 0.93, specificity = 0.34, AUC = 0.63) had the largest influence on the risk of HSI in the following week.
Gluteus medius (GMED) and gluteus maximus (GMAX) muscle volume and activation (EMG)[23]
  • Increased activation of GMED during running (p < 0.001) was a risk factor for HSI during the playing season.
  • There is no difference in GMED and GMAX muscle sizer or GMAX muscle activity between players who sustained a HSI vs did not.
Unilateral hamstring stiffness[25]
  • Players who sustained a HSI during the season recorded significantly higher mean hamstring stiffness (11%, p = 0.04) and leg stiffness (5%, p = 0.03) at preseason testing. When considering the injured players, the leg stiffness of the involved limb was significantly higher than the non-injured players (p = 0.02), whereas hamstring stiffness was significantly higher on the uninvolved limb (p = 0.01).
Long head of bicep femoris fascicle length[10]
  • Individual athletes with a shorter long head of biceps femoris fascicle length (<10.42 cm) were significantly associated with a higher risk of HSI (RR: 1.89; 95% CI: 1.20–2.99).
Increased use of interchanges[4]
  • Opposition team making 60 or more interchanges during the game (RR: 1.38; 95% CI: 1.12–1.68)
  • Players having made 7 or more interchanges off the field in the last 3 weeks (protective RR: 0.74; 95% CI: 0.59–0.93)
Eccentric hamstring strength [11]
  • The previously injured group displayed significantly less increase in eccentric hamstring strength across the preseason (absolute change, 13.9 ± 55.0 N; relative change, 1.07 ± 0.20 N) compared with the control group (absolute change, 54.6 ± 78.5 N; relative change, 1.26 ± 0.39 N) for both absolute and relative measures (p < 0.001)
[12]
  • Eccentric hamstring strength below 256 N at the start of preseason increased risk of future HSI 2.7-fold (RR, 2.7; 95% CI, 1.3 to 5.5; p = 0.006)
  • Eccentric hamstring strength below 279 N at the end of preseason increased risk of future HSI 4.3-fold (RR, 4.3; 95% CI, 1.7 to 11.0; p = 0.002)
[6]
  • Nordic strength was not significantly associated with future hamstring injury (Odds Ratio (OR) 1.9, p = 0.36)
Hip and knee proprioception [24]
  • No significant differences were found in hip and knee proprioception between uninjured and injured limbs (p > 0.05).

4. Discussion

The goal of the scoping review was to map the current literature for evidence-based evaluation of the impact of risk factors on HSI in the AFL with a biopsychosocial perspective of the injury. The risk factors examined in our body of research were subdivided into modifiable and non-modifiable, based on the framework of Sammito et al. [7].
Weekly exposure to high-speed running (HSR) > 24 km/h for >653 m was associated with a greater risk of HSI the following week [22]. This highlights the need to monitor acute and chronic running exposure and time spent at high speeds to mitigate the risk of injury in the AFL. Similar results have been found in soccer with acute and chronic workload ratios [28], indicating that exposing athletes to large and rapid increases in training, above their two-yearly session average, increased the odds of HSI. High-speed eccentric deceleration has been examined in a soccer setting and correlated with HSI [29,30]. Further research examining high-speed eccentric deceleration in an AFL setting is warranted to examine this association.
Opar and associates [11,12] reported that eccentric hamstring strength < 256 N at the preseason and <279 N at the end of the preseason increased the risk of future HSI 2.7-fold and 4.3-fold, respectively. Contradicting Opar’s research, Smith and associates [6] revealed that Nordic eccentric knee flexion strength was not associated with the risk of future HSI. However, mean eccentric hamstring strength was much lower in Opar’s study (250–300 N) compared to Smith’s study (>415 N), and this could account for the lack of significance in the findings. The potential clinical utility of these results suggests that if the mean eccentric hamstring strength is low (250–280 N) in the preseason, improving strength during the preseason could reduce HSI risk. Wollin and associates [31] reported that screening isometric hamstring strength in soccer players post-match (>40 h, on the morning of the first normal training day after a rest day) could indicate a higher risk of HSI if their strength at testing was impaired by >14%. They concluded that identifying hamstring strength impairments before returning to training after the match could help mitigate the risks of HSI. In soccer, Timmins and associates [32] also explored the effects of eccentric hamstring strength on HSIs, concluding that eccentric hamstring strength of less than 337 N could significantly increase the risk of HSIs. Further research is needed to transfer these findings from soccer into an AFL setting to justify using pre- and post-eccentric hamstring strength assessment as a risk factor for HSI.
While we have reported on the application of general hamstring strength monitoring, readers of this scoping review will likely have been surprised that greater evidence for H:Q ratio has not been reported. However, while the H:Q ratio is well established, the evidence for using the H:Q ratio as predictor of HSI is conflicted [33,34]. The authors did not directly exclude the H:Q ratio from the search as it is a modifiable strength ratio of the hamstrings to quadriceps and should have been captured with the search term used. Thus, it is clearly apparent from our literature search of primary peer reviewed literature that the H:Q ratio is either no longer being reported as high value use in AFL or at the least clinician researchers working in AFL are choosing not to report the H:Q ratio in their research. The measure is acknowledged to have a high-cost burden, both in terms of time to administer across a whole squad and the equipment access cost, and in the author’s experience both can negatively impact on the players compliance to this testing/monitoring measure [35]. Interestingly, in other forms of football, prospective studies have reported associations between lower functional H:Q ratios (especially <0.6) and increased HSI risk [36]. Furthermore, bilateral asymmetries in H:Q ratios greater than 10–15% have been linked with higher injury rates [37]. The standard protocol for assessing the H:Q ratio is a comparison of the peak torque generated at 60°·s−1 using an isokinetic dynamometer [36,38]; however, this testing is highly controlled with little relevance to match conditions and actual velocities of functional movement, leading to concerns of limited ecological validity to the measure [35]. While this scoping review has been limited to male AFL players, this highlights a glaring gap and lack of consensus on the continued use of the H:Q ratio. Applied practitioners and researchers are likely shifting to angle-specific measurements that appear more informative than single value ratios which reflects both the strain and force argument of injury mechanism [14,15]. While testing in an isokinetic dynamometer is not overly representative of functional movement, this device does provide the capacity to test under controlled fatigue conditions which may provide stronger predictive value than when tested in a rested or non-fatigue state. The literature suggests that while the H:Q ratio or another strength assessment of the hamstrings provides valuable information, it should be used as one component in a multivariable model within a comprehensive screening battery.
Hamstring and leg stiffness was identified as risk factor for future HSIs by Watsford and associates [25]. However, the assessments in the current study provide valid evidence of practical and contemporary techniques for determining lower body stiffness. Therefore, we conclude that the assessment of stiffness is an important component of player screening in preparation for professional ARF and reducing the risk of future HSI.
Higher gluteus medius (GMED) activation during running at 12 and 15 km/h correlated with an increased risk of HSIs [23]. These findings likely reflect an increased role of GMED as an abductor and facilitator of pelvic stability during running. The practicality of this testing in an elite sport setting using EMG surface electrodes must be considered. However, the task-specific nature of GMED activation is very relevant for injury risk monitoring. Further research is required to understand the involvement of GMED activation in running and how it contributes to HSI risk.
Opar and associates [10] discovered that shortened biceps femoris long head (BFlh) fascicle length (<10.42 cm) increased the risk of HSI when assessed at multiple time points during the season. The paper provided a cut-off line of 11 cm for BFlh fascicle length to mitigate the risk of HSIs. Similarly, Timmins and associates [32] concluded that a BFlh fascicle length of <10.56 cm significantly increased the risk of HSI in soccer. This may lead us to conclude that shorter BFlh fascicle length may correlate with poorer strength and less flexibility, increasing injury risk.
Orchard and associates [4] found that players who were interchanged seven or more times over the last three weeks of play were at less risk of HSI. This could be attributed to recovery and a transient reduction in hamstring injury risk with increased interchange. Therefore, a complicated relationship exists in terms of mitigating the risk of HSIs in AFL. Monitoring interchange is essential in mitigating the risk of HSI, assuming it reduces fatigue and cumulative load.
The relationship between hip and knee joint position sense (JPS) and prospective HSIs in AFL was explored by Smith and associates [24]. The results showed no correlation between JPS testing and predicting HSIs. Therefore, it does not seem to be worth screening in the professional AFL setting to mitigate the risk of injury.
An increase in age, cross-sectional injury size, and history of the previous hamstring, groin and calf injury have been associated with increased HSI risk (Table 3). Watford and associates [25] observed that AFL players who suffered HSIs were significantly older than non-injured players. The rationale proposed that a reduction in type II muscle fiber innervation and cross-sectional area could result from the ageing process. Furthermore, older players with a longer playing history were exposed to a greater accumulation of scar tissue over time which could have contributed to an increased likelihood of injury [25]. Smith and associates [6] established that a player aged ≥25 years would be three times more likely to suffer a HSI than players below that age. Interestingly, Duhig and associates [21] refute this, noting that younger players were considered to have a lower tolerance for training loads, whilst experienced players were more robust. This suggests that older players manage their exposure to stress and workloads better, and thus have reduced HSI risk. Whilst age is non-modifiable, some factors associated with age, like decreased strength, stiffness, and ankle ROM [39], are modifiable. A change in these factors could potentially minimize HSI within older players. Therefore, while age as an independent variable may not be predictive of injury, a more holistic approach to using this risk factor may be warranted, especially when other factors such as experience and training exposure of the athlete are considered.
A larger cross-sectional size of a hamstring injury on MRI was reported to have a two times higher chance of recurrent injury than players with a smaller injury size [27]. The British Athletics Muscle Injury Classification (BAMIC) evaluates the impact of injury size, injury location and the effect of hamstring injury recurrence [40]. Hamstring injuries that extend into the tendon (grade c) or present with the signal change of craniocaudal length of greater than 15 cm are more prone to re-injury and delay time to return to full training [40]. MacDonald and associates [41] documented the time for RTP using the BAMIC in track and field athletes post-HSI. Further study is needed to assess the transferability of such programs into the AFL population to facilitate evidence-based structured rehabilitation.
A history of previous lower limb injury was shown to increase HSI risk in elite AFL [4,6,26]. This is also reported in a soccer population resembling similar findings [42,43]; however, the evidence justifying the correlation between prior lower limb injury and hamstring injury risk is limited. Hägglund and associates [43] proposed that previous injury altered movement patterns, reduced proprioception, and decreased physical conditioning of the athlete, increasing HSI risk. Further research would be required to evaluate this hypothesis.
The paucity of literature examining the contribution of psychosocial factors in HSI causation in AFL requires further consideration to develop a holistic prevention strategy. Psychological factors [44] are monitored in other sports-related injuries, such as anterior cruciate ligament injury [45] and athletic groin pain [46], but are limited in a HSI scope. The biopsychosocial model of stress, athletic injury, and health [47] was developed exploring the influence of the physical/physiological and psychological/attentional changes that occur in response to stress and resultant increased injury risk [48]. It is thought that increased negative psychosocial factors (family life, work life, financial situation, practice and game pressures) affect an athlete neurocognitively, increasing distractibility, increasing reaction times, and missing task-relevant cues [48], all of which are detrimental to elite performance. This can be combined with poor behavioral mechanisms associated with increased stress, deficient coping strategies, lack of sleep hygiene, inadequate nutrition, reduced self-care habits, and neglected recovery [47], and has been found to increase the risk of injury development [48]. Exploring these risk factors through daily questionnaires, psychological screening, and chaplaincy may be worth addressing and exploring further in relation to HSI injury prevention in the AFL.

5. Holistic Approach to Injury Profiling

The broad aim of this scoping review was to provide practitioners with an informed approach towards the development of a holistic approach to HSI risk profiling generated from the past 20 yrs of published peer reviewed literature. For researchers, we intended to identify literature gaps that required further systematic investigation. As such our recommended HSI profiling in male AFL players should focus on modifiable risk factors and include the following:
  • Hamstring strength and in particular monitoring of eccentric hamstring strength is highly recommended. This requires further and up to date research, expanding the hamstring strength monitoring to also include the quadriceps, and systematically monitoring the H:Q ratio in male AFL players. We recommend that researchers in AFL consider exploring the utility of the eccentric H:Q ratio, as this been proposed as more reflective of injury mechanism than conventional concentric ratios [37,49].
  • Application of a practical and contemporary technique for determining lower body stiffness, such as that reported by Watsford and associates [25].
  • Athlete wellbeing and behavioral monitoring inclusive of sleep, recovery, nutritional habits, and psychosocial factors. However, researchers need to determine stronger causational links between negative psychosocial factors and increased HSI risk.

6. Limitations

This study has several limitations. Because of its design (scoping review), we did not conduct an analysis of the quality of the included studies. Readers should note the current scoping review does not focus purely on RCTs, and hence using a methodological quality assessment tool such as the PEDRO score is not suitable. We also did not include any grey literature in our scoping review search, which may have inadvertently biased our interpretation of HSI risk factor monitoring methods. Furthermore, this scoping review did not seek to exclude studies based on quality, and we purposefully included non-RCTs. Appreciating the role that methodological quality can have on outcome interpretation, we sought not to provide commentary on the methodological rigour or quality of the included studies.
In this study, we limited the search to very strict criteria, thus imposing a constraint of extrapolating these findings to other domains such as female, recreational, or other field team sports athletes. Lastly, there is a paucity of literature on the H:Q ratio that could be included into our search. This was a surprise to the authorship team as the H:Q ratio is a tool of importance and high use in other sports [50,51]. While we specifically searched using broad terms related to strength assessments of the hamstring and quadriceps muscles, researchers may need to consider deliberately including the terms “Hamstring: Quadriceps” and “H:Q ratio”. However, the concern with including these terms is the potential to inadvertently impose an investigator bias on the search outcome because of the specific nature of the term. This scoping review has potentially highlighted that either a change in practice and or a reduction in the availability of isokinetic dynamometry for monitoring purposes either due to time constraints when testing large numbers of athletes or the financial burden of accessing an isokinetic dynamometer has occurred in practitioners and researchers working with AFL athletes. If a change in practice has not occurred, then there is a clear evidence gap for researchers working with these athletes to report their findings.

7. Advances in Hamstring Injury Risk Prediction and Monitoring

The last three years have witnessed remarkable advancements in hamstring injury prediction and monitoring, particularly within professional football (soccer) and other professional team sports. Although reports specific to AFL are scarce, as seen in the low number of articles identified in this scoping review, the reported outcomes are applicable. Machine learning algorithms now integrate multimodal data from wearable technology, force plates, and player workload metrics to create more precise population-based risk profiles [52,53], with athlete-specific baselines becoming standard for injury prevention protocols in elite professional soccer [54,55,56]. The integration of machine learning into predictive modeling systems shows considerable promise for injury reduction; however, this approach often faces practical limitations in clinical settings due to overly broad injury definitions and imprecise prediction windows [57].
The development and integration of advanced monitoring systems within comprehensive athlete management platforms has revolutionized communication between medical staff, coaches, and players, creating more responsive intervention strategies based on dynamic risk assessment rather than static prediction models [28]. This holistic approach has been particularly effective in soccer, where fixture congestion and travel demands create unique recovery challenges.

8. Conclusions

This scoping review assisted in mapping concepts underpinning the risk factors associated with HSIs in the AFL for our advisory group, a club participating in the AFL, using a biopsychosocial perspective of the injury. Risk factors identified through this scoping review will help develop comprehensive injury profiling for athletes. Further meta-analysis and systematic review are warranted to appraise the quality of evidence and prioritize the importance of these risk factors. The ability to predict injury is limited due to the lack of psychosocial factors examined in the literature for hamstring injuries compared with other sports and soft tissue injuries. Further research is warranted to develop a holistic approach to injury profiling, and particularly in validating risk factor interactions using prospective cohort studies, to inform our consumers about best evidence-based practice in hamstring injury so that they can evaluate their current program for adjustment and ultimately help reduce the injury rate of hamstring injuries in the AFL.

Author Contributions

Conceptualization, D.W.C., K.N. and R.W.; methodology, S.H., S.S., N.T., D.Ø., K.N. and R.W.; data curation, S.H., S.S., N.T. and D.Ø.; writing—original draft preparation, S.H., S.S., N.T. and D.Ø.; writing—review and editing, D.W.C., K.N. and R.W.; supervision, D.W.C., K.N. and R.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Encyclopedia 05 00072 g001
Figure 1. Flow diagram illustrating different phases of data charting process; based on PRISMA recommendations. * Databases as identified in Section 2.2; ** Excluded records as per the defined criteria in Section 2.1 and Table 1.
Figure 1. Flow diagram illustrating different phases of data charting process; based on PRISMA recommendations. * Databases as identified in Section 2.2; ** Excluded records as per the defined criteria in Section 2.1 and Table 1.
Encyclopedia 05 00072 g001
Table 1. Eligibility criteria applied according to PICOS model.
Table 1. Eligibility criteria applied according to PICOS model.
PICOS CategoryInclusion CriteriaExclusion Criteria
P (Population)Healthy adult male athletes playing Australian Rules Football at a professional, semi-professional, elite competitive level 1 and were 18 yrs or olderFemale-only participants, or the male-only data could not be extracted; based on participants competing at non-elite or non-professional level; incorporated participants who were non-Australian Rules Football athletes
I (Intervention)Studies analyzing screening tools or assessments for HSITraining studies outcomes only with no use of screening tools or assessments
C (Comparators)OptionalExamining the effect of HSI rehabilitation or prevention programs, or reviewing return to play (RTP) criteria post-HSI
O (Outcomes)New data on musculoskeletal morphology, functional performance, and biopsychological risk factors in HSIsReview papers, conference proceedings, or case studies
S (Study designs)No restrictions on the types of study designs eligible for inclusionN/A
1 An international framework defined this as ‘elite’ [20].
Table 3. Synthesis of results for non-modifiable factors.
Table 3. Synthesis of results for non-modifiable factors.
Risk FactorReferencePredictors of Injury
Results, p-Value, Odds Ratio (OR), Confidence Intervals (CI)
History of HSI[6]
  • A player reporting a hamstring injury within the previous year (OR = 3.7, p = 0.01) or greater than 1-year (OR = 3.6, p = 0.01) was significantly associated with subsequent HSI.
[26]
  • Previous HSI in the last 12 months carried a statistically significant risk of hamstring reinjury (RR = 5.3, 95% CI 1.8–15.4, p = 0.006).
Age[6]
  • Player age greater than 25 years (OR = 2.9, 95% CI 1.1 to 7.6, p < 0.05) was associated with increased risk of HSI.
[25]
  • Injured players (mean = 27 +/− 3.4 years) were significantly older than the uninjured players (mean = 22.6 +/− 3.5) (p < 0.01).
History of lower limb injury (groin, calf and ACL)[6]
  • A history of groin injury was significantly associated with subsequent hamstring injury (OR = 8.6, p < 0.01).
  • A history of calf injury was significantly associated with subsequent hamstring injury (OR = 4.6, p = 0.01).
[4]
  • Past history of calf injury increased HSI risk (RR 1.58, 95% CI 1.37–1.82).
  • Past history of ACL reconstruction (RR 1.69, 95% CI 1.09–2.60).
Size of a hamstring injury on MRI[27]
  • A larger size of initial hamstring injury, as measured by MRI, was associated with an increased risk for recurrent injury (p < 0.001).
  • A measured transverse size of injury greater than 55% of the muscle, or calculated volume of injury greater than 21.8 cm3, resulted in an increased risk for hamstring recurrence of 2.2 (95% CI, 0.88–5.32) and 2.3 (95% CI, 0.94–5.81) times, respectively, when compared to athletes with hamstring injuries below these measurements.
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Chapman, D.W.; Humphreys, S.; Spencer, S.; Tai, N.; Øyen, D.; Netto, K.; Waller, R. A Scoping Review for Hamstring Injury Risk Monitoring in Australian Rules Football. Encyclopedia 2025, 5, 72. https://doi.org/10.3390/encyclopedia5020072

AMA Style

Chapman DW, Humphreys S, Spencer S, Tai N, Øyen D, Netto K, Waller R. A Scoping Review for Hamstring Injury Risk Monitoring in Australian Rules Football. Encyclopedia. 2025; 5(2):72. https://doi.org/10.3390/encyclopedia5020072

Chicago/Turabian Style

Chapman, Dale Wilson, Sorcha Humphreys, Shannon Spencer, Nathan Tai, Dag Øyen, Kevin Netto, and Robert Waller. 2025. "A Scoping Review for Hamstring Injury Risk Monitoring in Australian Rules Football" Encyclopedia 5, no. 2: 72. https://doi.org/10.3390/encyclopedia5020072

APA Style

Chapman, D. W., Humphreys, S., Spencer, S., Tai, N., Øyen, D., Netto, K., & Waller, R. (2025). A Scoping Review for Hamstring Injury Risk Monitoring in Australian Rules Football. Encyclopedia, 5(2), 72. https://doi.org/10.3390/encyclopedia5020072

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