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Abstract
Introduction Hamstring muscle injuries (HMI) continue to plague professional football. Several scientific publications have encouraged a multifactorial approach; however, no multifactorial HMI risk reduction studies have been conducted in professional football. Furthermore, individualisation of HMI management programmes has only been researched in a rehabilitation setting. Therefore, this study aims to determine if a specific multifactorial and individualised programme can reduce HMI occurrence in professional football.
Methods and analysis We conducted a prospective cohort study over two seasons within the Finnish Premier League and compare the amount of HMI sustained during a control season to an intervention season. Injury data and sport exposure were collected during the two seasons (2019–2020), and a multifactorial and individualised HMI risk reduction programme will be implemented during intervention season (2020). After a hamstring screening protocol is completed, individual training will be defined for each player within several categories: lumbo-pelvic control, range of motion, posterior chain strength, sprint mechanical output and an additional non-individualised ‘training for all players’ category. Screening and respective updates to training programmes were conducted three times during the season. The outcome will be to compare if there is a significant effect of the intervention on the HMI occurrence using Cox regression analysis.
Ethics and dissemination Approval for the injury and sport exposure data collection was obtained by the Saint-Etienne University Hospital Ethics Committee (request number: IORG0007394; record number IRBN322016/CHUSTE). Approval for the intervention season was obtained from the Central Finland healthcare District (request and record number: U6/2019).
- Prevention
- Sprint
- Sports
- Hamstring
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INTRODUCTION
In professional football, hamstring muscle injuries (HMI) account for 20–26% of all sustained injuries,1 2 making them one of the most prevalent. Furthermore, nearly one-third of HMI have been reported to recur.3 HMI has been considered a long-lasting, unresolved problem within football4; according to some research, HMI have increased.5 Due to lost playing and training time, HMI is considered being one of the largest burdens in professional football, including diminished performance and financial loss.2 5 Therefore, there is a need to continue improving HMI risk reduction strategies.
HMI are most often sustained during sprinting, but also commonly via slide tackling (overstretch), cutting (change of direction) and kicking.1 Multiple intrinsic risk factors have been established with large variation in importance, some of which are unmodifiable, including age, gender, ethnicity and injury history.4 6 Possible modifiable intrinsic risk factors include the strength of the hamstring and surrounding lumbo-pelvic muscles, strength asymmetry, fatigue tolerance, muscle architecture, range of motion (ROM), lack or excess of high-speed sprinting and sprint performance technique.4 7 Therefore, by present-day standards, the underlying optimal strategy to manage HMI is generally agreed to be multifactorial.4 7 8 Furthermore, these training strategies should be contextualised to the general demands of the sport and changes within practice. Practitioners and scientists contest the extent to which each intrinsic risk factor can be modified and how each of them should be trained.4 7–10 Multiple intervention programmes within football have aimed to reduce the risk of HMI by unifactorial means, with both the largest focus and success given to isolating improvements in eccentric knee flexor strength.11–13 However, to the best of our knowledge, no multifactorial injury reduction studies have been conducted in professional football settings where the demands are arguably the highest.
Additionally, there are no unifactorial or multifactorial HMI risk reduction studies using high-speed sprinting as a training method. This is despite evidence showing that the potential lack of optimal sprinting kinematics,14 15 a lack of exposure to maximal velocity sprinting16 and even lower sprint performance17 are risk factors associated with lower body and HMI in sprint-based team sports. The inclusion of sprint work is further made compelling by the fact that sprint performance capability is considered one of the key performance tests distinguishing lower- and higher-level football athletes.18 19 The muscle activity of the hamstrings in sprinting surpasses common hamstring strengthening exercises,20 which supports their use as a time-efficient means of training for performance and injury risk reduction simultaneously. This in return could foster cooperation between team physiotherapists and strength and conditioning coaches, which might help create a multidisciplinary practical approach for reducing the risk of HMI.
Although a general multifactorial injury risk reduction approach is likely needed, professional football players vary substantially in how many risk factors they possess.3 Therefore, from a holistic injury management perspective, a multifactorial approach should be individualised.4 7 21 Specifically, individualisation is an approach where training towards a certain common outcome, such as reducing injury occurrence (eg, injury risk reduction programmes), is constructed to a certain extent independently for every player. This is done by first evaluating what training stimuli a certain individual seems to require based on categories of ‘screening’ tests. Research within football using individualised training for HMI risk reduction has only been completed once,22 whereas research including individualised multifactorial training has only been performed within a hamstring rehabilitation setting.21 Individualisation can also be done by merely manipulating the training volume of a certain stimuli or even within exercise selection depending on the situation.23
Therefore, this study aims to determine if a specific multifactorial and individualised programme can reduce the occurrence of HMI in a professional football setting.
METHODS AND ANALYSIS
Study design and procedure
We conducted a prospective cohort study over two professional football seasons. The 2019 season serves as the control season, including sport exposure and injury data collection. The 2020 season serves as the intervention season, including the implementation of a multifactorial and individualised HMI risk reduction programme in addition to the sport exposure and injury data measurements obtained, as per the control season. The study design is presented in figure 1.
Study design. The study includes one control season (2019) and one intervention season (2020) with a total of three measurements.
Participants
The participants were recruited from teams within ‘Veikkausliiga’, the professional football premier league in Finland. For each team, the recruitment will be done by separately contacting each team’s strength and conditioning coach and physiotherapist. The teams within the league without a full-time strength and conditioning coach and a physiotherapist are included in the present study. Thereafter, the objectives, procedure and risks of the study are explained orally and in written format by the leading author (JL) to the staff and players. Strong contact networks have already been established with all the participating teams due to an ongoing collaborative research projects within the same league. Subsequently, players were included or excluded based on the criteria presented in table 1.
Inclusion and exclusion criteria
Written consent for the study will be sent via email at least 1 week prior to initial testing, and participants must have signed consent. Players under 18 require parental approval. Participation is entirely voluntary, and they may refuse any test or exercise at any time and for any reason. Participation, suspension or exclusion will in no way affect the position of those recruited for research in their team community.
Patient and public involvement
Many of the researchers (JL, JM, LA, TK, MK, AM, VP, MT and R-MT) involved in the present study have worked and continue to work in clinical practice dealing with injured football players. As they have shared their stories underpinning injury occurrence, these football players indirectly assisted in the hypothesis-making process for the current study. No football players were, however, invited to take active part in the design of the current study via, for example, knowledge-transfer scheme.
Primary outcome: HMI
Injury definition and data collection
Injury is defined as traumatic or overuse physical damage that occurred during a scheduled training session or match that caused absence from the next training session or match.24 Injury data are prospectively collected and registered by each team’s physiotherapist, using a standardised report form including the date of injury, circumstances (match/training), injury location, type, cause and date of return to play.
Hamstring muscle injury definition
The primary outcome of the present study will be the occurrence of HMI. HMI is defined as an injury, located at the posterior side of the thigh, and involving muscle tissue. Hamstring injuries defined as cramping/spasm are also included as muscle injuries. The diagnosis will be made by interview and physical examination of the players and confirmed by ultrasound or MRI.
Other data collection
Anthropomorphological measurements and player information
The players’ body mass (in kg), height (in cm), age (in years) and player position are registered at the start of each of the two seasons. Further, the moment arm distances are measured at the knee and hip during manual dynamometry strength testing so that strength can be reported in torque format.
Sport exposure definition and data collection
Sport exposure is defined as weekly training hours and matches within each team’s season. This data will be collected by either the team strength and conditioning coach or physiotherapist.
Physical coach staff education
After measurements, full responsibility will be given to each team’s physiotherapist and strength and conditioning staff to instruct and monitor the completion of the training programme. To ensure high standards, video material and a weekend workshop were organised for all strength and conditioning coaches, physiotherapists and other practitioners responsible for injury risk reduction within the team.
All staff participating in the educational workshop and subsequent data collections complete two questionnaires at different time points during the study to improve the qualitative interpretation of results (online supplemental tables 8 and 9). The first questionnaire, completed at end of the 2019 season but before the educational workshop, aims to clarify understanding of current HMI risk reduction practices within the team. The second questionnaire, completed before the end of the intervention season, aims to determine what training categories and methods of the intervention the participating staff consider to be the most impactful on their practice compared to the control season. It includes their opinion on the compliance of the players. Furthermore, the lead author (JL) of the study will be fully available for questions during the entire study.
Supplemental material
Intervention: multifactorial and individualised HMI risk reduction programme for professional football
Each player’s HMI injury risk reduction training protocol will be largely based on the results of the multifactorial hamstring screening protocol results, which determines individualised training targets. The implementation of the entire injury risk reduction training protocol will be managed by the team’s strength and conditioning coach and physiotherapist after being fully educated at the end of the control season.
Overview of the hamstring screening protocol for football (Football Hamstring Screening)
The intervention season includes three sessions of screening tests over the ~42-week season (figure 1). For each team, all screening tests were performed within a 2-day period and completed once at the start of pre-season (PRE), once at the end of the pre-season or start of the season (POST1) and a final test mid-season (POST2). Due to different scheduling of team practices, teams were screened within 3 weeks of each other.
The Football Hamstring Screening (FHS) protocol will be divided into the following categories that we considered important for football players: lumbo-pelvic control, ROM, strength and sprint mechanical output (figure 2). All clinical tests included in the lumbo-pelvic control, ROM and strength assessment total of 20 min per player. The sprint mechanical output test, which will be combined with sprint kinematic ‘kick-back’ analysis for the lumbo-pelvic control screening category, lasts 3–5 min per athlete or 10–15 min for the entire team. To improve reliability, all tests within each team were performed by the same experienced clinician (JL) with a mandatory familiarisation for all clinical screening tests 1 week pretesting. Appropriate initial steps are taken to help transfer the screening protocol into practice. Reliability testing has been conducted (manuscript in revision) in combination with a prospective cohort study to help support the FHS protocols validation in accordance with Bahr et al. 25
Hamstring screening protocol and training programme selection. Initially, the football player is tested within four screening categories. A percentile method within each team is used in all categories to define whether a player’s test outcome is positive or negative. Further, asymmetry is measured in the ROM and strength screening categories, adding further detail to the programmes. ASLR, Active Straight Leg Raise; FHS, Football Hamstring Screening; MDM, manual dynamometer.
Efforts are made to standardise the order and timing in which teams and players are screened and the given exposure time to the training intervention before post screenings are initiated. The FHS protocol is divided into clinical tests and sprint tests, both of which are tested before practice and/or on a rest day. To control for fatigue, players completed clinical testing a minimum of 72 hours post matches,26 whereas sprint testing will be completed a minimum of 96 hours post matches.27
This research project will be specifically designed so that both the screening and training protocols can be efficiently integrated into the athletes’ training environment. This will be possible as the teams already have reserved time slots for their own frequent testing and physical training protocols, and the changes made by the research protocol were made in their own training environment and support the general aims of their practice.
Lumbo-pelvic control tests
Lumbo-pelvic control will be tested via one clinical test and one sprint kinematics test done in parallel with sprint mechanical output testing. The first lumbo-pelvic control test, that is a part of the clinical tests, is named the ‘walk test’, which uses a validated WIVA digital gyroscope (LetSense Group, Castel Maggiore, Italy) to estimate 3D pelvic kinematics in walking.28 It has greater intrasubject and intersubject repeatability for pelvic kinematics measurements compared with stereo optoelectronic systems.29 To further improve reliability, we use a composite score of the sagittal and frontal plane pelvic movement in normal gait. The test includes the player walking 10 m forward and back twice with the WIVA digital gyroscope attached to the S1/L5 junction.
The second lumbo-pelvic control test will be included in the 30 m maximal sprint performance test, which assessed simple sagittal plane 2D upright sprinting kinematics using a high-speed camera (240 fps) at the 22.5 m mark, 11 m perpendicular to the line of sprinting. This test aims to indirectly assess suboptimal sagittal plane lumbo-pelvic movement in sprinting by focusing on the lower-limb angles at touchdown and toe-off (figure 3). Excess rotational work being completed by the lower limbs ‘behind the body’ (centre of mass) is associated with the ‘kick-back’ mechanism and is a sprint coach concept related to the quality of ‘front-side mechanics’.30 Angles are calculated based on the mean value of two strides (touchdown and toe-off) within two maximal sprints using Kinovea video analysis software (v.0.8.15), and an example of the calculation method is provided in figure 3.
The ‘kick-back’ mechanism is quantified by composite angle score within the sprint stride; the contralateral thigh angle at touchdown and the ipsilateral thigh angle at toe-off. Angles were placed after first manually digitizing of the hip, and knee joint centres. Less (A) or more optimal (B) is based on both anecdotal evidence from practitioners and Schuermans et al 14 results (see figure 4 for a similar visual). The less or more optimal movement is also visualised with tracking the foots path through the sprint stride cycle. Within each team, football players’ kick-back mechanism will be classified as positive if they are ranked at or under the team’s percentile of 33%, corresponding to increased lumbo-pelvic training.
ROM tests
The FHS protocol includes two ROM tests: Active Straight Leg Raise (ASLR) and a new proposed test named the ‘Jurdan test’ (figure 4C and D). After one familiarisation repetition, tests are performed twice at a slow pace (3 s), and angles averaged for improved reliability using a validated digital goniometer app (Goniometer Records, Indian Orthopedic Research Group).31
Range of motion tests used in the study. Picture (A) and (B) are from the Active Straight Leg Raise test (ASLR) and pictures (C) and (D) from the ‘Jurdan test’. Within each team, football players’ range of motion will be classified as positive if they are ranked at or under the team’s percentile of 33% in any of the range of motion tests, corresponding to increased range of motion training. If asymmetry is found between legs (≥15%), increased range of motion training will be prescribed for the less flexible leg.
The ASLR test has been shown to be a high reliability active hamstring flexibility test, where the thigh angle is measured from a controlled straight leg lift in supine position.32 The Jurdan test is new to the literature and is derived from anecdotal observations by experienced health professionals to be an interesting option for further scientific scrutiny. The aim of the test is to demonstrate the interaction between hip flexor and hamstring flexibility, which has been considered a potential risk factor in sprinting.33 The Jurdan test position and execution is considered to be a combination of the modified Thomas test34 and the active knee extension test.32 Initially, the participant is supine in a similar position to the modified Thomas test but is asked to complete an active knee extension (holding the thigh at 90°) while holding the table and holding the lumbar spine in contact with the table. The lumbar position will be verified kinaesthetically by the practitioner in the starting position and visually during execution. Maintenance of the thigh angle at around 90° for the active knee extension during testing is visually verified. The result will be defined as the difference between the actively lengthened legs shin angle and the opposite legs passive thigh angle (which is hanging over the table’s edge). Both angles are measured relative to horizontal. From figure 4C and D, this corresponds to the following calculation: 53°—(−16°)=69°, where 53° is the shin angle and −16° is the opposite leg’s negative thigh angle. Another example result that leads to the same value, but different ROM values would be 72°–(3°)=69°, where 72° is the shin angle and 3° is the opposite leg’s positive thigh angle. Therefore, this composite angle does not focus on which specific leg’s ROM is potentially the most problematic but instead focuses more on the leg interaction. This also corresponds to the approach behind the selected risk reduction ROM exercises in the training programme.
Posterior chain strength tests
Isometric strength for hip extensors and knee flexors will be assessed using a handheld dynamometry method in previously described reliable positions.35 36 Participants laid in a prone position on a table while strapped from the waist (figure 5). The knee flexors are tested in 0° of hip extension and 30° of knee flexion with force placed on the heel. The knee flexion angle start position will be verified by the digital goniometer. As no apparatus will be used to hold the knee flexion position during contraction, shielding during contraction is expected to be around 5°. The hip extensors are tested in a 0-degree position with the knee extended to 95–100° with force placed on the distal tibia. The dynamometer will be placed at ~5 cm from knee flexion crease,33 which determines how far the shin needs to be pushed backed so that the calf muscle is not in the way. A belt will be placed across the hips to avoid raising of the gluteals during the test.
Posterior chain strength tests. The hip extensors are tested in position (A) and knee flexors in position (B). Within each team, football players’ knee flexor strength and hip extensor strength are separately classified as positive if they are ranked at or under the team’s percentile of 66%, corresponding to increased strength training for the respective joint. If asymmetry is found between legs at any joint (≥15%), increased training is prescribed for the weaker leg.
Sprint mechanical output test
Players perform two 30 m maximal sprints in sequence with football practice. Specifically, sprints are performed after the team’s normal sprint testing warm-up protocol and with 3 min of passive recovery between sprints. Sprint performance (split times 0–5, 0–10, 0–20 and 0–30 m), maximal velocity and sprint mechanical output (ie, maximal theoretical horizontal force (F0)) are computed using a validated field method measured with a radar device (Stalker ATS Pro II, Applied Concepts, TX, USA) as reported previously.37–39 Briefly, this computation method for F0 is based on a macroscopic inverse dynamic’s analysis of the centre-of-mass motion. Raw velocity–time data wereare fitted by an exponential function. Instantaneous velocity data are then be combined with system mass (body mass) and aerodynamic friction to compute the net horizontal antero-posterior ground reaction force.39 Individual linear sprint force–velocity profiles are then extrapolated to calculate relative F0.
Individualised HMI risk reduction protocol
Training within the HMI risk reduction protocol will be completed in the exact same categories as used within the FHS protocol: lumbo-pelvic control (table 2), ROM (table 3), posterior chain strength (table 4) and sprint mechanical output (table 5). In every screening test category, football players are either ranked as positive or negative within each team and then accordingly given individual training protocols that are instructed by each team’s coaching staff (figures 2 and 6). The approach for determining positive and negative cut-offs is explained in more detail in the following section. Each individualised training protocol includes the same exercises for all players, but the training volume varied based on the individual. In practical terms, if a weakness is found (ie, ‘positive’ result), the player should work on the weakness more. However, due to the physical requirements in football, even those with negative test scores complete maintenance training within each category; therefore, all players benefit from at least minimal lumbo-pelvic, posterior chain strength, ROM and sprint mechanical output training.
Lumbo-pelvic control
Range of motion (ROM)
Posterior chain strength
Sprint programming
Brief rationale and programming methods of each training category during the entire season. In the last column, each square block represents one training session during the week. The number of blocks for every athlete are defined by the screening protocol outcomes. Target training volume is based on one match weeks. A full exercise list is provided in tables 2–7. *To avoid fatigue, hip and knee strength asymmetry are not tested within the same session.
Sprint drills programming
Cut-offs used for individualisation of the HMI risk reduction protocol
Individual training protocols are designed largely based on a percentile cut-offs within each team in all four screening categories. These percentiles are based on both evidence-based guidelines and consistent anecdotal evidence from experienced practitioners within professional football in the research team. Current evidence suggests that strength training has the highest validity in injury risk reduction.10 This is why the posterior chain strength category includes the highest cut-off percentile to classify positive or negative players compared to the other categories. This means that there is a higher likelihood that a player will be ranked as positive in the posterior strength training category compared to ROM and lumbo-pelvic control, leading to an increased training volume. Specifically, the higher percentile of 66% has been chosen for posterior chain strength, whereas ROM and lumbo-pelvic control have a lower cut-off percentile of 33% (figure 6).
In practical terms, based on the screening scores in the lumbo-pelvic and ROM categories, a positive result (percentile ≤33%) corresponds to a target training volume of four times per week and a negative result (percentile >33%) corresponds to a target volume of twice per week. If there is more than one positive in a specific testing category, it has no further influence on the training protocol, with an exception made for the categories that include limb asymmetry measurements. Limb asymmetry will be measured in the ROM and strength categories, defined as a 15% difference between sides.22 If an asymmetry is found within the ROM category, an extra set for all ROM exercises will be placed for the stiffer leg four times per week. If an asymmetry is found within the posterior strength category (hip extensor and/or knee flexor), an extra set within one exercise is required for the weaker leg once per week.
In the posterior chain strength category, a positive result (percentile ≤66%) corresponds to a target training volume of twice per week and a negative result (percentile >66%) corresponds to a target volume of once per week. The sprint mechanical output training category has the same percentile as the strength training category. In this case, both upper and lower horizontal force output players have the same training frequency, but the lower 66% has heavier resistance for early acceleration work, while the upper percentile predominantly works with lighter resistance. This is based on our research group’s data currently in review, showing that players with elevated F0 output will likely respond less, or even not respond, to heavy loading.
Figure 6 provides more detailed aims for each training protocol category and how the test outcome, either positive or negative, determines the corresponding individualised weekly training session frequency (volume).
Non-individualised part of training within the intervention protocol
As briefly explained in figure 6 in the training category of ‘Training for all players’, as a research limitation, we found that some training stimuli will be impractical to provide on an individualised level versus a group level. These training subcategories include high-speed sprinting, post-sport ROM, triceps surae health and manual therapy (table 6). High-speed sprinting has been selected due to its potential benefits on injury risk reduction,16 and provides an opportunity to work on the athletes' sprint ‘technique’. Furthermore, this possibly contributes to improved lumbo-pelvic control (publication from our group in progress). This will be performed via different drills (table 7) and tools such as wicket hurdles. Post-sport ROM aims to relax the hamstrings and the latissimus dorsi after practice. The hamstrings are relaxed via a proposed compliance stimulus to the muscle-tendon unit via a light long contraction in a stretched position,40 in theory counteracting the high stiffness stimuli provided from football practice. The latissimus dorsi will be relaxed by completing 10 deep breaths in a stretch relax format, with the aim to counteract stiffening and a possible anterior pull on the pelvis.41 The third subcategory will be triceps surae health. This subcategory has been chosen based on evidence suggesting ankle and hamstring injuries may be related in linear sprinting.42 Neural adaptations are prioritised with isometric holds at short muscle length ankle positions that are specific to sprinting (initial contact and mid-stance angles).43 This in turn may improve stiffness and support overall improvements in sprint performance and technique.44 Longer muscle length isometric holds have been shown to stimulate structural adaptations43 and longer isometric holds seem to contribute to overcoming tendon stress shielding caused by repetitive microtrauma.40 45 Therefore, to support the players’ seasonal triceps surae load tolerance, long isometric holds at longer muscle lengths are used. The fourth subcategory, manual therapy, aims to more precisely influence compliance of the hamstrings and muscle tissues, possibly affecting anterior pelvic tilt. Manual therapy will be performed ideally by the team physiotherapist to the adductor magnus, erector spinae, latissimus dorsi and hamstrings. If manual therapy treatment is not available within a specific week, it is replaced by foam rolling to the same tissues (table 3).
For all players exercises and treatments
Programming guidelines and compliance
General advice is provided to all teams on the ideal placement of training categories during one match (figures 7) and two match weeks (figure 8). Exercises have been designed considering budget differences between teams to reduce bias favouring higher programme completion rates in better funded teams. Teams are advised to complete the following: lumbo-pelvic control and ROM training as a pre-warm-up; strength training so that hip strength, hamstrings, and triceps surae health are trained in the same time slot; sprint mechanical output and high-speed sprinting in combination with the team warm-up; manual therapy on off-days; and post-sport ROM after the last session of the day. Based on our ongoing discussions with the teams, there are both similarities and inevitable differences in weekly programming of the training categories due to different team cultures. For example, some teams’ physical coaching staff might not be provided sufficient time to complete the entire training programme. All teams have already confirmed the entire staff would collaborate to provide the highest compliance possible, but the reality is portrayed in the compliance data.
Example week for individualised and team programming for one match per week (on Saturday in this example). A hypothetical scenario is demonstrated based on one player’s screening results. Each team finds slightly different solutions to fit in the training blocks, which are discussed in the main publication.
Example week for individuali'sed and team programming for two matches per week (Wednesday and Sunday in this example). On double match weeks, training sessions will be to different degrees sacrificed for improved recovery (red crosses).
Therefore, each week the coaching staff records all completed sessions for all players within each training component. Furthermore, in training within the high-speed sprinting subcategory, all sprints instructed to be at or over 90% are reported in metres. All the data are anonymously uploaded to a server every week for verification. From here, the compliance to the intervention training protocol is calculated each week: (completed intervention sessions/intervention training target)×100. This will be done in each training category so that compliance with specific training forms can be measured. A full report of team training schedules within a typical week is provided as online supplementary material once the study has been completed.
Sample size calculation
According to the literature, about 22% of the professional football players sustain a hamstring muscle injury during a season.5 We believe that we can obtain a relative risk reduction of 66% by implementing the multifactorial and individualised programme, which has been shown to be realistic based on previous hamstring risk reduction literature showing up to 50–70% reductions.11–13 This corresponds to obtaining a percentage of professional football players with a new hamstring muscle injury of around 7.5%. To attain a power of 80% (a=5%) we include 93 players per group, or 186 players in total. Estimating a dropout rate of 15%, 107 players are recruited per season, or 214 players in total. The number of participants necessary was calculated using the online UCSF Clinical & Translational Science Institute application (https://www.sample-size.net/sample-size-proportions/).
Statistical analysis
Descriptive analyses of the collected data (eg, player characteristics, screening test results, injuries, sport exposure) are first performed using frequency with percentages for categorical variables and mean with SD (±SD) for continuous variables. Descriptive statistics for the total number of HMI (and percentage of all injuries), duration of time lost from sport, HMI incidence (per 1000 hour of training, match and total football practice) and burden of HMI (number of days lost due to HMI per 1000 hour of training, match and total football practice) will be provided. Compliance with the training programme will be calculated.
To analyse the impact of the HMI risk reduction programme, we perform a Cox proportional hazards regression (or Cox regression) model using ‘seasons’ (ie, control season vs intervention season) as explanatory variables and the first occurrence of a ‘new HMI’ as outcome, adjusted for age, team, body mass, height and history of HMI (previous two seasons); the unit of analysis will be the individual player and time to first event will be analysed using cumulative hours of football practice (ie, training and competition) as a timescale. The HR with a 95% CI will be presented for each variable, and assumption that the HR will be constant over time will be tested.
Due to our main research question not being related to the changes in screening tests, we have not completed null hypothesis significance test statistics. However, to improve the relevance of discussions for clinicians, magnitude of difference statistics (effect size) will be performed for all screening categories between the three testing sessions.
ETHICS AND DISSEMINATION
This study has received two separate ethical approvals. The study protocol for the injury and sport exposure data collection used in the control season was reviewed and approved by the Saint-Etienne University Hospital Ethics Committee (Institutional Review Board: IORG0007394; IRBN322016/CHUSTE). This ethical approval was obtained in 2016 for conducting multicenter prospective injury data and sport exposure data collection but did not include the intervention. The study protocol for the intervention season was approved separately by the Central Finland healthcare District (U6/2019). Applying for one ethical approval that permitted for both prospective data collection from the 2019 control season followed by an intervention season was not possible, as the opportunity to conduct an intervention among professional football players was first provided in 2019, while prospective injury data and sport exposure data collection were in process. Thus, the ethical approval for the intervention protocol was accepted at the end of the control season (2019). Therefore, our present study relies on two different ethical approvals: one for prospective data collection only corresponding to the first part of the study and the control season, and other for the intervention corresponding to the second part of the study and the intervention season. This study will be conducted in accordance with the Declaration of Helsinki.
Prior to enrolment in the study, all participants were asked to give their informed consent. The participants can decide at any time to be released from the study, and they are informed of this in the information documents. If accepted, data obtained during this study are used by the research team until their papers are accepted for publication, but for a maximum of 5 years, after which all materials will be destroyed. Participation is entirely voluntary, and participants may refuse any test or exercise at any time and for any reason. Participation, suspension or exclusion from this research study will in no way affect the position of recruits in their team community.
Results are published in a peer-reviewed sport and exercise medicine journal, regardless of the findings related to the number of positive or negative hamstring injuries sustained between the two seasons. In order to enhance knowledge translation of the findings, a multimodal approach will be used for dissemination; findings are presented at conferences, and multimedia resources (eg, infographics, animations, videos, podcasts and blogs) are created to share findings via various social media platforms and through media release.
CONCLUSIONS
Although there has been a large effort to include up to date evidence-based exercises for HMI risk reduction,4 8 46 the aim of this study is not to answer what specific exercises (and their respective implementation strategies) are optimal. Our aim is to focus on the bigger picture and, thus, test the possible functionality of a specific multifactorial and individualised approach conceptualised for HMI risk in professional football.
There is consensus among sport scientists that multifactorial programming is necessary for hamstring injuries,4 9–12 and we hope this study provides an interesting first step despite inevitable methodological limitations. Ideally, the teams are randomised to either a multifactorial programme or both multifactorial and individualised programme. However, this is difficult to create in real-life professional settings as many teams likely already have multifactorial and individualised protocols in use to varying extents. Thus, it is likely implausible in many cases that professional teams would agree to complete an intervention where their current protocols would be downgraded for the benefit of research. The format in which the screening protocol data is used to identify players at risk and assign individualised training protocols could be considered to be another limitation. Another approach would use non-linear machine learning algorithms based on data from multifactorial testing, emphasising the idea that no single data point is important in isolation.47 These machine learning models are compatible with data that are considered important for most injuries in football, such as body mass, age, injury history, workload management and wellness scores. Ideally, before conducting such an intervention, the screening protocol should be properly tested for its accuracy in identifying risk using such models with an entire control season devoted to it. In addition, since our aim is to maximise the dissemination and implementation of the intervention programme in the professional football community, we prefer using a relatively straightforward approach. This also provides an approach compatible with the data processing skills of most practitioners in real-life professional football. Therefore, we use the team percentile method, and future follow-up studies should analyse the interest of more advanced prediction models. If the protocol is successful, the current approach may work in other football populations with similar baseline values. However, it is inevitable that this approach presents its limitations in the form of producing false negatives and not being able to appropriately address players that are true positives. Additionally, updates and replacements to testing methods are encouraged within each testing category as advances in validated technology take place. Furthermore, it is important to state that this type of musculoskeletal multifactorial approach should ideally be a part of a biopsychosocial approach used for all injuries.47 Finally, we acknowledge the fact that two separate ethical approvals were needed for one research project.
The strength of this study is its potential for direct practical implementation in teams with varying resources and budgets. We expect that reaching appropriate compliance is one of the greatest challenges facing this project. Most literature indicates that compliance is a clear problem in injury risk reduction protocols and likely explains the lack of results.2 9 46 48 Player buy-in will be paramount, which itself will be mediated by the coaching practices within each team. We are optimistic that an injury risk reduction programme that considers the individual, both from a risk reduction and performance standpoint, might increase the potential for long-term compliance.
Strengths and limitations of this study
This study helps to demonstrate the initial value of individualised training programmes based on a multifactorial hamstring screening protocol designed to reduce HMI in professional football.
All testing and training are implemented in the field. Therefore, if the approach is successful in reducing HMI (study outcome), it has a high potential for direct transfer into practice. This includes free video links of all exercises once the study is completed.
Normative data from the screening tests are published and provide a good initial reference database for practitioners looking to use the same tests.
This study lacks randomisation and blinding, and therefore, at best provides good but not the highest level of evidence for validity of the HMI risk reduction programme.
Comparing HMI between two separate seasons increases the risk of confounding factors affecting result interpretation.
REFERENCES
Footnotes
Twitter Johan Lahti @lahti_johan.
Acknowledgements We would like to thank all the teams and players participating in this project. We thank Matt R. Cross for his input on the manuscript. We also would like to thank the following sprint coaches for their input to our training programme format: Håkan Andersson, Jonas Dodoo and Stuart McMillan.
Contributors JL, PE, JM and JBM conceived the idea behind the study and JA, LA, TK, MK, AM, VP, MT and R-MT provided advice on the study design. JL, JA, LA, TK, MK, AM, VP, MT and R-MT are responsible for data acquisition and data management. JL, PE, JM, JA and JBM are responsible for statistical analyses. JA, PE and JL developed the health-, injury-, study information-, coaching questionnaire- and consent forms with feedback from JBM, JM. JL is the corresponding author. All authors are entitled to explore the data set and publish on prespecified hypotheses. JL drafted the article, while all other authors revised the article for important intellectual content. All authors read and approved the final manuscript.
Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.
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