A cross-sectional analysis was performed to investigate associations between environmental temperatures and injury occurrence in two professional male football (soccer) leagues. Data from seven seasons of the German Bundesliga (2142 matches) and four seasons of the Australian A-League (470 matches) were included. Injuries were collated via media reports for the Bundesliga and via team staff reports in the A-League and comprised injury incidence, mechanisms (contact, noncontact), locations (e.g., ankle, knee, and thigh), and types (e.g., muscle and tendon, joint and ligament). Weather data included ambient air temperature (temperature or T) and wet bulb globe temperature (WBGT), which were collected from online sources retrospectively. Generalized linear mixed models were analyzed to examine associations between temperature or WBGT and injury occurrence for each league, respectively. Additionally, matches were grouped into categories of 5°C temperature steps to compare for injury occurrence. Results showed no relationship existed between either temperature or WBGT and any injury occurrence, mechanisms, locations or types for the Bundesliga (P > 0.10). A trend for an increase in injury occurrence in higher WBGT existed in the A-League (P = 0.05). Comparisons between 5°C temperature categories showed no significant differences for injury occurrence for either temperature or WBGT in either League (P > 0.05). Within the observed temperature ranges (−11.2 to 37.1°C T; −12.2 to 29.6°C WBGT) environmental temperature had no relationship with the rate or type of injury occurrence in professional football. Nevertheless, the number of matches at extreme heat within this study was limited and other factors (e.g., playing intensity, season stage, ground conditions) likely co-influence the relationship with injuries.

Injury risk in professional football (soccer) is increased in the weeks following return-to-play (RTP). However, the time course of injury risk after RTP (the hazard curve) as well as its influencing factors are largely unknown. This knowledge gap, which is arguably due to the volatility of instantaneous risk when calculated for short time intervals, impedes on informed RTP decision making and post-RTP player management. This study aimed to characterize the hazard curve for non-contact time-loss injuries after RTP in male professional football and to investigate the influence of the severity of the index injury and playing position. Media-based injury records from the first German football league were collected over four seasons as previously published. Time-to-event analysis was employed for non-contact time-loss injury after RTP. The Kaplan–Meier survival function was used to calculate the cumulative hazard function, from which the continuous hazard function was retrieved by derivation. There were 1623 observed and 1520 censored events from 646 players analyzed. The overall shape of the hazard curve was compatible with an exponential decline of injury risk, from an approximately two-fold level shortly after RTP towards baseline, with a half-time of about 4 weeks. Interestingly, the peak of the hazard curve was slightly delayed for moderate and more clearly for severe index injuries. The time course of injury risk after RTP (the hazard curve) can be characterized based on the Kaplan–Meier model. The shape of the hazard curve and its influencing factors are of practical as well as methodological relevance and warrant further investigation.

To assess the players' risk of a subsequent injury after sustaining concussive injuries and their return-to-competition in German professional men's football. A prospective injury database in the 1 (st) Bundesliga was created encompassing 7 seasons (2014/15-2020/21). Cox proportional hazard model analyzed whether a concussive injury increased the risk of a subsequent injury in the first year after the index injury. 6,651 injuries were reported (n=182 concussive injuries). The incidence rate was 0.15 (95% CI 0.13-0.17) per 1000 football hours. A concussive injury was associated with only a slightly numerical higher risk of 7% (HR=1.07, 95% CI 0.78-1.47) in the subsequent year after the injury compared to a randomly selected non-concussive injury, but the effect was not significant. The risk was higher after 6-12 months post-SRC reaching 70% (HR=1.70, 95% CI 1.15-2.52). For 0-3 months (HR=0.76, 95% CI 0.48-1.20) and 3-6 months (HR=0.97, 95% CI 0.62-1.50) the injury risk was lower. The present data do not confirm previously published investigations about an increased injury risk after SRC. Contrasting effects of lower hazard ratios were found early after SRC, followed by an increase after 6-12 months. Further research should look into compliance rates with regards to return-to-competition protocols.

Background This study describes the implementation of a standardised, prospective injury database covering the entire 1st male German football league (“Bundesliga”) based on publicly available media data. For the first time, various media sources were used simultaneously as the external validity of media-generated data was low in the past compared to data obtained by way of the “gold standard”, i.e. by the teams’ medical staffs. Methods The study covers 7 consecutive seasons (2014/15–2020/21). The primary data source was the online version of the sport-specific journal “kicker Sportmagazin™” complemented by further publicly available media data. Injury data collection followed the Fuller consensus statement on football injury studies. Results During the 7 seasons, 6653 injuries occurred, thereof 3821 in training and 2832 in matches. The injury incidence rates (IRs) per 1000 football hours were 5.5 [95% CI 5.3–5.6], 25.9 [25.0–26.9] per 1000 match, and 3.4 [3.3–3.6] per 1000 training hours. Twenty-four per cent of the injuries ( n = 1569, IR 1.3 [1.2–1.4]) affected the thigh, 15% ( n = 1023, IR 0.8 [0.8–0.9]) the knee, and 13% ( n = 856, IR 0.7 [0.7–0.8]) the ankle. Muscle/tendon injuries contributed 49% ( n = 3288, IR 2.7 [2.6–2.8]), joint/ligament injuries 17% ( n = 1152, IR 0.9 [0.9–1.0]), and contusions 13% ( n = 855, IR 0.7 [0.7–0.8]). Compared to studies using injury reports from the clubs’ medical staff, media data revealed similar proportional distributions of the injuries, but the IRs tended towards the lower end. Obtaining specific locations or diagnosis especially with regard to minor injuries is difficult. Conclusions Media data are convenient for investigating the quantity of injuries of an entire league, for identifying injuries for further subanalysis, and for analysing complex injuries. Future studies will focus on the identification of inter- and intraseasonal trends, players' individual injury histories, and risk factors for subsequent injuries. Furthermore, these data will be used in a complex system approach for developing a clinical decision support system, e.g. for return to play decisions.

Abstract To assess head impact incidents (HIIs) and to distinguish diagnosed head injuries from other incidents, a video observation analysis of match HIIs was conducted in the German Bundesliga (2017/18 season). Video recordings of each match were screened to identify the respective events. Head injury data were identified by a prospective injury registry. HII and head injury incidence rates (IR) were calculated with 95% CIs. The total number of HIIs was 1,362 corresponding to an IR of 134.9/1000 match hours (95% CI 127.9–142.2). In 123 HII (IR 12.2, 95% CI 10.2–14.5) the contact was classified as severe. Head contact with the opponent was the most frequent cause (85%). The most frequent mechanism was in 44% (combined) the arm and elbow-to-head, followed by head-to-head and hand-to-head contacts (each 13%). In 58%, the HIIs occurred during header duels. Twenty-nine head injuries were recorded (IR 2.9, 95% CI 2.0–4.1). Concussions/traumatic brain injuries accounted for 48%, head/facial fractures 24%, head/facial contusions 21%, and lacerations/abrasions 7%. The number of HIIs not classified as concussions/more severe trauma was high. Identification of HIIs and head injury severity should be improved during on-field assessment as many head injuries might go unrecognised based on the large number of HIIs.

The coronavirus lockdown in 2020 resulted in a worldwide suspension of professional sports. The first major professional football league to restart after the lockdown was the German Bundesliga. This study investigates whether the injury incidence increased after the restart of the season with only 9 days of regular preparation time and without any friendly matches in comparison to three control periods. In a prospective cohort study, injury analysis (at least 1 day of absence from official football matches or training sessions) of the German Bundesliga registry was standardised according to Hägglund et al. (Br J Sports Med 39:340–346, 2005) and Fuller et al. (Clin J Sports Med 16:97–106, 2006) for data collection and to previous publications for the validated use of media sources for injury registration. The study period after the lockdown in May and June of the 2019–2020 season was compared to three control periods: the period directly before the lockdown, the beginning of the 2019–2020 season and the 2018–2019 season final. The nine match days after the restart of the 2019–2020 season showed an overall injury incidence of 4.9 per 1000 h football. This rate was significantly lower than that of the previous season final (9 last match days, overall injury incidence: 6.9 per 1000 h football; p < 0.001) and not increased compared to the rates after the summer break (9 match days; incidence: 5.5/1000 h, p > 0.05) or the winter break (8 match days; incidence: 5.6/1000 h, p > 0.05). The period after the unexpected break in the 2019–2020 season due to the coronavirus lockdown and the rapid return to competition showed no increase in the injury rate compared to the pre-lockdown period and a lower injury rate than in the previous season final. The unintentional mid-season rest with its potential for physical recovery and individual fitness training seems to have had a positive effect on injury occurrence.

Many professional football players sustain at least one severe injury over the course of their career. Because detailed epidemiological data on different severe injuries in professional football have been missing so far, this study describes the frequency and return-to-competition (RTC) periods of different types of severe football injuries. This epidemiological investigation is a prospective standardised injury analysis based on national media longitudinal registration. Injuries were classified according to the consensus statement by Fuller et al. (2006). The analysis includes injuries sustained by players of the first German football league during the seasons 2014–2015 to 2017–2018. Level of evidence: II. Overall, 660 severe injuries were registered during the four seasons (mean 165 per season; 9.2 per season per team; incidence in 1000 h: 0.77). The body region most frequently affected by severe injury was the knee (30.0%; 49.5 injuries per season/SD 13.2) followed by the thigh (26.4%; 43.5 injuries/SD 4.2) and the ankle (16.7%; 27.5 injuries/SD 5.0). The distribution of injuries over the course of a season showed a trend for ACL ruptures to mainly occur at the beginning of a season (45.8%), overuse syndromes such as achillodynia (40.9%) and irritation of the knee (44.4%) during the winter months and severe muscle and ankle injuries at the end of a season. ACL ruptures showed the longest RTC durations (median 222 days). This study presents detailed epidemiological data on severe injuries in professional football. The body region most frequently affected by severe injuries was the knee. Several types of severe injuries showed a seasonal injury pattern. The appropriate timing of RTC after an injury is one of the most important and complex decisions to be made. This study provides information on the typical time loss due to specific severe football injuries, which may serve as a guideline.

Background Bayesian networks (BN) are directed acyclic graphs derived from empirical data that describe the dependency and probability structure. It may facilitate understanding of complex epidemiology by presenting the data in a multi-dimensional visual representation, and guiding inferences on the likelihood of the severity based on new information. Objective To provide a brief overview of BN and demonstrate its utility on a practical example of making inferences on days of absence when hypothetically new information was introduced. Design Retrospective analysis of prospectively collected injury data. Participants All male football players who were playing in the highest German professional league (Bundesliga) from 2014/15 to 2019/20 seasons were included. Players were identified from a publicly available database. Data analysis A BN structure was inferred using GeNIe 2.0. A search and score algorithm and existing empirical evidence knowledge were used to identify the structure. The variables included were age, height, weight, main position, part of the season, event, injury type, the injured body part, days of absence. The parameters were calculated with the expectation-maximization algorithm. Main Outcome Measurements Injury severity based on days of absence (mild: <4, minimal >4–7, moderate >7–28, severe >28). Results 3,030 player seasons were registered over the six seasons (age: 25.5±4.0, height (cm): 183.3±6.4 and weight (kg): 78.3±6.8), with 5,883 time-loss injuries. A network structure with distribution probability was built. A hypothetical scenario is used to illustrate how a BN makes inferences regarding injury severity. Case 1, a defender, 20 years old, suffered from a groin muscle injury. Case 2, a defender, 27 years old, suffered from a thigh muscle injury. Based on the BN constructed, we can infer the likelihood of the injury severity and the result is shown in Table 1. The result is based on the Bundesliga dataset and is specific to the study population. Counterfactual analysis may be used to inform coaches and clinicians about the likelihood of severity of an injury based on the features of the injury, for example, the characteristics of the player and the game. Conclusions The BN may offer an enhanced insight into the complex epidemiological systems and guide inferences on injury severity based on new information. This may potentially help clinicians in creating hypothetical scenarios on the severity and facilitate shared decision making.

OBJECTIVE:To identify risk situations promoting head injuries in professional male football (soccer) and to investigate the impact of a rule change in 2006 punishing elbow-head contacts.DESIGN:Analysis of video sequences of head events leading to head injury.PARTICIPANTS:Professional football players of the first male German Bundesliga.MAIN OUTCOME MEASURES:Observational criteria of head impacts on video recordings (players' actions preceding head injuries, foul play-referee's decision and assessment of rater, ball possession, on-pitch medical treatment, and consequences of head impact).RESULTS:Three hundred thirty-four head injuries were reported in kicker Sportmagazin corresponding to an incidence rate of 2.25 (95% confidence interval 2.01-2.51) per 1000 player match hours. The injured player predominantly jumped (60%), headed the ball (36%), or ran forwards (20%); the noninjured players mainly jumped (64%), headed the ball (27%), or raised the elbow to the head (23%). Free ball situations (2 players challenge for the ball) caused most of the head injuries (81%). The players' action "raising the elbow" during a head injury seemed to be lower after the rule change.CONCLUSIONS:Jumping for the ball with the intention of heading is the predominant action associated with head injury risk. Head injuries occur most often when players challenge for the ball in a header duel. As head injuries bear the potential risk of long-term health sequelae, the identification of situational circumstances is essential to develop preventative means in the future.

Background Absolute numbers of head injuries in football (soccer) are considerable because of its high popularity and the large number of players. In 2006 a rule was changed to reduce head injuries. Players were given a red card (sent off) for intentional elbow-head contact. Aims To describe the head injury mechanism and examine the effect of the rule change. Methods Based on continuously recorded data from the German football magazine "kicker", a database of all head injuries in the 1st German Male Bundesliga was generated comprising seasons 2000/01-2012/13. Injury mechanisms were analysed from video recordings. Injury incidence rates (IR) and 95% confidence intervals (95% CI) as well as incidence rate ratios (IRR) to assess differences before and after the rule change were calculated. Results 356 head injuries were recorded (IR 2.22, 95% CI 2.00 to 2.46 per 1000 match hours). Contact with another player caused most head injuries, more specifically because of head-head (34%) or elbow-head (17%) contacts. After the rule change, head injuries were reduced by 29% (IRR 0.71, 95% CI 0.57 to 0.86, p=0.002). Lacerations/abrasions declined by 42% (95% CI 0.39 to 0.85), concussions by 29% (95% CI 0.46 to 1.09), contusions by 18% (95% CI 0.43 to 1.55) and facial fractures by 16% (95% CI 0.55 to 1.28). Conclusions This rule change appeared to reduce the risk of head injuries in men's professional football.

Ruptures of the anterior cruciate ligament (ACL) typically occur in professional football and epidemiological data about longitudinal injury development is needed. This practice-driven investigation of media-derived ACL data provides information about professional football over 10 years. Injury registration was based on "kicker" sports magazine information that have been recorded over one decade in a standardized manner. Only ACL ruptures in the first German football league were included when they could be verified by a second reliable source. Level of evidence: III. Fifty-seven primary ACL ruptures were verified in the first German football league during the seasons 2007/2008 to 2016/2017. Among them, six re-injuries were found. Mean age at the time of injury was 24.8 years (SD 3.8). 31% (n = 20) of ACL ruptures occurred at the beginning of the season in August or September (p = 0.02). Mean time of RTC after primary ACL ruptures was 226.7 days (SD: 93.5) and 245.6 days (SD: 45.4) after re-injury. Although 62 (98%) players returned to football after injury and only one player immediately finished his career, 54.9% of the affected individuals played 3 years after the ACL rupture in the same league. ACL ruptures lead to longer absence than 7 months from football but does not give reason for immediate career-ending. The decrease in playing level after 3 years illustrate the serious consequences of ACL ruptures in football. Media-based injury reports may provide interesting information.

AbstractThe present study aimed to investigate time trends of head injuries and their injury mechanisms since a rule change as monitoring may help to identify causes of head injuries and may advance head injury prevention efforts. Based on continuously recorded data from the German football magazine “kicker Sportmagazin®” as well as other media sources, a database of head injuries in the 1st German male Bundesliga was generated comprising 11 seasons (2006/07–2016/17). Injury mechanisms were analysed from video recordings. Injury incidence rates (IR) and 95% confidence intervals (95% CI) were calculated. Time trends were analysed via linear regression. Two hundred thirty-eight match head injuries occurred (IR 1.77/1000 match hours, 95% CI 1.56–2.01). There were no significant seasonal changes, expressed as annual average year-on-year change, in IRs over the 11-year period for total head injuries (p=0.693), facial/head fractures (p=0.455), lacerations/abrasions (p=0.162), and head contusions (p=0.106). The annual average year-on-year increase for concussion was 6.4% (p=0.004). Five head injury mechanisms were identified. There were no seasonal changes in injury mechanisms over the study period. The concussion subcategory increased slightly over the seasons, which may either be a result of increasing match dynamics or raised awareness among team physicians and players.