Rugby league is a collision sport that involves frequent periods of high-intensity activity interspersed by short periods of low-intensity activity (12). This requires players to have highly developed speed and agility, muscular strength and power, and aerobic capacity (10,11). Anecdotally, these players experience a large number of calf muscle cramps, most frequently observed at the end of a game. To date there have been no identified studies examining the predictors of calf cramping in rugby league players.
Cramps of the triceps surae, or more commonly referred to as calf cramps, that occur during game play are known in sports medicine literature as exercise-associated muscle cramps (EAMC) (15,16,23,24,27,28,31). Exercise-associated muscle cramps are defined as “painful spasmodic involuntary contractions of skeletal muscle that occur during or immediately after muscular exercise” (26). Though it is possible for athletes to suffer from idiopathic and paraphysiological calf cramps such as occasional cramps, familial or idiopathic nocturnal cramps (21), this study is focused solely on EAMC. Historically, the etiology of EAMC has been hypothesized to be dehydration and/or serum electrolyte concentration abnormalities (23,26). However, 2 recent cohort studies on marathon runners and triathletes found no relationship between EAMC and dehydration or serum electrolyte concentration changes (28,31). Another theory proposes that EAMC are caused by altered neuromuscular control through muscular fatigue (27). This is based on animal experimentation and electromyographic data and is supported by the large number of EAMC that occur in muscles involved in repetitive contractions (26). Furthermore, an association between EAMC and fatigue would be consistent with EAMC occurring in the final minutes of a rugby league game.
Prevention of EAMC is desirable. A common strategy for developing preventative measures is to compare the characteristics of EAMC-prone players and EAMC-resistant players with a view to identifying potential risk factors for EAMC. To date there are no published investigations in at-risk team sport populations such as rugby league players. In endurance athletes demographic and anthropometric data, and a history of EAMC, are reported in the literature as predictors of EAMC. However, the strength of this evidence is varied (23–25,27,30). Furthermore, the demands placed on endurance athletes are largely different to those on rugby league players due to the intermittent nature of this sport. Therefore, potential contributors to EAMC in rugby league players may be different and need to be explored. For example, muscle flexibility (25), age (25,28,31), and the time point during an event (typically the latter part) (25) have been shown to have a weak relationship with EAMC in an endurance population, but there are currently no published studies on team sport populations. Furthermore, it is premature to dismiss other possible predictors of EAMC in rugby league that have not yet been previously investigated. These include ethnicity, playing position, foot posture and strike, calf girth, and number of games played in a season.
The primary aim of this study was to undertake an initial exploratory prospective investigation to identify predictors of calf cramping in rugby league players. The secondary aims were to compare possible predictors of EAMC between calf cramping and non–calf cramping players of all competition levels in a single professional rugby league club and to investigate the relationship between hydration measures and incidence of calf cramping.
Experimental Approach to the Problem
This was a prospective study consisting of extensive preseason screening followed by season long (juniors February to April and seniors March to September) game day assessments and monitoring of EAMC. A review of the literature and discussions with medical staff led to the development of the following list of potential EAMC predictors: competition level, age (30), ethnicity, playing position, history of cramping (25), precramping (27), low back pain, orthotic usage, foot posture, foot strike, muscle flexibility (26), calf girth, hydration status (16), and number of games played. Logistic regression was used to determine which factors were associated with developing EAMC.
A convenient sample of male rugby league players (n = 117) from a single club in NSW, Australia, were recruited at the start of 2010 preseason training. One hundred and three players, ranging in age from 15 to 34 years (mean age: 18.8 ± 4.1 years) were included in the analysis after exclusions. Players were excluded if they did not play in any regular season games (13 players) or joined the club after preseason screening was completed (1 player). Players competed at elite levels in teams that were determined first by their age on January 1, 2010, and second by their performance and ability. The teams were defined as younger than 16 years (U16), younger than 18 years (U18), younger than 20 years (U20), and open age full-time professionals (National Rugby League [NRL]). For the current study, players were categorized as either junior (n = 44; mean age: 15.8 ± 0.9 years) or senior (n = 59; 21.1 ± 4.1) by the highest competition level they played. The junior category consisted of U16 and U18 teams, and the senior category consisted of U20 and NRL teams. This study was approved by the University of Newcastle Human Research Ethics Committee, and all participants provided written informed consent, including parent/guardian consent for adolescents younger than 16 years.
Preseason Data Collection
Players completed an electronic questionnaire in the presence of an assessor, which included demographics (age, rugby league age, training age, ethnicity, and playing position), injury history (history of cramping, precramping, and low back pain), and orthotic usage. The questionnaire was piloted the previous season in players from the same rugby league club and subsequently refined. Age was a player's age on January 1, 2010. Rugby league age was a player's age when they first played rugby league in any competition. Training age was a player's age when they first played in a team with both a coach and a strength and conditioning coach. Ethnicity was categorized by both the player's and their parent's country of birth, with the questionnaire format allowing more than 1 category to be chosen. The following categories were used, as defined by the Australian Bureau of Statistics 2006 classifications (1): white, Mediterranean, European, Polynesian, Aboriginal/Torres Strait Islander, and Maori. Playing position was defined as the player's positional category that they played most often. Categories were adapted from Gabbett as follows (11): front row, back row, outside back, and half/hooker, plus utility for players who played in more than 1 of these categories. Injury history was restricted to the previous season to reduce recall bias. History of cramping was defined as having experienced at least 1 incidence of calf cramping and if a player answered yes, they were then asked the frequency of incidence during the season. History of precramping was having experienced at least 1 incidence of “cramp-prone state” in the calf (27). “Cramp-prone state” was defined as heavy tightness felt before cramping that does not result in muscle spasm (27). If a player answered yes to “cramp-prone state,” they were then asked the frequency of incidence during the season. For history of low back pain, players were asked if they had experienced low back pain and/or injury. If the player answered yes, they were then asked whether it resulted in missing a training session and/or game, known as “missed field minutes.” For orthotic usage, players were asked whether they wore any type of foot orthotic, and if so, whether or not they were worn in normal shoes, training boots and playing boots.
Preseason screening included foot posture, foot strike while sprinting, muscle flexibility, and calf girth measurements. Foot posture was measured using the Foot Posture Index 6 (FPI-6) by 1 practiced assessor as per the FPI-6 guidelines (6,22). Barefoot players marched on the spot of a level surface for 10 seconds before settling into a normal double limb stance position. The assessor assigned scores for each foot on 6 clinical criteria using a 5-point Likert scale as follows: neutral postures scored zero, supinated postures were assigned a negative value of either −1 or −2, and pronated postures were assigned a score of 1 or 2 (22). The scores on the 6 clinical tests were then summed to create the aggregate FPI-6 score for each foot between a minimum of −12 (extremely supinated) and a maximum of +12 (extremely pronated). The single foot aggregate FPI-6 furthest from zero was used for statistical analyses as it has been suggested that the most extreme measures will have the most functional impact, (32) and selecting a single limb for analysis is statistically more robust (18).
A video camera (Flip UltraHD FVU32120B, 1280 × 720 resolution, 50 frames per second) was used to record foot strike during a timed maximal 40-m sprint in football boots. The camera was placed perpendicular to the player's line of progression at the 20-m line. The foot closest to the camera was categorized for each player as it was best visualized, and foot strike is usually the same for both feet (7). Two assessors analyzed each video independently, with any discrepancy resulting in further review of the video footage and discussion until an agreed category was reached. Players were categorized as “Toe,” “Mid,” or “Heel” strikers by the area of the foot that first touched the ground. “Toe” was the area distal to the metatarsal heads, “Mid” was the area between the calcaneous and metatarsal heads, and “Heel” was the calcaneous.
Muscle flexibility was measured by individual assessors to remove interrater measurement differences. One assessor measured gastrocnemius, the second assessor measured hamstring and iliopsoas. Goniometer placement for all measurements followed guidelines as stated by Clarkson (5). For gastrocnemius, players lay prone on a plinth with their feet relaxed over the edge. The assessor applied pressure with their thigh through the ball of the player's foot until they first felt resistance to the passive stretch of gastrocnemius. Gastrocnemius was measured with zero being plantargrade. Positive values were taken in dorsiflexion with the lowest value (tightest gastrocnemius, right or left side) being used for statistical analysis (18,32). Iliopsoas and hamstrings were measured using a standardized frame holding players in a modified Thomas Test position (Figure 1). With hips at the edge of the plinth, the frame stabilized the top leg in 90° angle hip flexion. The bottom leg hung relaxed over the edge of the plinth with a normal curve of the lumbar spine maintained. Hamstrings were measured using the top leg through active knee extension. Terminal knee extension was equal to 180° angle with values less than that taken in knee flexion. The lowest value (tightest hamstring, right or left side) was used for statistical analysis (18,32). Iliopsoas was measured using the bottom leg with zero being in line with the plinth, and positive values taken as the relaxed thigh hung below the plinth. The lowest value (tightest illiopsoas, right or left side) was used for statistical analysis (18,32). The reliability of muscle flexibility measurement was investigated in a prior study and found to be excellent (intra-class correlation coefficient ≥ 0.84, 95% confidence interval, 0.67–0.92) (9,19).
Calf girth was measured with players seated in 90° angle knee flexion with bare feet on the ground. Tape measurement placement was at the largest circumference of the calf. The larger of the 2 calves was used for statistical analyses (18,32). Player's height was measured using a stadiometer with the player barefoot in double limb stance on a flat, even surface. Calf girth was normalized to a player's height using the following formula: calf girth/height × 100 (28,31).
Game Day Data Collection
Hydration status was recorded at each game and measured in 2 ways as follows: urinary specific gravity (USG) and percent weight loss during the game. Player's urine was measured by the same member of staff at each game before competition using a urine refractometer (General Tools & Instruments Co LLC, New York, NY, USA, manufacturer number REF312ATC) with automatic temperature compensation to the nearest microgram (μg). To measure change in dehydration status during the game, players weighed themselves in football shorts ∼30 minutes before the game (i.e., before warm-up) and shortly after the game on Wedderburn TIBWB800P personal scales with 200 kg capacity to the nearest 100 g. Percent weight loss was calculated using the following formula: (pregame weight − postgame weight)/pregame weight × 100 (28,31). To capture incidence of calf cramping and precramping (i.e., cramp-prone state), players completed a questionnaire after each game (in the presence of an assessor) recording if they played and, if so, whether or not they experienced calf cramps during the game. The assessor was always a member of the medical staff (physiotherapist or trainer) who was present during the game and able to answer any player's questions about defining or identifying their cramp or cramp-prone state.
Players were categorized as either EAMC (experienced at least 1 incidence of calf cramps in the season) or no EAMC (no calf cramps). As this was an exploratory study including multiple independent variables, sample size calculations were based on the variable (history of calf cramping) most likely to show a difference between groups (EAMC and no EAMC) based on previous studies of other lower limb injuries (8,13). The sample size recruited (n = 103) was adequate for detecting a difference between groups in the proportion of players with a history of calf cramping at the alpha level of 0.05 with 90% power. Descriptive statistics were calculated for each variable for EAMC and no EAMC players with differences between the groups determined using independent t-tests for continuous and χ2 for categorical variables. Data were examined for normality, with nonparametric statistics reported where appropriate. Potential predictors of EAMC were determined using logistic regression. The dependent variable was experiencing EAMC at least once during the 2010 season. The following possible independent variables (predictors) were examined: competition level, age, rugby league age, training age, ethnicity, playing position, history of cramping, history of cramping frequency, history of “cramp-prone state,” history of “cramp-prone state” frequency, history of low back pain, history of low back pain resulting in missed field minutes, orthotic usage in any shoe type, foot posture, muscle flexibility (gastrocnemius, hamstring and iliopsoas), and number of games played. Due to the large number of possible predictors, univariate models were generated for each variable before the multivariate modeling. Those variables with p < 0.25 in the univariate models were subsequently included in a multivariate model (20) analyzed with the backwards (Wald) method. The Alpha level for significance was set at p <0.05.
As data for foot strike and calf girth were only available for senior players, and data for hydration status were only available for junior players, separate modeling using 2 subsets of data were performed. Subset 1 consisted of senior players only and replicated the multivariate modeling method described above with the inclusion of the additional variables of calf girth and foot strike. Subset 2 consisted of data from junior players only and investigated the relationship between hydration measures (USG and percent weight loss) and the incidence of cramping. For the regression model for subset 2, the dependent variable was the incidence of cramping, defined by whether or not a cramp occurred for each player on each game day. Independent variables were USG and percent weight loss. All statistical analyzes were performed with PASW 18.0 (SPSS, Inc., Chicago, IL, USA).
Fifty-two players experienced at least 1 incidence of calf cramping throughout the 2010 season; 77% of those were in the senior competition level (Figure 2). Of the players categorized in the EAMC group, 42% experienced only 1 incidence of cramping, whereas 21% were classified as chronic crampers suffering from ≥4 incidences of cramping (Figure 3).
Descriptive data for EAMC and no EAMC groups of players are listed in Tables 1–3. Significant differences between EAMC and no EAMC groups were observed for age and competition level, number of games played, cramping history and frequency, and experience of low back pain. Although not significant, Polynesian and Maori players were overrepresented in the EAMC group. Due to the constraints of working with elite athletes, there were varying levels of missing data. From the primary model, there were 4 missing questionnaires, 13 missing muscle flexibility measurements, and 1 missing FPI score; from subset 1, there were 23 foot strike and 13 calf girth scores missing; in contrast, from subset 2 there were no missing data. Players with missing data were omitted from individual analyses, where the data item was used. The primary regression model identified playing in a senior competition level, a previous history of cramping, and a previous history of low back pain resulting in missed field minutes, as predictors for experiencing EAMC at least once during the season (Table 4).
In subset 1 (seniors only), the additional variables of foot strike and calf girth were not predictors of experiencing EAMC in the logistic regression modeling, and they were not significantly different between the groups. In the EAMC group (n = 24; 67% of senior players), there were 4 heel strikers, 15 midfoot strikers, and 5 toe strikers compared with 1, 9, and 2, respectively, in the non-EAMC group (n = 12). Calf girth as a percent of height was a median of 22.6% for EAMC players (interquartile range [IQR]: 21.7–24.1) and 22.3% for no EAMC players (IQR, 21.4–22.9). In subset 2 (juniors only; 27.3% experiencing EAMC), USG and percent weight loss were not predictors of the incidence of cramping. There was no difference in USG when EAMC occurred (median: 6.0 μg; IQR: 4.5–8.0) compared with when EAMC did not occur (median: 10.0 μg; IQR: 5.0–15.0) and similarly in percent weight loss when EAMC occurred (median: 2.3%; IQR: 1.6–2.7) or did not occur (median: 1.8%; IQR: 1.1–2.4).
The current study suggests that there is a high incidence of calf cramps occurring in rugby league with 50% of the players experiencing EAMC during 1 playing season. Three following possible predictors were found to have a positive relationship with calf cramping: playing in a senior competition level, having a prior history of calf cramping, and having a prior history of low back pain resulting in missed field minutes. Hydration status, muscle flexibility, and player demographics were not associated with calf cramping. This casts some doubt on common theories and beliefs about the causes of EAMC such as dehydration. In contrast, low back pain resulting in missed field minutes, a factor not identified in previous literature, may provide new opportunities to develop preventative strategies. The specific mechanisms by which these predictors increase calf cramp risk remain to be elucidated.
Fifty percent of players experienced at least 1 incidence of calf cramping throughout the season. The majority occurred in players at a senior competition level, with 74% of the club's NRL team (full-time professionals) experiencing calf cramps at least once during the season (Figure 2). The high frequency of calf cramping in this population indicates that this is a substantial issue in rugby league, and factors leading to calf cramping should be clearly identified to develop preventative strategies. Although nearly half of the EAMC group suffered from only 1 incidence of calf cramping in the 2010 season, 21% of players who experienced calf cramps (n = 11) suffered from 4 or more incidences (Figure 3). This suggests that although calf cramping occurs across a range of rugby league players, there is a small group of players who can be classified as chronic crampers. It is suggested that future research targets this population, especially players who cramped in 8 of a possible 24 games, as predictors of EAMC for this high-risk subgroup may be different to those in the remaining rugby league population.
Playing at a senior competition level was found to be a predictor of calf cramping. No previous studies were identified investigating competition level as an EAMC predictor, however, 3 hypotheses are proposed. First, senior games are played in 40-minute halves, whereas juniors play either 30-minute or 35-minute halves. Schwellnus et al. (23) propose that there is a positive relationship between increased exercise duration and the development of EAMC. The extra 10 minutes played by senior players may increase their potential to calf cramp. This theory is also supported by observations made by rugby league medical staff that calf cramping often occurs in the last 10 minutes of a game. Second, the junior competition season is 9 rounds (weeks of play), whereas the senior competitions are played for 26 rounds (usually containing 2 byes). The current study found that as the number of games increased, there was a slightly higher risk (p = 0.051) of a player being in the EAMC group after accounting for other factors. This suggests that the risk of developing calf cramps increases with the number of games played during a season. Third, the mean age of the 2 competition levels is different, with juniors on average being 6 years younger than seniors. Previous studies support a positive association between increasing age and the development of EAMC (23,30).
In the current study, a history of calf cramping in the previous season was shown to be a strong predictor of EAMC. Two recent studies in marathon runners support this conclusion (25,28). Marathon runners with a history of EAMC in the previous year were more likely to cramp during a race than marathon runners without this history (25,28). Cramping is often preceded by a “cramp-prone state,” where there is noticeable twitching of the muscle (27). In the current study a history of experiencing a “cramp-prone state” (27) in the previous season was a poor predictor of calf cramping in rugby league players. Importantly, the definition of “cramp-prone state” is ambiguous and potentially affected by the player's interpretation of the definition. For players to understand the definition given, they need to have previously experienced EAMC to understand the sensation of heavy tightness described in “cramp-prone state.” As it is a potentially unreliable measure, it is recommended that for future research the term be more clearly defined and explained to participating players or otherwise excluded.
Calf cramping players were often observed by medical staff to have low back pain. This is supported by the current study with the relationship found between calf cramping and a history of low back pain resulting in missed field minutes in the previous season. It is important to note that low back pain not resulting in missed field minutes had no relationship with calf cramping. However, this may have been related to recall bias in players' reporting, as players are more likely to recall low back pain resulting in missed field minutes than pain that does not. One possible theory for this relationship is that low back pain results in altered neural transmission in the nerves supplying the lower limb resulting in calf cramps. As potential structural sources of low back pain were not identified in the current study, reasons for the link between low back pain and calf cramping cannot be determined. However, this novel finding should be further explored in future research.
Although it has been suggested that foot biomechanical issues such as pronation may be associated with calf cramping (14,29), the current study found no association between FPI-6 score and calf cramping. This may have been a result of the scoring criteria used to classify pronation within the FPI-6. As the FPI-6 scoring guidelines are designed for a population that includes neurological conditions (17), the FPI-6 classifications may lack sensitivity for detecting differences in an athletic population. However, different classifications or “cut-offs” for defining a pronated foot posture with the FPI-6 in athletic populations have yet to be established. The FPI-6 has been used previously in 2 studies on athletic populations (3,4). In both of these studies, the aggregate FPI-6 score used was based on statistical definitions of “normal, pronated, and supinated” calculated from data collected from their study populations, whereas the current study strictly adhered to the FPI-6 guidelines for scoring classification. The FPI-6 is a useful clinical screening tool that has been validated against more sophisticated methods such as pedograph analysis and electromagnetic motion tracking (22). Foot Posture Index 6 scoring methods for athletes, and other methods of measuring foot posture, should be explored before foot posture is ruled out as a possible predictor of calf cramping.
The other aspect of the foot measured in this study was a player's foot strike while sprinting. Although in the current study no relationship was found between foot strike and calf cramping, players foot strike patterns should be noted. The foot strike patterns of a large number of players in this study would not be considered efficient for a sport that demands near maximum velocity sprinting (11,12). Of the 36 senior players with foot strike measurements obtained, 67% were midfoot strikers and 15% were heel strikers when sprinting. The increased stress placed on the foot through these nonoptimal techniques for speed and agility may lead to earlier muscular fatigue and calf cramping (2,16,26). In a larger population, it might be possible to demonstrate an association between these nonoptimal running techniques and calf cramping.
Despite evidence suggesting decreased muscle flexibility as a possible predictor of EAMC (23,26), the current study found no relationship between calf cramping and muscle flexibility of the gastrocnemius, hamstring, or hip flexors in rugby league players. There was also no relationship found between calf cramping and calf girth in rugby league players. Muscle flexibility may not have differed sufficiently among the players in this study to result in a difference between EAMC and non-EAMC players because they spent similar time each week stretching as part of their standardized training protocol. Similarly, the standardized conditioning regimes in senior players resulted in similar anthropometric measures and minimal differences in calf girth between EAMC players (median girth as a percentage of height 22.6%) and no EAMC players (22.3%). Therefore, the standardized training protocols in senior players may have contributed to the lack of relationship between calf girth and calf cramping, and this relationship was only examined in senior players.
In the current study, hydration status was not related to calf cramping in junior rugby league players. This finding is consistent with 2 previous studies in triathletes and marathon runners that found EAMC were not associated with a greater fluid associated body mass loss (28,31). The findings in the current study also suggest that hydration status has little or no influence on EAMC incidence. However, as the study investigated hydration status only in junior players (n = 44), and the incidence of calf cramping is relatively low in this group (n = 12), this limited the ability to detect a possible relationship. As the relationship between hydration status and EAMC is a strongly held belief (23,24), hydration status should be investigated further in players at a senior competition level where the incidence of calf cramping is greater (up to 3 times greater in the current study).
The main limitation of this study is the sample size and its power to detect predictors of calf cramping from among the many possible factors. There is limited research on EAMC in any athletic populations and no previous research was indentified on EAMC in the rugby league population. As there has been such little prospective research to either support or refute relationships between various factors and risk of calf cramping, it was important to include all possible proposed predictors of calf cramping in this exploratory study, even those with little supporting evidence (23,24,27,30). The sample size required to adequately test all possible predictors would be much larger than was feasible in the current study, though differences between EAMC and no EAMC groups were detected with adequate power for some variables. The current study restricted data collection to a single rugby league club because professional clubs are reluctant to participate where there is a possibility of data from their players being compared with those of other teams, even informally. In future research, sample size could be increased by collecting data on calf cramping over several seasons within a single club, with additional players added in subsequent years. One advantage of using a single club was that this facilitated consistency and reliability in the data collection methods. Last, missing data were another limitation of this study with constraints on both preseason data collection days and game days. On preseason data collection days, some players were not in attendance due to other commitments.
Another limitation of this study is the use of a single anatomical side (left or right) for statistical analysis when data are paired, such as foot posture, foot strike, muscle flexibility, and calf girth. Sutton et al. (32) suggests that 1 side, usually the worst side, be chosen to address paired data analysis as it has the most functional impact on the subject being analyzed. However there is a likelihood that by using this approach important unilateral factors may be missed as not all the side-specific data are used (18,32). The “worst side” was chosen for all paired data analysis in this study, as this is more likely to have the most functional impact on the player (18,32).
As the incidence of calf cramping was much greater in the senior competition levels of rugby league, it is suggested that future research focuses on this group to better identify the predictors of calf cramping. Furthermore, as this is the first study to show a possible relationship between low back pain and EAMC in rugby league, further research is needed to substantiate and clarify this relationship, such as identifying specific painful structures and the frequency of low back pain and their relationship to EAMC. Experimental studies should also be designed to determine whether particular interventions for low back pain could reduce a player's risk of calf cramping. Additionally, the following possible predictors should be further investigated as there remains the possibility that they might contribute to the development of calf cramps if a different population was studied: ethnicity, playing position, orthotic usage, foot posture and strike, muscle flexibility, and calf girth. Last, all possible predictors should be explored in a population that experiences repeated cramps as there may be factors specific to this population that contribute to their recurring incidences of calf cramps (Figure 3).
In conclusion, there are large numbers of rugby league players experiencing at least 1 incidence of calf cramps during a rugby league season. The results of this initial exploratory prospective investigation suggest that playing in a senior competition level, a history of calf cramps in the previous season, and a history of low back pain resulting in missed field minutes in the previous season, are predictors of experiencing calf cramps in rugby league players.
The results of this initial exploratory prospective investigation show that a large number of rugby league players experience calf cramps. Playing in a senior competition level, a history of calf cramps in the previous season and a history of low back pain resulting in missed field minutes in the previous season significantly increase the risk of experiencing calf cramps. It is recommended that preseason screening identify senior rugby league players with a history of calf cramps or low back pain and explore interventions that have been proposed to reduce calf cramps, such as reducing training intensity or improving conditioning and range of motion. (2) Through early identification, players may be treated to potentially reduce their risk of developing calf cramps.
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Keywords:Copyright © 2014 by the National Strength & Conditioning Association.
athletic injuries; muscle cramp; exercise-associated muscle cramps; risk factors; sports or sports medicine; triceps surae