Australian Rules football (ARF) is a physically demanding game, which can result in signs of fatigue for up to 3 days postmatch (2). To some extent, postmatch fatigue may be related to muscle fiber damage as indicated by elevated plasma creatine kinase (CK). This marker has been shown to be significantly elevated after a rugby game, and without specialized interventions (e.g., water therapy), CK remained partially elevated after 3.5 days (5). Muscle damage, as a result of playing field sports such as ARF, is likely to be caused by running, body contact (13), and eccentric muscle activity when stopping from sprints and landing from jumps (10) and has been associated with performance attenuation. For example, muscle damage induced by 10 sets of 10 repetitions of vertical jumps was associated with reduced multiple 10-m sprint performance 1–2 days postexercise (14). The presence of muscle damage after exercise may potentially impair subsequent training and competition performances.
In addition to attenuating subsequent performance, muscle damage may elevate the risk of injury. Lazarim et al. (9) suggested that playing soccer matches with extremely high levels of CK could increase the risk of injury during competition. Further, Brockett et al. (1) suggested that muscle damage consisting of microtears that are induced by eccentric exercises can increase the susceptibility of the muscle to a more serious tear. As injury prevention and performance level are major concerns at all levels of sport, postexercise muscle damage deserves consideration when constructing training and competition schedules.
The demands of ARF have been quantified by video analysis of games (4) and more recently by global positioning system (GPS) tracking (15). The use of GPS and associated software has allowed coaches to quantify player movements using several variables, which can be reported in real time or shortly after competition. It is possible that GPS measures that describe movement demands are associated with the level of muscle damage elicited via match play. It is presently unknown as to which, if any, variables may be related to muscle damage as measured by plasma CK. Therefore, the purpose of this research was to determine if there was an association between GPS variables describing movement demands of an elite junior ARF game and postmatch CK levels. It was hypothesized that variables that reflect eccentric muscle activity would be more strongly associated with higher, as compared with lower, CK levels.
Experimental Approach to the Problem
Global positioning systems were used to collect data related to the movement demands of elite junior ARF match play. Creatine kinase levels were determined 24 hours postmatch as an indicator of relative muscle damage. Participants were median split into high and low CK groups to examine the association between match movement demands and muscle damage. Elucidation of the various relationships between movement demands and muscle damage will provide an insight into efficacious recovery strategies.
Fifteen male elite junior ARF players aged 16–18 years who were representing their state in the National under-18 football championships volunteered to participate in the study. The subjects were in-season and had experience with basic resistance training. The study was approved by the University Human Ethics Committee Review. Before the investigation, all the subjects were briefed on data collection protocols, experimental risks, equipment, and the nature of the study before signing an informed consent document.
The ARF match was completed in the afternoon in mild to warm conditions. Meals before the match and 24 hours postmatch were self-selected. The players were provided with unlimited water before, during, and after playing to maintain a hydrated status.
As has previously been suggested that CK may be at or near peak levels 24 hours postmatch (13,14), samples were taken at this time. A pinprick on the finger allowed 28.5 μl of capillary whole blood to be drawn, which was placed on a measurement strip and analyzed by means of a Reflotron (Roch Diagnostics, Grezacherstrasse, Switzerland). It was assumed that the CK analyzed emanated from muscle damage rather than from cardiac or brain damage. The Reflotron was calibrated according to the recommendations of the manufacturer, and analysis took place in a controlled laboratory environment at 25°C.
The participating players wore a Minimax GPS unit (Catapult Innovations, Melbourne, Australia) operating at 5 Hz. The validity of this device has been previously determined (7). The unit was secured in a pouch in a harness and was placed on the upper back of the player. Shortly after the game, GPS files were downloaded to a computer and analyzed with the software provided by the manufacturer (Logan Plus Version 4.2.3, Melbourne, Australia). The distances covered in meters for the following speed zones were recorded: 0.1–1.9 m·s−1 (walking), 2.0–3.9 m·s−1 (jogging), 4.0–5.9 m·s−1 (running), 6–7.0 m·s−1 (fast running), and >7.0 m·s−1 (sprinting). The distance traveled accelerating or decelerating was also recorded for high acceleration (3–15 m·s−2), moderate acceleration (1–3 m·s−2), low acceleration/deceleration (−1 to 1 m·s−2), moderate deceleration (−1 to −3 m·s−2), and high deceleration (−3 to −15 m·s−2). Because there was no precedence for determining the thresholds for accelerations zones, we conducted pilot testing with 1 player who was required to perform maximum accelerations and decelerations from 10-m sprints. Although the analysis was subjective in nature, it provided some indication of acceleration/deceleration values expected from maximum efforts.
A unique variable generated by the GPS software is “player load,” which is obtained by recordings from the in-built accelerometer in the GPS unit. This is a measure of the accumulated load based on combined 3-D acceleration and deceleration measurements sampled at 100 Hz. According to the manufacturer (Catapult Innovations), player load is calculated from the instantaneous rate of change of acceleration and deceleration in the forward, upward, and sideward directions. That is, it measures all accelerations and decelerations in all directions. The potential advantage of this metric is that it accumulates from nonrunning activities such as kicking and jumping and impacts in tackles and collisions that occur throughout an ARF game. Because acceleration is proportional to force, player load may provide a useful measure of the total load applied to a player in a match.
Inspection of the individual CK data revealed an outlier that was 23% greater than the next highest score and 83% greater than the group mean. This score was observed in a ruckman whose role was to be involved in stoppages and use his body to give advantage to his team in contests. Because this specialized playing role involving a high level of body contact was not typical of the average player, we chose to omit this participant from further analysis. To determine if there was an association between CK production and any of the variables describing movement demands of the game, we chose to median split the players into 2 groups. This produced a high CK group (n = 7) and a low CK group (n = 7). A t-test for independent samples confirmed that the groups were significantly different in CK (p < 0.001, 119%, effect size = 3.23).
Independent t-tests were also performed to determine if there were any statistically significant differences in GPS variables between the groups. The magnitude of the differences in group means were described with effect sizes (ES) using Hopkins (6) thresholds: trivial, <0.19; small, 0.20–0.59; moderate, 0.60–1.19; large, 1.20–1.99; and very large, 2.0–4.0. Pearson (r) correlation coefficients were determined to investigate the group-specific relationships between CK and the GPS variables. Magnitudes of effect of the correlations were determined as follows: trivial <0.10; small ≤0.10–0.29; moderate 0.30–0.49; large 0.50–0.69; very large 0.70–0.89; and nearly perfect 0.90–0.99 (6). All statistical analyses were performed using Statistical Package for Social Sciences (Version 17), and significance was set at p ≤ 0.05.
The mean ± SD results for the high and low CK groups are presented in Table 1. There are a number of variables in which the high CK group produced significantly greater scores than did the low CK group (p < 0.05), with the single biggest difference being the distance covered during fast running (80%, p = 0.004, ES = 1.98). Correlations between CK levels and GPS variables specific to group are presented in Table 2. Many of the correlations elicited in the high CK group are in the opposite direction as compared with those elicited in the low CK group. Among the group-specific relationships exhibiting the greatest differences are those between CK and running, sprinting, moderate and high acceleration, and high deceleration.
The high CK group achieved greater scores on all GPS variables describing ARF game movements. This suggests that greater distances covered at various speeds and accelerations and decelerations are associated with greater muscle damage. The high CK group covered a 29% greater mean total distance than did the low CK group (p < 0.05). Although a number of factors likely contribute to muscle damage, including walking and jogging, the results of this study suggest that relatively high-intensity running and acceleration and deceleration across intensities are relatively large contributors.
Although total distance is one measure of movement demands in matches, important findings from this study are concerned with the particular variables that best distinguish the high and low CK groups. It is interesting that the distances covered at walking and jogging are only moderately greater (not significant) for the high CK group and are accompanied by group-specific correlation coefficients for which the directions and magnitudes suggest little association (i.e., greater distance covered is not associated with elevated CK release) between either measures and CK levels in both groups. In contrast, there are large statistically significant differences (accompanied by large effect sizes) between the groups for the distances covered at running (4–6 m·s−1) and fast running (6–7 m·s−1) speeds (Table 1). The greatest difference between the groups was found for the distance covered between 6 and 7 m·s−1 (fast running), which was 80% (ES = 1.98, p < 0.05). Further supporting the notion that high-intensity running is more strongly associated with CK release are the magnitudes and directions of the correlations presented in Table 2. Specifically, the low CK group, which performed less of these types of movements (running, fast running, and sprinting), presented small negative correlations, indicating a negative, if any, relationship. In fact, the direction and magnitude of the correlations observed for the low CK group suggest little association between any of the GPS variables and CK levels. It may be that the volume achieved in any of the measures was insufficient to have significant impact on CK release. Conversely, the high CK group presented positive coefficients ranging from small to large values in magnitude. These results suggest that high-, as compared with low-, intensity running is more strongly associated with CK release and that certain volumes of such running are necessary to elevate CK levels.
A higher level of muscle damage may be caused by the combination of volume and intensity of running. For example, jogging was performed with a relatively high volume in both groups, but the intensity of muscle contractions would have been low (8). Given the relatively high volumes, the intensity of the contraction (i.e., low) may help explain the strength and direction of the relationships between variables such as walking, jogging, low acceleration and deceleration, and total distance and CK level. Sprinting involves very high-intensity muscle contractions and ground reaction forces (8) that likely contribute to muscle damage, but the volume of sprinting was quite low (165 m for the high CK group), which may explain the lack of significant difference between groups. However, the direction and strength (positive and moderate) of the correlation coefficient between sprinting and CK observed under the high, as compared with that under the low (negative and small) CK group suggests some association between sprinting and CK levels, given a certain volume of sprinting is achieved. The combination of moderate volume and relatively high-intensity contractions associated with relatively high-intensity running (4–7 m·s−1) may produce more total muscle damage.
Previous research using GPS tracking of AFL games (15) has used a 1-Hz sampling rate, which may be of limited value when attempting to track rapid changes of velocity (accelerations and decelerations) (3). Because we were able to sample player position at 5 Hz, new insights into movement demands are provided. The distances covered performing moderate acceleration and deceleration and high deceleration were significantly greater for the high CK group (Table 1). Further, the 2 relationships exhibiting the greatest differences among groups are those between high acceleration and deceleration and CK levels. Specifically, the group performing greater volumes of these movements (high CK) present very large and moderate positive correlations for high acceleration and deceleration, respectively. Conversely, the group performing lesser volumes (low CK) presents small and moderate negative correlations for high acceleration and deceleration, respectively. Moderate- to high-intensity acceleration and deceleration are likely linked to muscle damage. It is possible that the significantly greater distance covered performing high deceleration running, as compared with high acceleration running, which was not different between groups, may have more greatly influenced CK release. Although the players covered <200 m on average performing high deceleration, this type of running involves high-intensity eccentric contractions of various muscle groups such as the quadriceps. Eccentric muscle activity is known to induce muscle damage, as measured by CK (11,12). The fact that all 3 deceleration measures were significantly greater under the high CK group, as compared with those under the low CK group, supports the hypothesis that eccentric muscle activity is more strongly associated with high CK levels.
Player load was significantly greater for the high, as compared with low, CK group but was weakly correlated with CK levels in either group. However, when data are pooled, the correlation between player load and CK level is of a large magnitude. The player load variable was designed in an attempt to monitor “impacts,” which in ARF would include not only impacts because of running foot strikes but also impacts because of body contact with other players (e.g., tackles). In rugby union, a very high correlation of r = 0.92 was reported for the number of tackles in a game and CK level (13), suggesting that body contact was the predominant determinant of muscle damage. In ARF, in which there is arguably less body contact but more running, it is likely that the primary cause of muscle damage is high-intensity running, high acceleration and deceleration running, and running with changes of direction. Body contact is likely of secondary influence. However, the contribution of various game activities to muscle damage is likely to be quite variable between individuals, positions, and games.
Of interest in this study was whether the volume of certain GPS variables is associated with CK levels and, thus, indirectly muscle damage. Data have not been normalized to whole-game playing time or partial (e.g., game quarter) playing time because match volume, rather than density (volume/time) was investigated. Also, prematch CK levels were not determined, and therefore, a comment on the extent of muscle damage is impossible to make. Further, the correlations presented were determined using very small sample sizes and should be viewed with caution and, by nature, they indicate an association only, rather than cause and effect. Nonetheless, the results of this preliminary investigation suggest that GPS variables describing player movements in ARF games are associated with postmatch muscle damage. In particular, the distance covered during running between 4 and 7 m·s−1, moderate acceleration, and moderate to high deceleration are variables best able to distinguish between players who produced relatively high CK from those who produced lower CK levels. It may be that certain levels of volume for specific movement variables are necessary to influence CK levels. The results of this study suggest that postmatch GPS reporting may be used to indicate the likely muscle damage 24 hours after an ARF game.
The use of GPS to predict muscle damage could be of use to coaches and practitioners in prescribing recovery practices. Based on GPS data, more individualized strategies could be devised and could potentially result in better subsequent performance and the prevention of injury. For example, one player covered 3,565 m of running between 4 and 7 m·s−1; 1,036 m of moderate-high deceleration running; achieved a player load value of 1,556; and produced a CK score of 487 U·L−1. With respect to the same measures, a second player achieved values of 1,908 m, 506 m, 657 U·L−1, and 125 U·L−1, respectively. For the first player, more aggressive recovery strategies targeting muscle damage and adjustment of training loads may be required to accelerate recovery and optimize player performance for future games. Coaches able to exploit information elucidating muscle damage will be able to achieve a competitive advantage. Recovery protocols that are most effective for this purpose should be the topic of future research. The player load variable may be a potentially useful indicator of muscle damage because of a combination of running and other impact events. Before endorsement of this measure, further research is needed to determine its validity and reliability.
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Keywords:Copyright © 2012 by the National Strength & Conditioning Association.
global positioning system; GPS; creatine kinase; body contact; acceleration; deceleration