POWER, FATIGUE, AND RECOVERY CHANGES IN NATIONAL COLLEGIATE ATHLETIC ASSOCIATION DIVISION I HOCKEY PLAYERS ACROSS A COMPETITIVE SEASON C. MATTHEW LAURENT,1 ADAM M. FULLENKAMP,1 AMY L. MORGAN,1
AND
DANIEL A. FISCHER2
1
Exercise Science Program, Bowling Green State University, Bowling Green, Ohio; and 2Department of Athletics, Bowling Green State University, Bowling Green, Ohio ABSTRACT
Laurent, CM, Fullenkamp, AM, Morgan, AL, and Fischer, DA. Power, fatigue, and recovery changes in National Collegiate Athletic Association Division I hockey players across a competitive season. J Strength Cond Res 28(12): 3338–3345, 2014—This study aimed to evaluate changes in pre- to postseason power output, fatigue, and recovery during a repeated sprint test. Twenty National Collegiate Athletic Association Division I men’s hockey athletes performed identical sessions of repeated sprint work pre- and postseason. The repeated sprint test consisted of 5 sets of 45 seconds of repeated sprint work with 90 seconds of rest in between each series of sprints. Power output (W), decrement, and recovery scores (RECs) were determined using raw data from a nonmotorized treadmill. Ratings of perceived exertion were recorded after, and perceived readiness (PR) recorded before, each series of sprints. Mean power was significantly higher in preseason vs. postseason performance during sprint 1 (760.6 vs. 691.3 W; p = 0.03), sprint 2 (719.9 vs 657.0 W; p = 0.05), sprint 4 (648.4 vs 588.9 W; p = 0.04), and sprint 5 (656.6 vs. 586.8 W, p = 0.04). Ratings of perceived exertion were significantly higher during sprints 3, 4, and 5 postseason with PR significantly higher (indicating less readiness) before sprints 3 and 4. There were no significant differences in REC or decrement score. Overall, athletes were unable to maintain power during subsequent repeated sprint work during postseason. The degree to which the athletes fatigued and recovered between sprints did not change between pre- and postseason testing, however, athletes exhibit increased perceptual strain during the repeated sprint work. These data indicate meaningful performance and per-
Address correspondence to C. Matthew Laurent, [email protected]. 28(12)/3338–3345 Journal of Strength and Conditioning Research Ó 2014 National Strength and Conditioning Association
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ceptual differences throughout the competitive season in collegiate-level hockey players.
KEY WORDS repeated sprint, high-intensity, performance, anaerobic
INTRODUCTION
I
ce hockey is characterized by periods of high-intensity effort interspersed with brief recovery periods. A determinant of success for an athlete depends on their ability to generate high levels of power output during a line shift and throughout the game. A typical line shift will vary depending on a number of factors but will last approximately 30 seconds, and could range up to 85 seconds (2,21). These line shifts consist of variable power demands, integrating starts-and-stops requiring the athlete to generate high bursts of power output quickly while on the ice. The ability to generate power within these starts-and-stops is important and reflects the inherent glycolytic nature of this sport (2). Although power demand during a line shift reflects the importance of the anaerobic system, the aerobic system plays an integral part. Indeed, the role of the aerobic system to ensure recovery between line shifts becomes a critically important factor in determining successful play and should be considered in assessing the athlete (4,9). Although there is not unilateral agreement, research does show utility in dryland testing, and overall, supports the inclusion of off-ice measures when evaluating these athletes (15). For example, a study by Peyer et al. (18) indicated that success across a competitive season was significantly related to off-ice repeated sprint performance. In addition, Farlinger et al. (6) have shown that off-ice 30-m sprints share a significant correlation with on-ice measures of performance. Power et al. (20) have also shown that an on-ice repeated sprint test shares a significant correlation with off-ice assessment of anaerobic power and capacity. Similarly, Roczniok et al. (23) found anaerobic power was significantly correlated with on-ice performance of turns, stops, speed, and endurance. Thus, although not universally accepted, the inclusion
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shifts and games as the season progresses (aerobic recovery) TABLE 1. Changes in anthropometric and body composition among National (23). Therefore, it seems approCollegiate Athletic Association division I men’s hockey players from preseason priate to use tests that can proto postseason (N = 20). vide objective data to identify Mean 6 SD 95% CI p d an athlete’s ability to generate optimal power output, similar Total body mass (kg) to what occurs in a shift of Preseason 87.5 6 7.8 83.7–91.1 Postseason 85.6 6 7.7 82.0–89.3 0.47 0.49 work, as well as ability to Body fat mass (kg) recover to generate optimal Preseason 11.9 6 4.1 10.1–13.9 power in subsequent bouts Postseason 11.5 6 3.4 9.9–13.1 0.72 0.11 (17). Data from this type of testLean body mass (kg) ing can help gauge the toll the Preseason 75.4 6 6.8 72.2–78.6 Postseason 74.1 6 6.4 71.0–77.1 0.54 0.20 physical nature of the sport may Body fat (%) have on performance, which Preseason 13.7 6 3.9 11.8–15.6 may subsequently influence inPostseason 13.4 6 3.3 11.8–14.9 0.77 0.08 season training strategies and Lean body mass (%) help to identify overtraining or Preseason 86.3 6 3.9 84.4–88.1 Postseason 86.6 6 3.3 85.0–88.2 0.77 0.18 staleness from the cumulative load of the season. In addition to the assessment of objective measures of power and performance, the use of subjective measures may proof off-ice testing does seem to possess utility in the assessment vide insight on fatigue and recovery. Ratings of perceived of competitive hockey athletes. Importantly, when athlete exertion (RPEs) are routinely used to assess subjective measures of fatigue during bouts of work and possess unique assessment is completed at regular intervals (e.g., pre- and postutility as they are associated with a variety of physiological, season), it allows associated personnel to monitor physical performance, and psychological mediators (1,22). There is development and performance characteristics of the athletes (26,27). Additionally, data derived from testing can help deteralso emerging literature that suggests that subjective measmine the toll a competitive season may have on performance ures (i.e., perception) of recovery can be a useful correlate of by allowing comparisons of baseline performance measures to performance change (5,13). Perceptual measures of recovery postseason values. The high-impact nature of hockey may may provide a more sensitive measure to identify early signs of overtraining than objective performance measures alone indeed have a negative influence on an athlete’s performance (11,12,14). Therefore, the inclusion of perceptual measures with respect to power output during a line shift (i.e., anaerobic during testing aimed at quantifying differences across a compower and capacity) as well as the ability to recover between petitive season may provide sensitivity to changes that would be absent from analyzing objective performance data alone. Therefore, the purpose of this study was to use an office protocol of repeated sprints to observe changes in performance and perceptual measures between preseason and postseason in a men’s National Collegiate Athletic Association (NCAA) Division I ice hockey team. Data from this testing may provide useful information to strength and conditioning Figure 1. Mean power output for National Collegiate Athletic Association Division I men’s ice-hockey team during repeated sprint testing from pre- to postseason (N = 20). *Significantly different at the p # 0.05 level. professionals regarding the toll a competitive season has on VOLUME 28 | NUMBER 12 | DECEMBER 2014 |
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Pre- to Postseason Changes in Hockey sprints would be negatively affected during postseason vs. preseason testing.
TABLE 2. Changes in decrement score (% decline) during the repeated sprint tests among National Collegiate Athletic Association Division I men’s hockey players from preseason to postseason (N = 20).
Sprint 1 Preseason Postseason Sprint 2 Preseason Postseason Sprint 3 Preseason Postseason Sprint 4 Preseason Postseason Sprint 5 Preseason Postseason
METHODS
Mean 6 SD
95% CI
10.1 6 5.2 12.9 6 4.5
7.7–12.5 10.8–15.0
91.0 6 3.9 88.7 6 3.5
89.2–92.3 87.1–90.3
0.06
0.62
86.1 6 4.5 84.3 6 4.0
83.9–88.2 82.3–86.1
0.18
0.42
80.0 6 6.6 79.1 6 5.4
76.9–83.1 76.5–81.6
0.64
0.15
77.6 6 6.3 75.6 6 4.8
74.6–80.6 73.3–77.9
0.27
0.36
78.4 6 6.9 74.5 6 6.1
75.1–81.6 72.1–77.8
0.10
0.60
p
d
Experimental Approach to the Problem
The current experiment examined changes in power, fatigue, recovery, and perceptual 16.6 6 6.4 13.6–19.5 response during a repeated 18.9 6 5.6 16.3–21.5 0.22 0.38 sprint test of a collegiate men’s ice hockey team pre- and post25.7 6 10.5 20.8–30.6 26.9 6 8.4 23.0–30.8 0.68 0.13 season. The subjects performed repeated sprint tests on a non29.8 6 10.7 24.8–34.8 motorized treadmill (NMT) 32.7 6 8.0 28.9–36.5 0.34 0.31 (Woodway Curve; Woodway, Inc., Waukesha, WI, USA) as 28.4 6 11.4 23.1–33.8 34.3 6 11.4 29.0–39.7 0.11 0.52 part of the team’s pre- and postseason assessment. The repeated sprint tests allowed for the determination of changes in absolute peak power (PP) and mean power (MP), decrement score (DEC), recovery index, and percepthe ability to achieve optimal power output as well as rate tual responses. The design of the repeated sprint test was of fatigue and ability to recover. It was hypothesized that meant to mimic the undulating nature of a line shift in that the team would demonstrate significantly lower power they were 45 seconds in duration with incorporated periods outputs, higher fatigue, and decreased recovery ability of stops-and-starts. Each 45-second sprint was separated by during the postseason compared with preseason. More90-second passive recovery periods and each athlete perover, it was hypothesized that the level of perceived effort formed 5 series of the 45-second sprints. Therefore, this as well as perceived recovery during a test of repeated experimental design was a within-subject repeated measures design with subjects serving as their own control TABLE 3. Changes in recovery score (% of peak power maintained) during the to be compared with the resulrepeated sprint tests among National Collegiate Athletic Association Division I tant changes stemming from men’s hockey players from preseason to postseason (N = 20). participation in a competitive season. Mean 6 SD 95% CI p d Sprint 1 Preseason Postseason Sprint 2 Preseason Postseason Sprint 3 Preseason Postseason Sprint 4 Preseason Postseason Sprint 5 Preseason Postseason
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0.08
0.58
Subjects
All procedures were approved by, and conducted in accordance with, the local university Institutional Review Board for the use of human subjects, and each individual provided written informed consent for participation in this study. The subjects were 20 members (age = 21.6 6 1.3 years [range, 20–24 years]; height = 1.82 6 0.06 m) of an NCAA Division I men’s ice hockey team that was eligible for participation
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Throughout the season, no dryland sprint training was performed as part of their conditioning. All testing were performed at the same time of day, and identical procedures were followed each session. Procedures
Familiarization. After assessment of descriptive data, each individual performed a standardized familiarization session to acclimate to the NMT. This session involved having the subject walk at a self-selected pace for approximately 30 secFigure 2. Rating of perceived exertions for National Collegiate Athletic Association Division I men’s ice-hockey onds, then walk at a faster pace team during repeated sprint testing from pre- to postseason (N = 20). *Significantly different at the p # 0.05 level. progressing to a jog that took about 30 seconds, then a run followed by all 10-second sprints and deceleration. If the during both pre- and postseason test sessions. Initially, 24 subject requested further familiarization, they were afforded members participated in the preseason session, but 4 indithe opportunity. viduals were subsequently omitted from the study as they did not complete the postseason testing. Before the repeated sprint tests, all subjects were assessed for height (m) and total Repeated Sprint Tests. Both testing sessions were preceded by body mass (kg) using a calibrated beam scale (Detecto, an identical 10-minute warm-up on a cycle ergometer Webb City, MO, USA). Body fat percentage was estimated (Monark 828E, Varberg, Sweden) at a self-selected intensity. using air displacement plethysmyogrpahy (i.e., BOD POD; After warm-up, each individual performed 5 series of 45COSMED, Rome, Italy) following manufacturer recommensecond sprints separated by 90 seconds of passive recovery. dations. All subjects were instructed to arrive well hydrated Within the 45-second sprints were undulating periods of and to abstain from alcohol 24 hours and caffeine 4 hours starts-and-stops meant to mimic a line shift. That is, there before testing. These instructions were verbally confirmed at were series of accelerations to maximal effort followed by the beginning of each testing session. For preseason assesssudden stops and reaccelerations to achieve optimal power. ment, subjects were tested within the first week on reporting The sprint trial started with an initial 10-second sprint for preseason camp, and for postseason assessment, athletes followed by a 5-second deceleration, a subsequent 5-second were tested 1 week after the end of their competitive season. sprint followed by 10-second deceleration and walk, then
Figure 3. Perceived readiness for National Collegiate Athletic Association Division I men’s ice-hockey team during repeated sprint testing from pre- to postseason (N = 20). *Significantly different at the p # 0.05 level.
a 5-second sprint, 5-second deceleration, and a final 5second sprint. During the 45second sprint, athletes were provided verbal cues to perform a sprint or deceleration by an investigator who monitored time through specialized software on a PC integrated with the NMT (Curve Software, Version 1.32; World Wide Software Solutions, Inc., Milwaukee, WI, USA). The investigator shouted “start” and “stop” to correspond to periods when athletes were to sprint or decelerate. Previous research investigating the reliability of anaerobic power and
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Pre- to Postseason Changes in Hockey ate, and large at 0.20, 0.50, and 0.80, respectively (3). The TABLE 4. Correlation matrix of perceptual measures with performance measures determination of the relationduring the repeated sprint tests among National Collegiate Athletic Association ships between power, recovDivision I men’s hockey players from preseason to postseason (N = 20).* ery, fatigue, and perceptual Mean power Decrement score Recovery score measures during the testing session for both pre- and postRating of perceived exertion 20.29 20.65 20.63 season was performed using Perceived readiness 20.42 20.72 20.71 simple bivariate correlations. *All correlations significant at p , 0.01 level. All data are reported as the mean 6 SD with 95% confidence intervals (CIs) unless otherwise noted. Statistical performance measures obtained from sprint work on NMTs significance was determined a priori at the 0.05 level of has shown strong reliability (intraclass correlation coefficient significance. All data were analyzed using the Statistical = 0.88–0.96) as well as stable coefficient of variation ranges Package for Social Sciences (IBM Corporation, Armonk, of approximately 4–11% (7,10,24). NY, USA). During the sprints, raw belt speed was obtained from the RESULTS NMT at 120 Hz through a USB cord linked to a PC running specialized software that captures total work time-series in Changes in body composition from pre- to postseason are Joules in real time. After testing, the raw work time-series data shown in Table 1. No changes between pre- and postseason were analyzed using custom software written in NI LabVIEW were significantly different. Although the athletes main2011 (National Instruments, Austin, TX, USA) to calculate tained similar body fat and lean body mass percentages, performance data for each series of sprint work wherein a time there was loss of body mass, fat mass, and fat-free mass derivative analysis of the work waveform was computed to throughout the season. Results from the repeated sprint tests reveal no significant convert work (J) to power output (W). Specific variables difference in PP output from pre- to postseason testing derived from raw data were absolute PP (W), absolute MP (W) throughout each set of the 45-second sprints, a DEC (836.8 6 86.3 vs. 780.9 6 135 W; p = 0.13; d = 0.51). In representing percent decline from PP, and a recovery score addition, PP was achieved in the first 10-second effort of the (REC) representing relative recovery to PP calculated in first series of sprints for all individuals in both pre- and postaccordance with Oliver (16). Immediately after each season testing. The 95% CI for PP preseason was 684– 45-second sprint, RPE was recorded using the 0–10 OMNI 877 W, whereas postseason PP 95% CIs was 488–844 W. running scale (25). Each athlete was given a 90-second passive Figure 1 shows the MP output changes from pre- to postseason and shows the significantly lower MP outputs during recovery period where they were seated in a chair and allowed sprints 1, 2, 4, and 5 while approaching significance at p = to drink water ad libitum. With 15 seconds remaining in the recovery period, athletes provided a perceived readiness (PR) 0.07 level during sprint 3. The effect sizes associated with to begin the next series of sprints using a PR Scale from these differences ranged from 0.59 to 0.71, suggesting the Edwards et al. (5). The PR scale is similar to an RPE scale, significant differences were moderate with respect to effect in that, it consists of numbers (1–7) anchored to categories of size. Comparisons of average DEC score and REC score readiness (from 1-ready to run maximally to 7-not able to data measured during the repeated sprint tests are shown exercise) and has been shown to be a reliable measure of in Tables 2 and 3. As shown, preseason data demonstrate lower, although not significantly, percent decline with conreadiness to perform in previous work (5). These procedures comitantly higher rates of recovery (i.e., REC score) comwere followed identically for both pre- and postseason sessions. pared with postseason. Ratings of perceived exertion and PR between preseason Statistical Analyses and postseason are shown in Figures 2 and 3. The athletes Basic descriptive data for participants were computed and reported significantly higher levels of RPE during postseason analyzed. To determine any significant differences between sprints 3, 4, and 5 (p = 0.04, 0.02, and ,0.01, respectively) pre- and postseason anthropometrics and performance but not sprint 1 or 2 (p = 0.65 and 0.32). The associated during the repeated sprint tests, a series of 1-way analyses effect sizes from sprints 3, 4, and 5 ranged from 0.67 to of variance were performed. There were no violations of 1.17 suggesting large-to-moderate differences between sesthe test for homogeneity of variance for any of the sions. In addition, there was significantly lower readiness variables; therefore, no corrective techniques were applied reported postseason during sprints 4 and 5 (p = 0.03 and to the data. Post hoc effect sizes were calculated between 0.01, respectively), while no significant difference was found differences using Cohen’s d and classified as small, moderbetween sprints 1, 2, or 3 (p = 0.21, 0.70, and 0.42,
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Journal of Strength and Conditioning Research respectively). The effect sizes from sprints 4 and 5 were 0.74 and 0.71, respectively, suggesting moderate differences between sessions with respect to readiness. The relationship between perceptual measures during both the pre- and postseason testing and performance variables are shown in Table 4. Both RPE and PR were significantly related (p , 0.01), albeit only small-to-moderately, and ranged in magnitude from R = 20.30 to 20.72 with performance measures of power output, fatigue, and recovery accounting for between 9 and 51% of the variance in performance variables.
DISCUSSION The purpose of this study was to evaluate changes in power, fatigue, recovery, and perceptual measures between pre- and postseason during repeated sprint tests on an NMT. The primary finding from this study shows that NCAA Division I ice-hockey athletes demonstrate similar PP during pre- and postseason testing but significantly lower MP during undulating sprint work while displaying similar rates of fatigue and recovery (DEC and REC). Additionally, athletes perceive postseason testing as more difficult during a sprint trial and report diminished levels of perceived recovery, despite identical demands during testing. The individuals in this study maintained similar anthropometric and body composition profiles across the competitive season (Table 1) and presented similar values to other studies using comparable participants (2,9,18,19). Although body composition was not significantly different between pre- and postseason testing, athletes did lose total body mass, and of the total body mass lost, about 50% was lean body mass. A study by Green et al. (8) found significant reductions in muscle cross-sectional area across a competitive hockey season, which may explain the loss of lean mass in this study. This is of note as the overarching goal during an in-season training program should be to maintain body mass. When body mass is lost, however, it is not desirable to lose lean body mass. Although our data did not reach significance, it may still be advisable to assess changes in body mass and composition throughout the course of the season to monitor and mediate any undesired loss of mass and minimize the potentially negative impact that may have on performance. There was no significant difference in the athletes’ PP preseason to postseason. To the best of our knowledge, this is the first study aimed specifically to investigate the change in anaerobic power and capacity in this level of competitive athlete. The similarities in PP may suggest that at least during the initial phase of the tests, the anaerobic pathways responsible for power production are relatively unaltered across the season. However, postseason MP outputs during the repeated sprints were significantly lower than preseason values. A comparison of a controlled, pre- to postseason test that measures sport-specific performance with respect to the undulant nature of play may be attractive and appropriate. The current protocol allows for evaluation of PP and MP
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not only from 1 challenge but also over the course of repeated sprints and provides data regarding recovery and fatigue as well as perceptual data. Indeed, had only 1 sprint been used in the testing session, results would have suggested similar performance between the team pre- vs. postseason. However, data show that there are meaningful differences that occur as the session progresses that provide useful information about the toll of a competitive season. Green et al. (8) have previously suggested that there are important biochemical alterations that accompany a competitive hockey season aimed to maintain oxidative pathways at the expense of anaerobic power production. Indeed, initial power production and perception of effort and recovery were not significantly different; however, the consistently diminished MP in the postseason trial suggests athletes may have experienced accumulated fatigue during the season that negatively affects maintenance of power production during the testing on the NMT. Although these findings are novel, future work should examine if changes seen during this off-ice protocol would be congruent to an on-ice performance of repeated sprint work. Despite attenuated power output during postseason testing, no significant differences were found in DEC or REC between sessions (Tables 2 and 3). Superficially, this would indicate that over the course of a season, fatigue (i.e., DEC) incurred during line shifts would remain constant as would rate of recovery. However, the lack of significant differences for DEC and REC may be somewhat misleading and should be interpreted concomitantly with significantly lower postseason power outputs. That is, DEC and REC represent the relative percent of decay and relative ability to regain power within a trial. During the pre- vs. postseason testing, power was reduced significantly and despite producing similar DEC and REC scores, the attenuated power may suggest impaired recovery ability as well as magnified fatigue. Indeed, the data show that despite lower power, and thus, less theoretical metabolic, biomechanical, and physiologic work performed, players fatigue to the same degree. Despite athletes displaying a similar relative decline in power, they were not generating as much absolute power during the postseason assessment, which may suggest increased fatigability. Moreover, because athletes were unable to recover to similar absolute power outputs but only demonstrate similar relative recovery to the attenuated power seen in the postseason, it seems plausible that the toll of the competitive season may have negatively affected the ability to withstand fatigue and recover. Theoretically, a lower power output would have caused less disruption of homeostasis. This, in turn, should have allowed for improved resistance to fatigue and increased ability to recover because of the lower amount of total work performed. However, our data fail to support this, subsequently suggesting that ice hockey athletes fatigue and recover similarly despite achieving significantly lower power output signifying a negative effect of a competitive season on optimal performance and ability to recover. VOLUME 28 | NUMBER 12 | DECEMBER 2014 |
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Pre- to Postseason Changes in Hockey Perceptual measures have been shown to be useful measures during sport and exercise testing as they provide subjective measures as adjuncts to strenuous and invasive physiologic and metabolic measures. It has been shown that perceptual measures provide useful information as they are related to multiple mediators, and importantly, changes in performance (22). In this study, 2 measures of perceptual strain were used: 1 for assessment of fatigue (i.e., RPE) and the other a reflection of recovery (i.e., PR). These measures demonstrated a moderate, negative correlation with MP, REC, and DEC scores. The relationship shared between RPE and measures of performance may indicate accumulated mental fatigue, similar to an accumulated physical fatigue, which could have altered muscle recruitment strategies throughout the repeated sprint sessions. This should be interpreted, although, with caution as no measures of EMG were used to identify altered recruitment strategies. Although correlations between RPE and PR with performance were moderate, perception of recovery with performance may be a more salient finding, not simply because of the higher relationship shared, but because PR is obtained before activity while RPE is taken afterwards. The use of a perceptual recovery measure can be employed quickly and noninvasively to gauge an athlete’s mental readiness to perform as well as indicate potential performance (5). That is, if an athlete reports a lower readiness one could expect lower power output and perhaps higher fatigue during subsequent activity. Therefore, the use of a PR may help guide decisions about recovery afforded during a practice or game situation, thus preserving the athlete from accumulating too much work or experiencing compromised performance. Further research is needed, although, to maximize the utility of this measure to indicate optimal duration of recovery to ensure a successful performance. Additionally, perceptual measures may provide useful data regarding the toll a competitive season has on athletes. There is evidence suggesting perceptual measures as more sensitive indicators of the early signs of overtraining or nonfunctional overreaching (11,13,14). To that end, the use of these measures may not only assure optimal performance within a session or game but when used consistently may help identify those individuals who may need to be monitored for overtraining. Overall, the data show that after a competitive season, athletes are able to generate optimal lower-body power during the initial part of a test of repeated sprinting, but the ability to maintain power is significantly diminished as the test progresses. This could be due to a number of factors that may have incurred as result of a competitive season. Despite optimal PP, latter portions of the postseason data reveal significant differences in power production and capacity in the postseason vs. the preseason. No difference in the decrement of power during the sprints or recovery between sprints was shown in pre- to postseason testing, albeit at lower power outputs during the postseason. Finally, the study shows that the loss of power output during repeated
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sprint work meant to mimic a line shift is accompanied by significantly disrupted levels of perceptual strain, reflected by higher ratings of RPE and perceived recovery that correlate moderately well with performance measures. It is important to note, although, that it would be ideal to have established reliability values associated with this unique protocol to determine minimal expected changes across a season. Future work should aim to establish the reliability of this novel protocol to maximize its potential as a useful tool in identification of true performance change due to participation across a competitive season.
PRACTICAL APPLICATIONS Findings from this study provide multiple points of application to the strength and conditioning professional. Specifically, strength and conditioning professionals working with ice-hockey players are encouraged to be cognizant of the potential negative impact of loss of lean tissue throughout the season, thus, body composition should be monitored throughout the season. In addition, athletes may experience accumulated physical and mental fatigue across a competitive season that can negatively influence anaerobic capacity during performance, and recovery between sessions. Therefore, it is suggested that strength and conditioning professionals monitor, and when necessary, adjust total workload incurred throughout the season by manipulation of either intensity or duration during training sessions. Finally, the study indicates that the use of perceptual measures can help identify level of fatigue incurred as well as recovery achieved during a bout of work. These perceptual measures may serve as accurate estimates of an athlete’s upcoming line shift performance in a practice or game situation, and importantly, could be used to guard against overtraining. Collectively, data from this type of testing may help the strength and conditioning professional to estimate the toll that a competitive season has on their athletes. This, in turn, may allow for the development of individualized strategies to mediate against any overtraining or staleness in an effort to maintain optimal performance throughout the season.
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Journal of Strength and Conditioning Research 7. Gonzalez, AM, Wells, AJ, Hoffman, JR, Stout, JR, Fragala, MS, Mangine, GT, McCormack, WP, Townsend, JR, Jajtner, AR, Emerson, NS, and Robinson IV, EH. Reliability of the Woodway CurveTM non-motorized treadmill for assessing anaerobic performance. J Sports Sci Med 12: 104–108, 2013. 8. Green, HJ, Batada, A, Cole, B, Burnett, ME, Kollias, H, McKay, S, Roy, B, Schertzer, J, Smith, I, and Tupling, S. Cellular response in skeletal muscle to a season of ice hockey. Appl Physiol Nutr Metab 35: 657–670, 2010. 9. Green, MR, Pivarnik, JM, Carrier, DP, and Womack, CJ. Relationship between physiological profiles and on-ice performance of a National Collegiate Athletic Association Division I hockey team. J Strength Cond Res 20: 43–46, 2006. 10. Hughes, MG, Doherty, M, Tong, RJ, Reilly, T, and Cable, NT. Reliability of repeated sprint exercise in non-motorised treadmill ergometry. Int J Sports Med 27: 900–904, 2006. 11. Kentta, G and Hassmen, P. Overtraining and recovery: A conceptual model. Sports Med 26: 1–16, 1998. 12. Lambert, M and Borresen, J. A theoretical basis of monitoring fatigue: A practical approach for coaches. Int J Sports Sci Coach 1: 371–388, 2006. 13. Laurent, CM, Green, JM, Bishop, PA, Sjo¨kvist, J, Schumacker, RE, Richardson, MT, and Curtner-Smith, M. A practical approach to monitoring recovery: Development of a perceived recovery status scale. J Strength Cond Res 25: 620–628, 2011. 14. Morgan, WP, Brown, DR, Raglin, JS, O’Connor, PJ, and Ellickson, KA. Psychological monitoring of overtraining and staleness. Br J Sports Med 21: 107–114, 1987. 15. Nightingale, SC, Miller, S, and Turner, A. The usefuleness and reliability of fitness testing protocols for ice hockey players: A literature review. J Strength Cond Res 27: 1742–1748, 2013.
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18. Peyer, KL, Pivarnik, JM, Eisenmann, JC, and Vorkapich, M. Physiological characteristics of National College Athletic Association Division I ice hockey players and their relation to game performance. J Strength Cond Res 25: 1183–1192, 2011. 19. Potteiger, JA, Smith, DL, Maier, ML, and Foster, TS. Relationship between body composition, leg strength, anaerobic power, and onice skating performance in Divison I men’s hockey athltes. J Strength Cond Res 24: 1755–1762, 2010. 20. Power, A, Faught, BE, Przysucha, E, McPherson, M, and Montelpare, W. Establishing test-retest reliablity and concurrent validity for the Repeated Ice Skating Test (RIST) in adolescent male ice hockey players. Meas Phys Educ Exerc Sci 16: 69–80, 2012. 21. Quinney, HA, Dewart, R, Game, A, Snydmiller, G, Warburton, D, and Bell, G. A 26 year physiological description of a National Hockey League team. Appl Physiol Nutr Metab 33: 753–760, 2008. 22. Robertson, RJ and Noble, BJ. Perceptions of physical exertion; methods, mediators, and applications. Exerc Sports Sci Rev 25: 407– 452, 1997. 23. Roczniok, R, Maszcyzk, A, Czuba, M, Stanula, A, Pietraszewski, P, and Gabrys, T. The predicitive value of on-ice special tests in relation to indexes of aerobic and anaerobic capacity in ice hockey players. Hum Movement 13: 28–32, 2012. 24. Serpiello, FR, McKenna, MJ, Stepto, NK, Bishop, DJ, and Aughey, RJ. Performance and physiological responses to repeatedsprint exercise: A novel multiple set approach. Eur J Appl Physiol 111: 669–678, 2011. 25. Utter, AC, Robertson, RJ, Green, JM, Suminski, RR, McAnulty, SR, and Nieman, DC. Validation of the Adult OMNI Scale of Perceived Exertion for walking/running exercise. Med Sci Sports Exerc 36: 1776–1780, 2004.
16. Oliver, JL. Is a fatigue index a worthwhile measure of repeated sprint ability? J Sci Med Sport 12: 20–23, 2009.
26. Vescovi, JD, Murray, TM, Fiala, KA, and VanHeest, JL. Off-ice performance and draft status of elite ice hockey players. Int J Sports Physiol Perform 1: 207–221, 2006.
17. Petrella, JN, Montelpare, WJ, Nystrom, M, Plyley, M, and Faught, BE. Validation of the FAST skating protcol to predict aerobic power in ice hockey players. Appl Physiol Nutr Metab 32: 693–700, 2007.
27. Vescovi, JD, Murray, TM, and VanHeest, JL. Positional performance profiling of elite ice hockey players. Int J Sports Physiol Perform 1: 84–94, 2006.
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AND
DANIEL A. FISCHER2
1
Exercise Science Program, Bowling Green State University, Bowling Green, Ohio; and 2Department of Athletics, Bowling Green State University, Bowling Green, Ohio ABSTRACT
Laurent, CM, Fullenkamp, AM, Morgan, AL, and Fischer, DA. Power, fatigue, and recovery changes in National Collegiate Athletic Association Division I hockey players across a competitive season. J Strength Cond Res 28(12): 3338–3345, 2014—This study aimed to evaluate changes in pre- to postseason power output, fatigue, and recovery during a repeated sprint test. Twenty National Collegiate Athletic Association Division I men’s hockey athletes performed identical sessions of repeated sprint work pre- and postseason. The repeated sprint test consisted of 5 sets of 45 seconds of repeated sprint work with 90 seconds of rest in between each series of sprints. Power output (W), decrement, and recovery scores (RECs) were determined using raw data from a nonmotorized treadmill. Ratings of perceived exertion were recorded after, and perceived readiness (PR) recorded before, each series of sprints. Mean power was significantly higher in preseason vs. postseason performance during sprint 1 (760.6 vs. 691.3 W; p = 0.03), sprint 2 (719.9 vs 657.0 W; p = 0.05), sprint 4 (648.4 vs 588.9 W; p = 0.04), and sprint 5 (656.6 vs. 586.8 W, p = 0.04). Ratings of perceived exertion were significantly higher during sprints 3, 4, and 5 postseason with PR significantly higher (indicating less readiness) before sprints 3 and 4. There were no significant differences in REC or decrement score. Overall, athletes were unable to maintain power during subsequent repeated sprint work during postseason. The degree to which the athletes fatigued and recovered between sprints did not change between pre- and postseason testing, however, athletes exhibit increased perceptual strain during the repeated sprint work. These data indicate meaningful performance and per-
Address correspondence to C. Matthew Laurent, [email protected]. 28(12)/3338–3345 Journal of Strength and Conditioning Research Ó 2014 National Strength and Conditioning Association
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ceptual differences throughout the competitive season in collegiate-level hockey players.
KEY WORDS repeated sprint, high-intensity, performance, anaerobic
INTRODUCTION
I
ce hockey is characterized by periods of high-intensity effort interspersed with brief recovery periods. A determinant of success for an athlete depends on their ability to generate high levels of power output during a line shift and throughout the game. A typical line shift will vary depending on a number of factors but will last approximately 30 seconds, and could range up to 85 seconds (2,21). These line shifts consist of variable power demands, integrating starts-and-stops requiring the athlete to generate high bursts of power output quickly while on the ice. The ability to generate power within these starts-and-stops is important and reflects the inherent glycolytic nature of this sport (2). Although power demand during a line shift reflects the importance of the anaerobic system, the aerobic system plays an integral part. Indeed, the role of the aerobic system to ensure recovery between line shifts becomes a critically important factor in determining successful play and should be considered in assessing the athlete (4,9). Although there is not unilateral agreement, research does show utility in dryland testing, and overall, supports the inclusion of off-ice measures when evaluating these athletes (15). For example, a study by Peyer et al. (18) indicated that success across a competitive season was significantly related to off-ice repeated sprint performance. In addition, Farlinger et al. (6) have shown that off-ice 30-m sprints share a significant correlation with on-ice measures of performance. Power et al. (20) have also shown that an on-ice repeated sprint test shares a significant correlation with off-ice assessment of anaerobic power and capacity. Similarly, Roczniok et al. (23) found anaerobic power was significantly correlated with on-ice performance of turns, stops, speed, and endurance. Thus, although not universally accepted, the inclusion
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shifts and games as the season progresses (aerobic recovery) TABLE 1. Changes in anthropometric and body composition among National (23). Therefore, it seems approCollegiate Athletic Association division I men’s hockey players from preseason priate to use tests that can proto postseason (N = 20). vide objective data to identify Mean 6 SD 95% CI p d an athlete’s ability to generate optimal power output, similar Total body mass (kg) to what occurs in a shift of Preseason 87.5 6 7.8 83.7–91.1 Postseason 85.6 6 7.7 82.0–89.3 0.47 0.49 work, as well as ability to Body fat mass (kg) recover to generate optimal Preseason 11.9 6 4.1 10.1–13.9 power in subsequent bouts Postseason 11.5 6 3.4 9.9–13.1 0.72 0.11 (17). Data from this type of testLean body mass (kg) ing can help gauge the toll the Preseason 75.4 6 6.8 72.2–78.6 Postseason 74.1 6 6.4 71.0–77.1 0.54 0.20 physical nature of the sport may Body fat (%) have on performance, which Preseason 13.7 6 3.9 11.8–15.6 may subsequently influence inPostseason 13.4 6 3.3 11.8–14.9 0.77 0.08 season training strategies and Lean body mass (%) help to identify overtraining or Preseason 86.3 6 3.9 84.4–88.1 Postseason 86.6 6 3.3 85.0–88.2 0.77 0.18 staleness from the cumulative load of the season. In addition to the assessment of objective measures of power and performance, the use of subjective measures may proof off-ice testing does seem to possess utility in the assessment vide insight on fatigue and recovery. Ratings of perceived of competitive hockey athletes. Importantly, when athlete exertion (RPEs) are routinely used to assess subjective measures of fatigue during bouts of work and possess unique assessment is completed at regular intervals (e.g., pre- and postutility as they are associated with a variety of physiological, season), it allows associated personnel to monitor physical performance, and psychological mediators (1,22). There is development and performance characteristics of the athletes (26,27). Additionally, data derived from testing can help deteralso emerging literature that suggests that subjective measmine the toll a competitive season may have on performance ures (i.e., perception) of recovery can be a useful correlate of by allowing comparisons of baseline performance measures to performance change (5,13). Perceptual measures of recovery postseason values. The high-impact nature of hockey may may provide a more sensitive measure to identify early signs of overtraining than objective performance measures alone indeed have a negative influence on an athlete’s performance (11,12,14). Therefore, the inclusion of perceptual measures with respect to power output during a line shift (i.e., anaerobic during testing aimed at quantifying differences across a compower and capacity) as well as the ability to recover between petitive season may provide sensitivity to changes that would be absent from analyzing objective performance data alone. Therefore, the purpose of this study was to use an office protocol of repeated sprints to observe changes in performance and perceptual measures between preseason and postseason in a men’s National Collegiate Athletic Association (NCAA) Division I ice hockey team. Data from this testing may provide useful information to strength and conditioning Figure 1. Mean power output for National Collegiate Athletic Association Division I men’s ice-hockey team during repeated sprint testing from pre- to postseason (N = 20). *Significantly different at the p # 0.05 level. professionals regarding the toll a competitive season has on VOLUME 28 | NUMBER 12 | DECEMBER 2014 |
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Pre- to Postseason Changes in Hockey sprints would be negatively affected during postseason vs. preseason testing.
TABLE 2. Changes in decrement score (% decline) during the repeated sprint tests among National Collegiate Athletic Association Division I men’s hockey players from preseason to postseason (N = 20).
Sprint 1 Preseason Postseason Sprint 2 Preseason Postseason Sprint 3 Preseason Postseason Sprint 4 Preseason Postseason Sprint 5 Preseason Postseason
METHODS
Mean 6 SD
95% CI
10.1 6 5.2 12.9 6 4.5
7.7–12.5 10.8–15.0
91.0 6 3.9 88.7 6 3.5
89.2–92.3 87.1–90.3
0.06
0.62
86.1 6 4.5 84.3 6 4.0
83.9–88.2 82.3–86.1
0.18
0.42
80.0 6 6.6 79.1 6 5.4
76.9–83.1 76.5–81.6
0.64
0.15
77.6 6 6.3 75.6 6 4.8
74.6–80.6 73.3–77.9
0.27
0.36
78.4 6 6.9 74.5 6 6.1
75.1–81.6 72.1–77.8
0.10
0.60
p
d
Experimental Approach to the Problem
The current experiment examined changes in power, fatigue, recovery, and perceptual 16.6 6 6.4 13.6–19.5 response during a repeated 18.9 6 5.6 16.3–21.5 0.22 0.38 sprint test of a collegiate men’s ice hockey team pre- and post25.7 6 10.5 20.8–30.6 26.9 6 8.4 23.0–30.8 0.68 0.13 season. The subjects performed repeated sprint tests on a non29.8 6 10.7 24.8–34.8 motorized treadmill (NMT) 32.7 6 8.0 28.9–36.5 0.34 0.31 (Woodway Curve; Woodway, Inc., Waukesha, WI, USA) as 28.4 6 11.4 23.1–33.8 34.3 6 11.4 29.0–39.7 0.11 0.52 part of the team’s pre- and postseason assessment. The repeated sprint tests allowed for the determination of changes in absolute peak power (PP) and mean power (MP), decrement score (DEC), recovery index, and percepthe ability to achieve optimal power output as well as rate tual responses. The design of the repeated sprint test was of fatigue and ability to recover. It was hypothesized that meant to mimic the undulating nature of a line shift in that the team would demonstrate significantly lower power they were 45 seconds in duration with incorporated periods outputs, higher fatigue, and decreased recovery ability of stops-and-starts. Each 45-second sprint was separated by during the postseason compared with preseason. More90-second passive recovery periods and each athlete perover, it was hypothesized that the level of perceived effort formed 5 series of the 45-second sprints. Therefore, this as well as perceived recovery during a test of repeated experimental design was a within-subject repeated measures design with subjects serving as their own control TABLE 3. Changes in recovery score (% of peak power maintained) during the to be compared with the resulrepeated sprint tests among National Collegiate Athletic Association Division I tant changes stemming from men’s hockey players from preseason to postseason (N = 20). participation in a competitive season. Mean 6 SD 95% CI p d Sprint 1 Preseason Postseason Sprint 2 Preseason Postseason Sprint 3 Preseason Postseason Sprint 4 Preseason Postseason Sprint 5 Preseason Postseason
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0.08
0.58
Subjects
All procedures were approved by, and conducted in accordance with, the local university Institutional Review Board for the use of human subjects, and each individual provided written informed consent for participation in this study. The subjects were 20 members (age = 21.6 6 1.3 years [range, 20–24 years]; height = 1.82 6 0.06 m) of an NCAA Division I men’s ice hockey team that was eligible for participation
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Throughout the season, no dryland sprint training was performed as part of their conditioning. All testing were performed at the same time of day, and identical procedures were followed each session. Procedures
Familiarization. After assessment of descriptive data, each individual performed a standardized familiarization session to acclimate to the NMT. This session involved having the subject walk at a self-selected pace for approximately 30 secFigure 2. Rating of perceived exertions for National Collegiate Athletic Association Division I men’s ice-hockey onds, then walk at a faster pace team during repeated sprint testing from pre- to postseason (N = 20). *Significantly different at the p # 0.05 level. progressing to a jog that took about 30 seconds, then a run followed by all 10-second sprints and deceleration. If the during both pre- and postseason test sessions. Initially, 24 subject requested further familiarization, they were afforded members participated in the preseason session, but 4 indithe opportunity. viduals were subsequently omitted from the study as they did not complete the postseason testing. Before the repeated sprint tests, all subjects were assessed for height (m) and total Repeated Sprint Tests. Both testing sessions were preceded by body mass (kg) using a calibrated beam scale (Detecto, an identical 10-minute warm-up on a cycle ergometer Webb City, MO, USA). Body fat percentage was estimated (Monark 828E, Varberg, Sweden) at a self-selected intensity. using air displacement plethysmyogrpahy (i.e., BOD POD; After warm-up, each individual performed 5 series of 45COSMED, Rome, Italy) following manufacturer recommensecond sprints separated by 90 seconds of passive recovery. dations. All subjects were instructed to arrive well hydrated Within the 45-second sprints were undulating periods of and to abstain from alcohol 24 hours and caffeine 4 hours starts-and-stops meant to mimic a line shift. That is, there before testing. These instructions were verbally confirmed at were series of accelerations to maximal effort followed by the beginning of each testing session. For preseason assesssudden stops and reaccelerations to achieve optimal power. ment, subjects were tested within the first week on reporting The sprint trial started with an initial 10-second sprint for preseason camp, and for postseason assessment, athletes followed by a 5-second deceleration, a subsequent 5-second were tested 1 week after the end of their competitive season. sprint followed by 10-second deceleration and walk, then
Figure 3. Perceived readiness for National Collegiate Athletic Association Division I men’s ice-hockey team during repeated sprint testing from pre- to postseason (N = 20). *Significantly different at the p # 0.05 level.
a 5-second sprint, 5-second deceleration, and a final 5second sprint. During the 45second sprint, athletes were provided verbal cues to perform a sprint or deceleration by an investigator who monitored time through specialized software on a PC integrated with the NMT (Curve Software, Version 1.32; World Wide Software Solutions, Inc., Milwaukee, WI, USA). The investigator shouted “start” and “stop” to correspond to periods when athletes were to sprint or decelerate. Previous research investigating the reliability of anaerobic power and
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Pre- to Postseason Changes in Hockey ate, and large at 0.20, 0.50, and 0.80, respectively (3). The TABLE 4. Correlation matrix of perceptual measures with performance measures determination of the relationduring the repeated sprint tests among National Collegiate Athletic Association ships between power, recovDivision I men’s hockey players from preseason to postseason (N = 20).* ery, fatigue, and perceptual Mean power Decrement score Recovery score measures during the testing session for both pre- and postRating of perceived exertion 20.29 20.65 20.63 season was performed using Perceived readiness 20.42 20.72 20.71 simple bivariate correlations. *All correlations significant at p , 0.01 level. All data are reported as the mean 6 SD with 95% confidence intervals (CIs) unless otherwise noted. Statistical performance measures obtained from sprint work on NMTs significance was determined a priori at the 0.05 level of has shown strong reliability (intraclass correlation coefficient significance. All data were analyzed using the Statistical = 0.88–0.96) as well as stable coefficient of variation ranges Package for Social Sciences (IBM Corporation, Armonk, of approximately 4–11% (7,10,24). NY, USA). During the sprints, raw belt speed was obtained from the RESULTS NMT at 120 Hz through a USB cord linked to a PC running specialized software that captures total work time-series in Changes in body composition from pre- to postseason are Joules in real time. After testing, the raw work time-series data shown in Table 1. No changes between pre- and postseason were analyzed using custom software written in NI LabVIEW were significantly different. Although the athletes main2011 (National Instruments, Austin, TX, USA) to calculate tained similar body fat and lean body mass percentages, performance data for each series of sprint work wherein a time there was loss of body mass, fat mass, and fat-free mass derivative analysis of the work waveform was computed to throughout the season. Results from the repeated sprint tests reveal no significant convert work (J) to power output (W). Specific variables difference in PP output from pre- to postseason testing derived from raw data were absolute PP (W), absolute MP (W) throughout each set of the 45-second sprints, a DEC (836.8 6 86.3 vs. 780.9 6 135 W; p = 0.13; d = 0.51). In representing percent decline from PP, and a recovery score addition, PP was achieved in the first 10-second effort of the (REC) representing relative recovery to PP calculated in first series of sprints for all individuals in both pre- and postaccordance with Oliver (16). Immediately after each season testing. The 95% CI for PP preseason was 684– 45-second sprint, RPE was recorded using the 0–10 OMNI 877 W, whereas postseason PP 95% CIs was 488–844 W. running scale (25). Each athlete was given a 90-second passive Figure 1 shows the MP output changes from pre- to postseason and shows the significantly lower MP outputs during recovery period where they were seated in a chair and allowed sprints 1, 2, 4, and 5 while approaching significance at p = to drink water ad libitum. With 15 seconds remaining in the recovery period, athletes provided a perceived readiness (PR) 0.07 level during sprint 3. The effect sizes associated with to begin the next series of sprints using a PR Scale from these differences ranged from 0.59 to 0.71, suggesting the Edwards et al. (5). The PR scale is similar to an RPE scale, significant differences were moderate with respect to effect in that, it consists of numbers (1–7) anchored to categories of size. Comparisons of average DEC score and REC score readiness (from 1-ready to run maximally to 7-not able to data measured during the repeated sprint tests are shown exercise) and has been shown to be a reliable measure of in Tables 2 and 3. As shown, preseason data demonstrate lower, although not significantly, percent decline with conreadiness to perform in previous work (5). These procedures comitantly higher rates of recovery (i.e., REC score) comwere followed identically for both pre- and postseason sessions. pared with postseason. Ratings of perceived exertion and PR between preseason Statistical Analyses and postseason are shown in Figures 2 and 3. The athletes Basic descriptive data for participants were computed and reported significantly higher levels of RPE during postseason analyzed. To determine any significant differences between sprints 3, 4, and 5 (p = 0.04, 0.02, and ,0.01, respectively) pre- and postseason anthropometrics and performance but not sprint 1 or 2 (p = 0.65 and 0.32). The associated during the repeated sprint tests, a series of 1-way analyses effect sizes from sprints 3, 4, and 5 ranged from 0.67 to of variance were performed. There were no violations of 1.17 suggesting large-to-moderate differences between sesthe test for homogeneity of variance for any of the sions. In addition, there was significantly lower readiness variables; therefore, no corrective techniques were applied reported postseason during sprints 4 and 5 (p = 0.03 and to the data. Post hoc effect sizes were calculated between 0.01, respectively), while no significant difference was found differences using Cohen’s d and classified as small, moderbetween sprints 1, 2, or 3 (p = 0.21, 0.70, and 0.42,
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Journal of Strength and Conditioning Research respectively). The effect sizes from sprints 4 and 5 were 0.74 and 0.71, respectively, suggesting moderate differences between sessions with respect to readiness. The relationship between perceptual measures during both the pre- and postseason testing and performance variables are shown in Table 4. Both RPE and PR were significantly related (p , 0.01), albeit only small-to-moderately, and ranged in magnitude from R = 20.30 to 20.72 with performance measures of power output, fatigue, and recovery accounting for between 9 and 51% of the variance in performance variables.
DISCUSSION The purpose of this study was to evaluate changes in power, fatigue, recovery, and perceptual measures between pre- and postseason during repeated sprint tests on an NMT. The primary finding from this study shows that NCAA Division I ice-hockey athletes demonstrate similar PP during pre- and postseason testing but significantly lower MP during undulating sprint work while displaying similar rates of fatigue and recovery (DEC and REC). Additionally, athletes perceive postseason testing as more difficult during a sprint trial and report diminished levels of perceived recovery, despite identical demands during testing. The individuals in this study maintained similar anthropometric and body composition profiles across the competitive season (Table 1) and presented similar values to other studies using comparable participants (2,9,18,19). Although body composition was not significantly different between pre- and postseason testing, athletes did lose total body mass, and of the total body mass lost, about 50% was lean body mass. A study by Green et al. (8) found significant reductions in muscle cross-sectional area across a competitive hockey season, which may explain the loss of lean mass in this study. This is of note as the overarching goal during an in-season training program should be to maintain body mass. When body mass is lost, however, it is not desirable to lose lean body mass. Although our data did not reach significance, it may still be advisable to assess changes in body mass and composition throughout the course of the season to monitor and mediate any undesired loss of mass and minimize the potentially negative impact that may have on performance. There was no significant difference in the athletes’ PP preseason to postseason. To the best of our knowledge, this is the first study aimed specifically to investigate the change in anaerobic power and capacity in this level of competitive athlete. The similarities in PP may suggest that at least during the initial phase of the tests, the anaerobic pathways responsible for power production are relatively unaltered across the season. However, postseason MP outputs during the repeated sprints were significantly lower than preseason values. A comparison of a controlled, pre- to postseason test that measures sport-specific performance with respect to the undulant nature of play may be attractive and appropriate. The current protocol allows for evaluation of PP and MP
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not only from 1 challenge but also over the course of repeated sprints and provides data regarding recovery and fatigue as well as perceptual data. Indeed, had only 1 sprint been used in the testing session, results would have suggested similar performance between the team pre- vs. postseason. However, data show that there are meaningful differences that occur as the session progresses that provide useful information about the toll of a competitive season. Green et al. (8) have previously suggested that there are important biochemical alterations that accompany a competitive hockey season aimed to maintain oxidative pathways at the expense of anaerobic power production. Indeed, initial power production and perception of effort and recovery were not significantly different; however, the consistently diminished MP in the postseason trial suggests athletes may have experienced accumulated fatigue during the season that negatively affects maintenance of power production during the testing on the NMT. Although these findings are novel, future work should examine if changes seen during this off-ice protocol would be congruent to an on-ice performance of repeated sprint work. Despite attenuated power output during postseason testing, no significant differences were found in DEC or REC between sessions (Tables 2 and 3). Superficially, this would indicate that over the course of a season, fatigue (i.e., DEC) incurred during line shifts would remain constant as would rate of recovery. However, the lack of significant differences for DEC and REC may be somewhat misleading and should be interpreted concomitantly with significantly lower postseason power outputs. That is, DEC and REC represent the relative percent of decay and relative ability to regain power within a trial. During the pre- vs. postseason testing, power was reduced significantly and despite producing similar DEC and REC scores, the attenuated power may suggest impaired recovery ability as well as magnified fatigue. Indeed, the data show that despite lower power, and thus, less theoretical metabolic, biomechanical, and physiologic work performed, players fatigue to the same degree. Despite athletes displaying a similar relative decline in power, they were not generating as much absolute power during the postseason assessment, which may suggest increased fatigability. Moreover, because athletes were unable to recover to similar absolute power outputs but only demonstrate similar relative recovery to the attenuated power seen in the postseason, it seems plausible that the toll of the competitive season may have negatively affected the ability to withstand fatigue and recover. Theoretically, a lower power output would have caused less disruption of homeostasis. This, in turn, should have allowed for improved resistance to fatigue and increased ability to recover because of the lower amount of total work performed. However, our data fail to support this, subsequently suggesting that ice hockey athletes fatigue and recover similarly despite achieving significantly lower power output signifying a negative effect of a competitive season on optimal performance and ability to recover. VOLUME 28 | NUMBER 12 | DECEMBER 2014 |
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Pre- to Postseason Changes in Hockey Perceptual measures have been shown to be useful measures during sport and exercise testing as they provide subjective measures as adjuncts to strenuous and invasive physiologic and metabolic measures. It has been shown that perceptual measures provide useful information as they are related to multiple mediators, and importantly, changes in performance (22). In this study, 2 measures of perceptual strain were used: 1 for assessment of fatigue (i.e., RPE) and the other a reflection of recovery (i.e., PR). These measures demonstrated a moderate, negative correlation with MP, REC, and DEC scores. The relationship shared between RPE and measures of performance may indicate accumulated mental fatigue, similar to an accumulated physical fatigue, which could have altered muscle recruitment strategies throughout the repeated sprint sessions. This should be interpreted, although, with caution as no measures of EMG were used to identify altered recruitment strategies. Although correlations between RPE and PR with performance were moderate, perception of recovery with performance may be a more salient finding, not simply because of the higher relationship shared, but because PR is obtained before activity while RPE is taken afterwards. The use of a perceptual recovery measure can be employed quickly and noninvasively to gauge an athlete’s mental readiness to perform as well as indicate potential performance (5). That is, if an athlete reports a lower readiness one could expect lower power output and perhaps higher fatigue during subsequent activity. Therefore, the use of a PR may help guide decisions about recovery afforded during a practice or game situation, thus preserving the athlete from accumulating too much work or experiencing compromised performance. Further research is needed, although, to maximize the utility of this measure to indicate optimal duration of recovery to ensure a successful performance. Additionally, perceptual measures may provide useful data regarding the toll a competitive season has on athletes. There is evidence suggesting perceptual measures as more sensitive indicators of the early signs of overtraining or nonfunctional overreaching (11,13,14). To that end, the use of these measures may not only assure optimal performance within a session or game but when used consistently may help identify those individuals who may need to be monitored for overtraining. Overall, the data show that after a competitive season, athletes are able to generate optimal lower-body power during the initial part of a test of repeated sprinting, but the ability to maintain power is significantly diminished as the test progresses. This could be due to a number of factors that may have incurred as result of a competitive season. Despite optimal PP, latter portions of the postseason data reveal significant differences in power production and capacity in the postseason vs. the preseason. No difference in the decrement of power during the sprints or recovery between sprints was shown in pre- to postseason testing, albeit at lower power outputs during the postseason. Finally, the study shows that the loss of power output during repeated
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sprint work meant to mimic a line shift is accompanied by significantly disrupted levels of perceptual strain, reflected by higher ratings of RPE and perceived recovery that correlate moderately well with performance measures. It is important to note, although, that it would be ideal to have established reliability values associated with this unique protocol to determine minimal expected changes across a season. Future work should aim to establish the reliability of this novel protocol to maximize its potential as a useful tool in identification of true performance change due to participation across a competitive season.
PRACTICAL APPLICATIONS Findings from this study provide multiple points of application to the strength and conditioning professional. Specifically, strength and conditioning professionals working with ice-hockey players are encouraged to be cognizant of the potential negative impact of loss of lean tissue throughout the season, thus, body composition should be monitored throughout the season. In addition, athletes may experience accumulated physical and mental fatigue across a competitive season that can negatively influence anaerobic capacity during performance, and recovery between sessions. Therefore, it is suggested that strength and conditioning professionals monitor, and when necessary, adjust total workload incurred throughout the season by manipulation of either intensity or duration during training sessions. Finally, the study indicates that the use of perceptual measures can help identify level of fatigue incurred as well as recovery achieved during a bout of work. These perceptual measures may serve as accurate estimates of an athlete’s upcoming line shift performance in a practice or game situation, and importantly, could be used to guard against overtraining. Collectively, data from this type of testing may help the strength and conditioning professional to estimate the toll that a competitive season has on their athletes. This, in turn, may allow for the development of individualized strategies to mediate against any overtraining or staleness in an effort to maintain optimal performance throughout the season.
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