RESISTED SPRINTS DO NOT ACUTELY ENHANCE SPRINTING PERFORMANCE NIAMH WHELAN, CIARAN O’REGAN,
AND
ANDREW J. HARRISON
Biomechanics Research Unit, University of Limerick, Limerick, Ireland ABSTRACT
INTRODUCTION
Whelan, N, O’Regan, C, and Harrison, AJ. Resisted sprints do not acutely enhance sprinting performance. J Strength Cond Res 28(7): 1858–1866, 2014—Sprinting speed is a vital component of successful performance in many sports. Long-term resisted sprint training has been shown to improve early acceleration performance, but the acute post-activation potentiation (PAP) effects of resisted sprinting on subsequent performance remain unclear. The purpose of this investigation was to examine the effects of resisted sprinting on sprinting and factors related to sprint performance. Twelve active males participated in a pretest involving ten 10-m sprints through dual-beam timing gates and 10-m Optojump Next System with full recovery. This provided baseline data on step rate, step length, ground contact time, and running speed over the first 6 steps of a maximum effort sprint. One week later, the participants performed three 10-m resisted sprints using a sled loaded to 25–30% body mass followed by a 10-m sprint at 1, 2, 4, 6, 8, and 10 minutes after the final resisted sprint. The data were analyzed using an adapted typical error analysis and repeated measures analysis of variance. The results using analysis of variance provided evidence of significant initial fatigue followed by the enhancement of mean step rate, contact time, reactive strength index, and running speed in 10-m sprints performed after the resisted sprinting (p . 0.05). By contrast, the typical error analysis showed that this enhancement was limited and unsystematic in nature with little clear evidence of fatigue followed by potentiation. The results using typical error data do not provide strong evidence of PAP in 10-m sprint performance after resisted sprinting.
KEY WORDS resisted running, reactive strength index, ground contact time, typical errors, post-activation potentiation
Address correspondence to Dr. Andrew J. Harrison, drew.harrison@ul. ie. 28(7)/1858–1866 Journal of Strength and Conditioning Research Ó 2014 National Strength and Conditioning Association
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printing speed is a characteristic that is vital to successful performance in many sports (4,18). The initial acceleration phase of sprinting (from 0 to 10 m) is probably the most important phase in team sports (13). An athlete’s ability to accelerate can depend on their running kinematics and their capacity for force production (10). The kinematic parameters that determine acceleration and velocity include: step length (SL), step frequency (SF), ground contact time (CT), and flight time (23). Resisted sprints (RS) training methods using towing devices, sleds, and weighted vests have been shown to improve early acceleration phase sprinting performance when implemented over a sustained period, whereas complex training/contrast training methods have been shown to induce acute improvements in sprint performance (2). Complex training involves the combination of a heavily loaded exercise followed by a biomechanically similar plyometric exercise (29). It is based on the phenomenon of post-activation potentiation (PAP), which can be considered either from a physiological perspective or with respect to physical performance (i.e., running faster or jumping higher). Post-activation potentiation can present as an acute enhancement of performance or an enhancement of factors influencing performance after a preload stimulus. Generally, this PAP effect appears as a sequence of performance decrement due to acute fatigue followed by enhanced performance (6,7). No study to date has examined whether RS training can produce an acute PAP effect on sprint performance. Several studies have examined the acute and chronic effects of RS on kinematics (1,9,10,18,24) and kinetics (20,25). The literature shows that the load used in RS training has varied considerably across studies and no criterion for optimal loading has been established for longitudinal or acute studies. Lockie et al. (24) suggested that for optimal long-term training effects, the resistance load should decrease sprint velocity during RS by no more than 10%, and this recommendation has since been used in studies by Alcaraz et al. (1) and Clark et al. (4). The resistance load on RS training studies has ranged from 10 to 30% of the body mass (1,4,9,15,24,26,28). Recently, Linthorne et al. (22) examined the effect of the coefficient of friction on sprinting while towing a weighted sled across various
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Figure 1. Effects of resisted sprinting on step length across the first 6 steps in the sprint (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
surfaces and recommended a trial-and-error approach to find the most appropriate sled weight for an athlete to use on any given running surface. No study to date has established an optimal sled load for RS that may cause an acute PAP effect after RS; however, from complex training studies, it is known that heavy resistances in the preload activity (i.e., .90% of a single repetition maximum) are usually required to cause a PAP response (7). Although a significant amount of research exists on RS and PAP; research is limited on whether RS can provide an acute enhancement of sprint performance. Crewther et al. (8) suggested that PAP responses may depend on the specificity of the movement pattern in the preload exercise, therefore RS could have a potentiating effect on sprint performance because the movement pattern of RS is similar to sprinting and may have greater specificity than weighted
squats. RS is often used by athletes as a form of contrast training where sled resisted sprinting is followed by free sprinting with an expectation that the free sprint performance will be improved after RS. Such acute enhancements could be beneficial to athletes as a means of improving competition or training performance. Despite the widespread practice of this form of contrast training, no research to date has examined whether RS can induce a PAP response or a classic fatigue-potentiation sequence. There is a clear need to evaluate whether RS using sled towing generates a potentiation effect on sprint performance during recovery and examine whether there are specific changes in the factors that determine sprint performance such as SL, SF, and CT. Therefore, the aim of this study was to investigate the acute PAP effect of sled training on sprint performance– related factors including SF, SL, CT, and reactive strength VOLUME 28 | NUMBER 7 | JULY 2014 |
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Resisted Sprinting Effects on Sprint Performance
Figure 2. Effects of resisted sprinting on step rate across first the 6 steps in the sprint, (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
index (RSI). In addition, a comparison is made between typical error analysis and repeated measures analysis of variance (RM-ANOVA) methodologies and their suitability for correctly identifying PAP responses in sprint biomechanics.
METHODS Experimental Approach to the Problem
The investigation used a simple pretest posttest design and required the participants to complete testing on 2 separate days. On the first day, the participants completed a standard warm-up, which included a 3-minute jog, various shortduration stretches of the lower limb followed by some sprint specific dynamic exercises. This was followed by 10 3 10 m sprints at maximum effort with a 2-minute recovery between each run. Data obtained in these sprints were used to deter-
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mine the pretest means and typical error thresholds for sprint time, CT, RSI, and velocity in the first 6 steps of the sprint. One week later, the participants completed a standard warm–up, and 3 sled pulls over 10 m with a load of 25–30% of body mass with 90 seconds recovery between each resisted run. The participants then performed maximum effort unresisted sprints at 1, 2, 4, 6, 8, and 10 minutes after the third sled pull. The sprint times, CT, RSI, and velocity for the first 6 steps were compared with the pretest scores using both RM-ANOVA and typical error analysis. Subjects
Twelve (n = 12) physically active men aged 22.5 6 3.9 years, age range 19 to 35 years, (mean 6 SD), mass 74 6 5.9 kg, height 1.77 6 0.05 m, participated in this study. All participants were injury free and had completed at least 3 training
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Figure 3. Effects of resisted sprinting on ground contact time across the first 6 steps in the sprint (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05).
sessions per week in team sports or individual sports such as: hurling, Gaelic football, soccer, athletics, rowing, and triathlon in the 3 months weeks before testing. Participants were excluded from the study if they had previously suffered a lower limb injury in the 3 months before the testing. Ethical approval for the study was granted from the university research ethics committee, and written consent was obtained from all participants. Before taking part in the study, all participants completed a physical activity questionnaire and provided informed consent in writing. For the duration of the testing session, the participants wore their own shorts, t-shirt, and running shoes. Instrumentation
All testing took place on an indoor synthetic track surface and was completed over a period of 2 days. Sprint times over
5 and 10 m were recorded using Racetime 2, dual-beam timing gates (Microgate, Bolzano, Italy). Additional temporal event variables during sprinting were recorded using the Optojump Next system (Microgate, Bolzano, Italy). The timing gates and 10 m of Optojump Next system rails were set up to record times and footfall events during the 10 m sprint. The timing gates were placed at the beginning of the Optojump lane (0 m) and at 5 m and 10 m from the start, and both systems were electronically synchronized so that the Optojump began recording data when the first timing the gate beam was broken. Participants started each sprint from a standard 2 point (standing) starting position with their front foot placed behind a line 70 cm behind the first set of timing gates thus ensuring that they did not trigger the timing gates before the start of each sprint. VOLUME 28 | NUMBER 7 | JULY 2014 |
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Resisted Sprinting Effects on Sprint Performance
Figure 4. Effects of resisted sprinting on reactive strength index across the first 6 steps in the sprint (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
Two sled devices weighing 3.7 kg and 4.3 kg were used; mass was added to the sled in increments of 2.5 kg. The total sled mass for each participant was adjusted to approximately 25–30% of the body mass (to the nearest 2.5 kg); this mass also included the mass of the sled. The sled was attached to the participant with a shoulder harness and nonelastic rope. The 25–30% body mass load was chosen because this was near the upper limit of resistance used in sled resistance running studies and evidence from complex training studies indicated that higher resistance loads are normally required to cause a PAP response (7). Testing Procedures
Standardized Warm-up. All participants performed a standard warm-up consisting of 3 minutes of low-intensity jogging short-duration static stretching that included 1 exercise for
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each lower limb muscles (hamstrings, quadriceps, and calf muscles), which were held for 10 seconds and repeated 3 times. Participants then performed 2 sets of sprint-specific drills including: an “A march,” an “A skip,” a power skip over 10 m, and a wall drive exercise. They also completed three 10-m runs at approximately 50, 75, and 100% effort. Pretest. The first session (pretest) began with the standard warm-up outlined above. The participant then performed 10 maximum effort sprinting trials over a distance of 10 m with 2 minutes of recovery between each run. Participants were instructed to begin each sprint from a standing start position and to sprint as fast as they could past the 10-m timing gate. It was emphasized to them that they should run straight through the 10-m mark and not to slow down before it.
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Figure 5. Effects of resisted sprinting on running speed across the first 6 steps in the sprint (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
They were also instructed to avoid any rocking or forward movements before starting each trial. Sled Towing Intervention. In this session, the same warm-up procedures were used. Additionally, 3 sled pulls over 10 m with 90 seconds of recovery between each sled pull were completed before the running trials. The participant was required to perform each 10-m sled pull at maximum effort. The same track surface and the same lane were used for this session, and the participants were instructed to wear the same type of clothing and footwear as in the previous testing session. Posttest. One minute after the final sled pull, the participant performed the first unloaded run through the Optojump and
timing gates, and again at 2, 4, 6, 8, and 10 minutes after the last sled pull. Statistical Analyses
The data were analyzed using both RM-ANOVA and typical error analysis procedures. The RM-ANOVA was used to determine significant differences between the pretest mean and the posttest minimum and maximum mean scores. The maximum and minimum posttest scores were therefore compared with each subject’s mean of the 10 pretest trials. Typical error analysis was used to determine the pretest and posttest differences on an individual basis. This involved calculating the mean and within-subject standard deviation (SDwithin-subject) of the 10 pre-test trials to establish the upper and lower limits of variation. Using the recommendations of Hopkins (16,17), a potentiation event was defined as an VOLUME 28 | NUMBER 7 | JULY 2014 |
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Resisted Sprinting Effects on Sprint Performance
Figure 6. Effects of resisted sprinting on running speed through the timing gates at 0–5 m; 5–10 m, and 0–10 m. * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
improvement in a parameter of 1.5 3 SDwithin-subject relative to the mean score. Similarly, a fatigue event was defined as a worsening of a parameter by 1.5 3 SDwithin-subject relative to the mean score. In cases where an improvement in performance was indicated by a lower score (e.g., CT), a PAP event was represented by a score lower than typical error lower threshold. Using the typical error analysis, it was possible to identify the number of fatigue and potentiation events and fatigue-potentiation sequences that occurred on an individual subject and group basis.
TABLE 1. Analysis of potentiation and fatigue events and fatigue-potentiation patterns using typical error comparisons on Optojump Next data.* Variable
N
%
CT
39 28 2 39 62 7 48 7 0 45 57 7 67 31 1
9.0 6.48 2.8 9.0 14.4 9.8 11.1 1.6 0 10.4 13.2 9.7 15.5 7.2 1.4
Fatigue events PAP events Fatigue-PAP sequences RSI Fatigue events PAP events Fatigue-PAP sequences Velocity Fatigue events PAP events Fatigue-PAP sequences Stride length Fatigue events PAP events Fatigue-PAP sequences Step rate Fatigue events PAP events Fatigue-PAP sequences
*CT = ground contact time; RSI = reactive strength index; AP = post-activation potentiation.
RESULTS The results of the RM-ANOVA comparing group means for pretest with the minimum and maximum mean scores for SL, step rate, velocity, CT, and RSI for each of the first 6 steps during the posttest sprints are presented in Figure 1–5. These data show statistically significant improvements between the pretest and posttest maximum scores for all dependent variables. This analysis suggests the existence of both fatigue and PAP in the dependent variables in the posttest period. The results of the RM-ANOVA comparing group means for pretest with the minimum and maximum mean scores for average velocities through timing gates at 0–5 m, 5–10 m, and 0–10 m are shown in Figure 6. The results indicate significant reductions in running speed but no significant increases through 0–5 m, 5–10 m, or 0–10 m compared with pretest mean velocities. The results of the comparison of pretest and posttest scores in CT, RSI, velocity, SL, and step rate using typical error analysis to identify potentiation and fatigue events as well as fatigue-potentiation sequences during the first 6 steps of the sprint tests using the Optojump Next data are presented in Table 1. The results show only a small percentage of potentiation and fatigue events in relation to the total number of measures for CT, RSI, velocity, SL, and step rate. Of particular interest are the very small percentages of fatigue-potentiation sequences for each variable (velocity = 0%, step rate = 1.4%, and CT = 2.8%). The typical error analysis of average velocities determined using the optical timing gates found no evidence of fatigue or potentiation events.
DISCUSSION The RM-ANOVA results in Figure 1–5 seem to show patterns of fatigue and PAP which are similar to those found in
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Journal of Strength and Conditioning Research other studies where PAP effects were investigated (2,8,29,30). None of these studies investigated acute fatigue or PAP effects resulting from RS; however, the coexistence of fatigue and PAP during recovery and the pattern of fatigue followed by PAP is typical of several complex and contrast training studies (2,5,6,7,14,21). Several studies have suggested that PAP responses vary considerably between individuals and can be dependent on factors such as training age, intensity of the pre-load activity, and duration of the recovery period (3,6,11,12,19). The comparison of mean velocity through the timing gates in Figure 6 indicated significant fatigue effects for average velocities at 0–5 m, 5–10 m, and 0–10 m compared with pretest velocities. These data suggest that the RS induced fatigue related reductions in running speed over the first 10 m but no significant PAP effects were found on overall sprint performance. This is consistent with the findings of other studies examining PAP effects, which showed no significant PAP on overall performance measures but significant PAP effects on factors related to performance such as CT and RSI, (5,7). Harrison and Bourke (15) and Spinks et al. (27) examined RS training effects over a 6- and 8-week period, respectively. Harrison and Bourke (15) found significant improvements in CT, jump height, starting strength, and 5-m sprint time after 6 weeks of RS training when compared with a control group. Comyns et al. (7) and Harrison and Bourke (15) found that when using RM-ANOVA analysis, the data may show increases in variability between subjects at any given time point, and this variability could mask the differences between pretest and posttest measures. The RM-ANOVA analysis comparing pretest means with maximum and minimum posttest means used in this study indicated statistically significant differences between pretest and posttest means across most of the variables measured; however, individual typical error analysis seemed to contradict the results of the RM-ANOVA analysis. Typical error analysis found no consistent pattern within or across individuals for the occurrences of fatigue or PAP. Inspection of the group data using typical error analysis (Table 1) also showed relatively few fatigue or PAP events in any of the variables examined and more importantly, the number of fatigue-PAP response sequences was lower still. On balance, the RM-ANOVA method has inherent weaknesses in analyzing data from this type of investigation for 2 reasons. First, it does not take account of the biological variability of the subjects’ pretest scores. Second, it found significant differences between the pretest and posttest minimum and maximum means when closer examination showed that few, if any, subjects demonstrated the typical fatigue-PAP sequences on any of the variables examined. It does not make sense for an analysis to generate a statistically significant pattern of differences in the mean scores, suggesting the existence of a fatigue-PAP phenomenon, when very few subjects exhibit this pattern in their responses. Based on the typical error analysis, the results provide little evidence to support the notion that RS causes a PAP
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response during recovery. Considering individual incidents of fatigue and PAP, there seemed to be no consistent time or step where fatigue and PAP occurred for any of the participants. All of the variables analyzed showed results that were random and not consistent with the literature. Because PAP is assumed to coexist with fatigue (2), it may be that the pre-load RS activity using 30% body mass load was not sufficient to cause a fatigue effect, and without sufficient fatigue, the PAP response was unlikely to occur. Despite this, the 30% load is relatively high for this type of training activity, and it has been shown in RS training studies that heavier sled loads may induce detrimental effects on the movement patterns (1,24). The literature on complex training suggests that PAP responses are more likely to occur after highintensity exercises (6,7) and in highly trained athletes (3). The participant group in this study were active and participated in training at least 3 times a week but could not be described as highly trained participants. Therefore, the low training status may be a factor limiting PAP responses, but this does not explain the contradictory results of the different methods of analysis. Further investigation of fatigue-PAP in contrast and complex training using typical error analysis is recommended because this could verify whether the positive findings of PAP responses to complex training were an artifact of the analysis methods used. Clearly, the design and analysis methods used on training studies such as this are critically important. Simple pretest posttest designs with analysis using RM-ANOVA seem to have limitations in reliably detecting changes arising from fatigue or PAP because they may not account for biological variance within individuals or changes in performance that could be due to practice effects.
PRACTICAL APPLICATIONS The results of this study show no evidence of fatigue-PAP as an acute response to RS training. The results also indicate that typical error analysis may be used to identify acute fatigue-PAP sequences in RS training. Coaches and athletes may use this form of analysis to determine acute fatigue-PAP responses in training using repeated measures of performance in a nonfatigued state to determine the mean and normal biological variation in performance. Acute training adaptations may then be evaluated as performances that lie outside the typical range of variation using the mean 1.5 3 SDwithin-subject. This methodology could be used to identify fatigue and PAP events on an individual basis.
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Resisted Sprinting Effects on Sprint Performance 3. Chiu, LZE, Fry, AC, Weiss, LW, Schillingeiss, BK, Brown, LE, and Smith, SL. Postactivation potentiation response in athletic and recreationally trained individuals. J Strength Cond Res 17: 671–677, 2003.
18. Hrysomallis, C. The effectiveness of resisted movement training on sprinting and jumping performance. J Strength Cond Res 26: 299– 306, 2012.
4. Clark, KP, Stearne, DJ, Walts, CT, and Miller, AD. The longitudinal effects of resisted sprint training using weighted sleds vs. weighted vests. J Strength Cond Res 24: 3287–3295, 2010.
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22. Linthorne, NP, James, E, and Cooper, JE. Effect of the coefficient of friction of a running surface on sprint time in a sled-towing exercise. Sport Biom 12: 175–185, 2013. 23. Lockie, RG, Murphy, AJ, Schultz, AB, Knight, TJ, Xanne, AK, and de Jonge, J. The effects of different speed training protocols on sprint acceleration kinematics and muscle strength and power in field sports. J Strength Cond Res 26:1539– 1550, 2012. 24. Lockie, RG, Murphy, AJ, and Spinks, CD. Effects of resisted sled towing on sprint kinematics in field-sport athletes. J Strength Cond Res 17: 760–767, 2003. 25. McBride, JM, Nimphius, S, and Erickson, TM. The acute effects of heavy-load squats and loaded countermovement jumps on sprint performance. J Strength Cond Res 19: 893–897, 2005. 26. Okkonen, O and Ha¨kkinen, K. Biomechanical comparison between sprint start, sled pulling and selected squat type exercises. J Strength Cond Res 27: 2662–2673, 2013. 27. Spinks, CD, Murphy, AJ, Spinks, WL, and Lockie, RG. The effects of resisted sprint training on acceleration performance and kinematics in soccer, rugby union, and Australian football players. J Strength Cond Res 21: 77–85, 2007. 28. Upton, DE. The effects of assisted and resisted sprint training on acceleration and velocity in division IA female soccer athletes. J Strength Cond Res 25: 2645–2652, 2011.
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30. Yetter, M and Moir, GL. The acute effects of heavy back and front squats on speed during forty-meter sprint trials. J Strength Cond Res 22: 159–165, 2008.
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AND
ANDREW J. HARRISON
Biomechanics Research Unit, University of Limerick, Limerick, Ireland ABSTRACT
INTRODUCTION
Whelan, N, O’Regan, C, and Harrison, AJ. Resisted sprints do not acutely enhance sprinting performance. J Strength Cond Res 28(7): 1858–1866, 2014—Sprinting speed is a vital component of successful performance in many sports. Long-term resisted sprint training has been shown to improve early acceleration performance, but the acute post-activation potentiation (PAP) effects of resisted sprinting on subsequent performance remain unclear. The purpose of this investigation was to examine the effects of resisted sprinting on sprinting and factors related to sprint performance. Twelve active males participated in a pretest involving ten 10-m sprints through dual-beam timing gates and 10-m Optojump Next System with full recovery. This provided baseline data on step rate, step length, ground contact time, and running speed over the first 6 steps of a maximum effort sprint. One week later, the participants performed three 10-m resisted sprints using a sled loaded to 25–30% body mass followed by a 10-m sprint at 1, 2, 4, 6, 8, and 10 minutes after the final resisted sprint. The data were analyzed using an adapted typical error analysis and repeated measures analysis of variance. The results using analysis of variance provided evidence of significant initial fatigue followed by the enhancement of mean step rate, contact time, reactive strength index, and running speed in 10-m sprints performed after the resisted sprinting (p . 0.05). By contrast, the typical error analysis showed that this enhancement was limited and unsystematic in nature with little clear evidence of fatigue followed by potentiation. The results using typical error data do not provide strong evidence of PAP in 10-m sprint performance after resisted sprinting.
KEY WORDS resisted running, reactive strength index, ground contact time, typical errors, post-activation potentiation
Address correspondence to Dr. Andrew J. Harrison, drew.harrison@ul. ie. 28(7)/1858–1866 Journal of Strength and Conditioning Research Ó 2014 National Strength and Conditioning Association
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printing speed is a characteristic that is vital to successful performance in many sports (4,18). The initial acceleration phase of sprinting (from 0 to 10 m) is probably the most important phase in team sports (13). An athlete’s ability to accelerate can depend on their running kinematics and their capacity for force production (10). The kinematic parameters that determine acceleration and velocity include: step length (SL), step frequency (SF), ground contact time (CT), and flight time (23). Resisted sprints (RS) training methods using towing devices, sleds, and weighted vests have been shown to improve early acceleration phase sprinting performance when implemented over a sustained period, whereas complex training/contrast training methods have been shown to induce acute improvements in sprint performance (2). Complex training involves the combination of a heavily loaded exercise followed by a biomechanically similar plyometric exercise (29). It is based on the phenomenon of post-activation potentiation (PAP), which can be considered either from a physiological perspective or with respect to physical performance (i.e., running faster or jumping higher). Post-activation potentiation can present as an acute enhancement of performance or an enhancement of factors influencing performance after a preload stimulus. Generally, this PAP effect appears as a sequence of performance decrement due to acute fatigue followed by enhanced performance (6,7). No study to date has examined whether RS training can produce an acute PAP effect on sprint performance. Several studies have examined the acute and chronic effects of RS on kinematics (1,9,10,18,24) and kinetics (20,25). The literature shows that the load used in RS training has varied considerably across studies and no criterion for optimal loading has been established for longitudinal or acute studies. Lockie et al. (24) suggested that for optimal long-term training effects, the resistance load should decrease sprint velocity during RS by no more than 10%, and this recommendation has since been used in studies by Alcaraz et al. (1) and Clark et al. (4). The resistance load on RS training studies has ranged from 10 to 30% of the body mass (1,4,9,15,24,26,28). Recently, Linthorne et al. (22) examined the effect of the coefficient of friction on sprinting while towing a weighted sled across various
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Figure 1. Effects of resisted sprinting on step length across the first 6 steps in the sprint (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
surfaces and recommended a trial-and-error approach to find the most appropriate sled weight for an athlete to use on any given running surface. No study to date has established an optimal sled load for RS that may cause an acute PAP effect after RS; however, from complex training studies, it is known that heavy resistances in the preload activity (i.e., .90% of a single repetition maximum) are usually required to cause a PAP response (7). Although a significant amount of research exists on RS and PAP; research is limited on whether RS can provide an acute enhancement of sprint performance. Crewther et al. (8) suggested that PAP responses may depend on the specificity of the movement pattern in the preload exercise, therefore RS could have a potentiating effect on sprint performance because the movement pattern of RS is similar to sprinting and may have greater specificity than weighted
squats. RS is often used by athletes as a form of contrast training where sled resisted sprinting is followed by free sprinting with an expectation that the free sprint performance will be improved after RS. Such acute enhancements could be beneficial to athletes as a means of improving competition or training performance. Despite the widespread practice of this form of contrast training, no research to date has examined whether RS can induce a PAP response or a classic fatigue-potentiation sequence. There is a clear need to evaluate whether RS using sled towing generates a potentiation effect on sprint performance during recovery and examine whether there are specific changes in the factors that determine sprint performance such as SL, SF, and CT. Therefore, the aim of this study was to investigate the acute PAP effect of sled training on sprint performance– related factors including SF, SL, CT, and reactive strength VOLUME 28 | NUMBER 7 | JULY 2014 |
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Resisted Sprinting Effects on Sprint Performance
Figure 2. Effects of resisted sprinting on step rate across first the 6 steps in the sprint, (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
index (RSI). In addition, a comparison is made between typical error analysis and repeated measures analysis of variance (RM-ANOVA) methodologies and their suitability for correctly identifying PAP responses in sprint biomechanics.
METHODS Experimental Approach to the Problem
The investigation used a simple pretest posttest design and required the participants to complete testing on 2 separate days. On the first day, the participants completed a standard warm-up, which included a 3-minute jog, various shortduration stretches of the lower limb followed by some sprint specific dynamic exercises. This was followed by 10 3 10 m sprints at maximum effort with a 2-minute recovery between each run. Data obtained in these sprints were used to deter-
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mine the pretest means and typical error thresholds for sprint time, CT, RSI, and velocity in the first 6 steps of the sprint. One week later, the participants completed a standard warm–up, and 3 sled pulls over 10 m with a load of 25–30% of body mass with 90 seconds recovery between each resisted run. The participants then performed maximum effort unresisted sprints at 1, 2, 4, 6, 8, and 10 minutes after the third sled pull. The sprint times, CT, RSI, and velocity for the first 6 steps were compared with the pretest scores using both RM-ANOVA and typical error analysis. Subjects
Twelve (n = 12) physically active men aged 22.5 6 3.9 years, age range 19 to 35 years, (mean 6 SD), mass 74 6 5.9 kg, height 1.77 6 0.05 m, participated in this study. All participants were injury free and had completed at least 3 training
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Figure 3. Effects of resisted sprinting on ground contact time across the first 6 steps in the sprint (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05).
sessions per week in team sports or individual sports such as: hurling, Gaelic football, soccer, athletics, rowing, and triathlon in the 3 months weeks before testing. Participants were excluded from the study if they had previously suffered a lower limb injury in the 3 months before the testing. Ethical approval for the study was granted from the university research ethics committee, and written consent was obtained from all participants. Before taking part in the study, all participants completed a physical activity questionnaire and provided informed consent in writing. For the duration of the testing session, the participants wore their own shorts, t-shirt, and running shoes. Instrumentation
All testing took place on an indoor synthetic track surface and was completed over a period of 2 days. Sprint times over
5 and 10 m were recorded using Racetime 2, dual-beam timing gates (Microgate, Bolzano, Italy). Additional temporal event variables during sprinting were recorded using the Optojump Next system (Microgate, Bolzano, Italy). The timing gates and 10 m of Optojump Next system rails were set up to record times and footfall events during the 10 m sprint. The timing gates were placed at the beginning of the Optojump lane (0 m) and at 5 m and 10 m from the start, and both systems were electronically synchronized so that the Optojump began recording data when the first timing the gate beam was broken. Participants started each sprint from a standard 2 point (standing) starting position with their front foot placed behind a line 70 cm behind the first set of timing gates thus ensuring that they did not trigger the timing gates before the start of each sprint. VOLUME 28 | NUMBER 7 | JULY 2014 |
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Resisted Sprinting Effects on Sprint Performance
Figure 4. Effects of resisted sprinting on reactive strength index across the first 6 steps in the sprint (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
Two sled devices weighing 3.7 kg and 4.3 kg were used; mass was added to the sled in increments of 2.5 kg. The total sled mass for each participant was adjusted to approximately 25–30% of the body mass (to the nearest 2.5 kg); this mass also included the mass of the sled. The sled was attached to the participant with a shoulder harness and nonelastic rope. The 25–30% body mass load was chosen because this was near the upper limit of resistance used in sled resistance running studies and evidence from complex training studies indicated that higher resistance loads are normally required to cause a PAP response (7). Testing Procedures
Standardized Warm-up. All participants performed a standard warm-up consisting of 3 minutes of low-intensity jogging short-duration static stretching that included 1 exercise for
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each lower limb muscles (hamstrings, quadriceps, and calf muscles), which were held for 10 seconds and repeated 3 times. Participants then performed 2 sets of sprint-specific drills including: an “A march,” an “A skip,” a power skip over 10 m, and a wall drive exercise. They also completed three 10-m runs at approximately 50, 75, and 100% effort. Pretest. The first session (pretest) began with the standard warm-up outlined above. The participant then performed 10 maximum effort sprinting trials over a distance of 10 m with 2 minutes of recovery between each run. Participants were instructed to begin each sprint from a standing start position and to sprint as fast as they could past the 10-m timing gate. It was emphasized to them that they should run straight through the 10-m mark and not to slow down before it.
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Figure 5. Effects of resisted sprinting on running speed across the first 6 steps in the sprint (A to F, respectively). * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
They were also instructed to avoid any rocking or forward movements before starting each trial. Sled Towing Intervention. In this session, the same warm-up procedures were used. Additionally, 3 sled pulls over 10 m with 90 seconds of recovery between each sled pull were completed before the running trials. The participant was required to perform each 10-m sled pull at maximum effort. The same track surface and the same lane were used for this session, and the participants were instructed to wear the same type of clothing and footwear as in the previous testing session. Posttest. One minute after the final sled pull, the participant performed the first unloaded run through the Optojump and
timing gates, and again at 2, 4, 6, 8, and 10 minutes after the last sled pull. Statistical Analyses
The data were analyzed using both RM-ANOVA and typical error analysis procedures. The RM-ANOVA was used to determine significant differences between the pretest mean and the posttest minimum and maximum mean scores. The maximum and minimum posttest scores were therefore compared with each subject’s mean of the 10 pretest trials. Typical error analysis was used to determine the pretest and posttest differences on an individual basis. This involved calculating the mean and within-subject standard deviation (SDwithin-subject) of the 10 pre-test trials to establish the upper and lower limits of variation. Using the recommendations of Hopkins (16,17), a potentiation event was defined as an VOLUME 28 | NUMBER 7 | JULY 2014 |
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Resisted Sprinting Effects on Sprint Performance
Figure 6. Effects of resisted sprinting on running speed through the timing gates at 0–5 m; 5–10 m, and 0–10 m. * denotes a “fatigue effect”: i.e., significant difference between pretest and posttest minimum mean scores (p # 0.05). # denotes a “post-activation potentiation effect”: i.e., significant difference between pretest and posttest maximum mean scores (p # 0.05).
improvement in a parameter of 1.5 3 SDwithin-subject relative to the mean score. Similarly, a fatigue event was defined as a worsening of a parameter by 1.5 3 SDwithin-subject relative to the mean score. In cases where an improvement in performance was indicated by a lower score (e.g., CT), a PAP event was represented by a score lower than typical error lower threshold. Using the typical error analysis, it was possible to identify the number of fatigue and potentiation events and fatigue-potentiation sequences that occurred on an individual subject and group basis.
TABLE 1. Analysis of potentiation and fatigue events and fatigue-potentiation patterns using typical error comparisons on Optojump Next data.* Variable
N
%
CT
39 28 2 39 62 7 48 7 0 45 57 7 67 31 1
9.0 6.48 2.8 9.0 14.4 9.8 11.1 1.6 0 10.4 13.2 9.7 15.5 7.2 1.4
Fatigue events PAP events Fatigue-PAP sequences RSI Fatigue events PAP events Fatigue-PAP sequences Velocity Fatigue events PAP events Fatigue-PAP sequences Stride length Fatigue events PAP events Fatigue-PAP sequences Step rate Fatigue events PAP events Fatigue-PAP sequences
*CT = ground contact time; RSI = reactive strength index; AP = post-activation potentiation.
RESULTS The results of the RM-ANOVA comparing group means for pretest with the minimum and maximum mean scores for SL, step rate, velocity, CT, and RSI for each of the first 6 steps during the posttest sprints are presented in Figure 1–5. These data show statistically significant improvements between the pretest and posttest maximum scores for all dependent variables. This analysis suggests the existence of both fatigue and PAP in the dependent variables in the posttest period. The results of the RM-ANOVA comparing group means for pretest with the minimum and maximum mean scores for average velocities through timing gates at 0–5 m, 5–10 m, and 0–10 m are shown in Figure 6. The results indicate significant reductions in running speed but no significant increases through 0–5 m, 5–10 m, or 0–10 m compared with pretest mean velocities. The results of the comparison of pretest and posttest scores in CT, RSI, velocity, SL, and step rate using typical error analysis to identify potentiation and fatigue events as well as fatigue-potentiation sequences during the first 6 steps of the sprint tests using the Optojump Next data are presented in Table 1. The results show only a small percentage of potentiation and fatigue events in relation to the total number of measures for CT, RSI, velocity, SL, and step rate. Of particular interest are the very small percentages of fatigue-potentiation sequences for each variable (velocity = 0%, step rate = 1.4%, and CT = 2.8%). The typical error analysis of average velocities determined using the optical timing gates found no evidence of fatigue or potentiation events.
DISCUSSION The RM-ANOVA results in Figure 1–5 seem to show patterns of fatigue and PAP which are similar to those found in
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Journal of Strength and Conditioning Research other studies where PAP effects were investigated (2,8,29,30). None of these studies investigated acute fatigue or PAP effects resulting from RS; however, the coexistence of fatigue and PAP during recovery and the pattern of fatigue followed by PAP is typical of several complex and contrast training studies (2,5,6,7,14,21). Several studies have suggested that PAP responses vary considerably between individuals and can be dependent on factors such as training age, intensity of the pre-load activity, and duration of the recovery period (3,6,11,12,19). The comparison of mean velocity through the timing gates in Figure 6 indicated significant fatigue effects for average velocities at 0–5 m, 5–10 m, and 0–10 m compared with pretest velocities. These data suggest that the RS induced fatigue related reductions in running speed over the first 10 m but no significant PAP effects were found on overall sprint performance. This is consistent with the findings of other studies examining PAP effects, which showed no significant PAP on overall performance measures but significant PAP effects on factors related to performance such as CT and RSI, (5,7). Harrison and Bourke (15) and Spinks et al. (27) examined RS training effects over a 6- and 8-week period, respectively. Harrison and Bourke (15) found significant improvements in CT, jump height, starting strength, and 5-m sprint time after 6 weeks of RS training when compared with a control group. Comyns et al. (7) and Harrison and Bourke (15) found that when using RM-ANOVA analysis, the data may show increases in variability between subjects at any given time point, and this variability could mask the differences between pretest and posttest measures. The RM-ANOVA analysis comparing pretest means with maximum and minimum posttest means used in this study indicated statistically significant differences between pretest and posttest means across most of the variables measured; however, individual typical error analysis seemed to contradict the results of the RM-ANOVA analysis. Typical error analysis found no consistent pattern within or across individuals for the occurrences of fatigue or PAP. Inspection of the group data using typical error analysis (Table 1) also showed relatively few fatigue or PAP events in any of the variables examined and more importantly, the number of fatigue-PAP response sequences was lower still. On balance, the RM-ANOVA method has inherent weaknesses in analyzing data from this type of investigation for 2 reasons. First, it does not take account of the biological variability of the subjects’ pretest scores. Second, it found significant differences between the pretest and posttest minimum and maximum means when closer examination showed that few, if any, subjects demonstrated the typical fatigue-PAP sequences on any of the variables examined. It does not make sense for an analysis to generate a statistically significant pattern of differences in the mean scores, suggesting the existence of a fatigue-PAP phenomenon, when very few subjects exhibit this pattern in their responses. Based on the typical error analysis, the results provide little evidence to support the notion that RS causes a PAP
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response during recovery. Considering individual incidents of fatigue and PAP, there seemed to be no consistent time or step where fatigue and PAP occurred for any of the participants. All of the variables analyzed showed results that were random and not consistent with the literature. Because PAP is assumed to coexist with fatigue (2), it may be that the pre-load RS activity using 30% body mass load was not sufficient to cause a fatigue effect, and without sufficient fatigue, the PAP response was unlikely to occur. Despite this, the 30% load is relatively high for this type of training activity, and it has been shown in RS training studies that heavier sled loads may induce detrimental effects on the movement patterns (1,24). The literature on complex training suggests that PAP responses are more likely to occur after highintensity exercises (6,7) and in highly trained athletes (3). The participant group in this study were active and participated in training at least 3 times a week but could not be described as highly trained participants. Therefore, the low training status may be a factor limiting PAP responses, but this does not explain the contradictory results of the different methods of analysis. Further investigation of fatigue-PAP in contrast and complex training using typical error analysis is recommended because this could verify whether the positive findings of PAP responses to complex training were an artifact of the analysis methods used. Clearly, the design and analysis methods used on training studies such as this are critically important. Simple pretest posttest designs with analysis using RM-ANOVA seem to have limitations in reliably detecting changes arising from fatigue or PAP because they may not account for biological variance within individuals or changes in performance that could be due to practice effects.
PRACTICAL APPLICATIONS The results of this study show no evidence of fatigue-PAP as an acute response to RS training. The results also indicate that typical error analysis may be used to identify acute fatigue-PAP sequences in RS training. Coaches and athletes may use this form of analysis to determine acute fatigue-PAP responses in training using repeated measures of performance in a nonfatigued state to determine the mean and normal biological variation in performance. Acute training adaptations may then be evaluated as performances that lie outside the typical range of variation using the mean 1.5 3 SDwithin-subject. This methodology could be used to identify fatigue and PAP events on an individual basis.
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