The preparation of athletes in collision sports, such

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1 DO FORCE TIME AND POWER TIME MEASURES IN A LOADED JUMP SQUAT DIFFERENTIATE BETWEEN SPEED PERFORMANCE AND PLAYING LEVEL IN ELITE AND ELITE JUNIOR RUGBY UNION PLAYERS? KEIR T. HANSEN, 1,2 JOHN B. CRONIN, 1,3 STUART L. PICKERING, 2 AND LEE DOUGLAS 4 1 School of Exercise, Biomedical and Health Sciences, Edith Cowan University, Joondalup, Western Australia; 2 Worcester Rugby Football Club, Sixways Stadium, Worcester, United Kingdom; 3 Sport Performance Research Institute New Zealand, AUT University, Auckland, New Zealand; and 4 Edinburgh Rugby, Scottish Rugby Union, Murrayfield Stadium, Edinburgh, United Kingdom ABSTRACT Hansen, KT, Cronin, JB, Pickering, SL, and Douglas, L. Do force time and power time measures in a loaded jump squat differentiate between speed performance and playing level in elite and elite junior rugby union players? J Strength Cond Res 25(x): , 2011 The purpose of this study was to investigate discriminative ability of rebound jump squat force time and power time measures in differentiating speed performance and competition level in elite and elite junior rugby union players. Forty professional rugby union players performed 3 reboundjumpsquatswithanexternalloadof40kgfromwhich a number of force time and power time variables were acquired and analyzed. Additionally, players performed 3 sprints over 30 m with timing gates at 5, 10, and 30 m. Significant differences (p, 0.05) between fastest 20 and slowest 20 athletes, and elite (n = 25) and elite junior (n = 15) players in speed and force time and power time variables were determined using independent sample t-tests. The fastest and slowest sprinters over 10 m differed in peak power (PP) expressed relative to body weight. Over 30 m, re were significant differences in peak velocity and relative PP and rate of power development. There was no significant difference in speed over any distance between elite and elite junior rugby union players; however, a number of force and power variables including peak force, PP, force at 100 milliseconds from minimum force, and force and impulse 200 milliseconds from minimum force were significantly (p, 0.05) different between playing levels. Although only power values expressed relative to body weight were able to differentiate speed performance, both absolute and relative force and power values Address correspondence to Keir Hansen, keir.hansen@warriors.co.uk. 0(0)/1 10 Journal of Strength and Conditioning Research Ó 2011 National Strength and Conditioning Association differentiated playing levels in professional rugby union players. For speed development in rugby union players, training strategies should aim to optimize athlete s power to weight ratio, and lower body resistance training should focus on movement velocity. For player development to transition elite junior players to elite status, adding lean mass is likely to be most beneficial. KEY WORDS force, power, rugby union INTRODUCTION The preparation of athletes in collision sports, such as rugby union, rugby league, and American football, traditionally involves a large strength and power training component. Effective prescription of resistance training programs for athletic performance in se sports refore relies heavily upon accurate assessment of strength and power qualities. This assessment process has recently been termed strength diagnosis (32). The assessment of strength and power, or strength diagnosis, quantifies importance of a given strength quality to an athletic activity, identifies deficiencies in muscular function, monitors training interventions, and aids in identification of individual talent in a given athletic endeavor (1). Currently, most common method of assessment of closed chain, multijoint lower limb strength, and power uses isoinertial dynamometry (22,30,31), although use of both isometric (37) and isokinetic (38) dynamometry is also documented. Despite current popularity of isoinertial dynamometry, best measures for assessing force, velocity and power qualities of performance during isoinertial lower body movements remain unclear. Measures commonly used include peak and mean force (8,13,39), peak velocity (PV [22,26]), and peak and mean power (6,9,10,12,22,26,35). Yet validity of some of se measures has been a point of debate in literature (15,27). One shortcoming is that y do not consider temporal aspects of force measurement such as rate of force development (RFD). VOLUME 0 NUMBER 0 MONTH

2 Force Time and Power Time Measures TABLE 1. Mean (6SD) age, height, and weight for elite, elite junior, and all subjects. Group Age (y) Height (m) Weight (kg) Elite (n = 25) Elite junior (n = 15) All subjects (n = 40) Temporal measures are thought to be important to muscular performance for a number of explosive activities. A number of temporal measures of force have been discussed in literature, yet ir ability to differentiate performance levels and track training-induced changes has not been well documented. For example, Tidow (36) suggested that starting strength (force or impulse produced at 30 milliseconds), explosive strength (steepest point on force time curve or maximum RFD), and force or impulse at 100 milliseconds were crucial to performance in explosive tasks. However, rationale for selection of se qualities is not clear. The selection of starting strength as a crucial strength quality seems to be arbitrary (36). Likewise, many of RFD measures discussed by Zatsiorsky and Kraemer (40) (index of explosive strength, reactivity coefficient (RC), starting gradient, and acceleration gradient) have received limited attention in literature when measured using isoinertial dynamometry, and ir application to strength and conditioning practice has not been discussed in literature in any great depth. Finally, rate of power development (RPD) measures have received some limited research attention of late (11,24), but ir reliability and validity and thus ir application for strength and conditioning professional requires furr research. Previous research has attempted to establish discriminative ability of a number of tests of muscular function by differentiating between performance levels in a nominated TABLE 2. Mean (6SD) sprint times for fastest and slowest subjects over 5, 10, and 30 m. Distance Fastest 20 (mean 6 SD) Slowest 20 (mean 6 SD) p Value 5 m (s) m (s) m (s) functional task (5,14,16,19,23). For example, numerous studies have investigated ability of force and power values during jumping movements to differentiate sprinting performance over a variety of distances (5,14,20,23). Yet very few studies have addressed relationship between temporal aspects of force and power and sprinting performance or addressed ability of se temporal measures to differentiate between performance levels. Young et al. (39) investigated relationships between a number of force and force time variables during jumps with and without a countermovement, and speed over 2.5 and 10 m in male and female track and field athletes. They found that peak force (PF), average power, and force at 100 milliseconds all expressed relative to body weight (where absolute force or power value is divided by body weight of athlete) were significantly correlated (r = to 20.86) with 2.5-m speed (from a block start). Force at 100 milliseconds and average power output (both relative to body weight) were also significantly correlated (r = and 20.79, respectively) with 10-m performance. Wilson et al. (37) also investigated relationships between sprint ability in athletes from a variety of team and individual sports, and temporal aspects of force production, in both concentric only and countermovement jumps, and isometric contractions. In this study, only variable to correlate significantly with sprint performance (30 m) was force at 30 milliseconds in a concentric only jump squat (r = ). Unfortunately, both se studies were conducted with relatively small subject populations (15 20 subjects), and reliability of many of measures discussed was eir below what would be deemed acceptable or not stated. Additionally, neir study addressed RPD measures, which also warrant investigation. The ability of tests of strength and power to discriminate between performance levels in specific sports has also interested strength and conditioning researchers (2,3,7,34). For example, Baker (4) found that peak power (PP) in a jump squat with an external load of 20 kg was significantly greater in professional rugby league players than or playing levels. Sheppard et al. (34) reported that PP and relative PP were significantly different between senior elite and elite junior volleyball players. However, re remains little information about efficacy of isoinertial force time and power time values in differentiating performance levels of athletes. The best mode of muscular assessment in collision sports, such as rugby union, which require a combination of both speed and strength, is not well documented. The purpose of this study was to investigate discriminative ability of force time and power time measures, specifically investigating ir ability to differentiate speed performance and competition level in elite and elite junior rugby union players. This will help identify force and power measures, which are determinants of speed (as a key aspect of performance in many collision sports) and playing level, in this population. These measures are likely to be most appropriate for 2 Journal of Strength and Conditioning Research

3 TABLE 3. Mean (6SD) force variables and p values for fastest 20 and slowest 20 players over 5, 10, and 30 m.* 5m 10m 30m Measure 5 m Fast 5 m Slow p Value 10 m Fast 10 m Slow p Value 30 m Fast 30 m Slow p Value VOLUME 0 NUMBER 0 MONTH PF (N) 2, , , , , , PF/BW (Nkg) EC TTPF (ms) CO TTPF (ms) EC RFD-MA (Ns) 9, ,118 9, , , ,042 8, , , ,396 8, , Rel EC RFD-MA (Nskg) EC RC (Nskg) EC-FA30 ms (N) Rel EC-FA30 ms (Nkg) EC-FA100 ms (N) 1, , , , , , Rel EC-FA100 ms (Nkg) EC-FA200 ms (N) 1, , , , , Rel EC-FA200 ms (Nkg) CO-FA30 ms (N) 1, , , , , , Rel CO-FA30 ms (Nkg) CO-FA100 ms (N) 2, , , , , , Rel CO-FA100 ms (Nkg) EC-I30 ms (Ns) EC-I100 ms (Ns) EC-I200 ms (Ns) CO-I30 ms (N) CO-I100 ms (N) *Rel = relative to body weight; EC = eccentric concentric; CO = concentric only; PF = peak force; TTPF = time-to-peak force; RFD-MA = rate of force development calculated with a moving average; RC = reactivity coefficient; FA = force at; I = impulse. Significant difference between fast and slow groups. Journal of Strength and Conditioning Research

4 4 Journal of Strength and Conditioning Research TABLE 4. Mean (6SD) power and velocity variables and p values for top 20 and bottom 20 players over 5, 10, and 30 m.* 5m 10m 30m Force Time and Power Time Measures Measure Fastest Slowest p Value Fastest Slowest p Value Fastest Slowest p Value PP (W) 4, , , , , , Rel PP (Wkg) PV (m s 21 ) EC TTPP (ms) EC TTPV (ms) EC RPD-MA (Ws) 17, ,380 17, , ,389 17, , , ,466 16, , Rel EC RPD-MA (Wskg) EC RC (Wskg) *Rel = relative to body weight; EC = eccentric concentric; PP = peak power; PV = peak velocity; TTPP = time to peak power; TTPV = time to peak velocity; RPD-MA = rate of power development calculated with a moving average; RC = reactivity coefficient. Significant difference between fast and slow groups.

5 Journal of Strength and Conditioning Research TABLE 5. Mean (6SD) sprint times for elite and elite junior subjects over 5, 10, and 30 m. Distance assessment of force and power capabilities in collision sports and key foci in programming for performance enhancement. METHODS Elite (mean 6 SD) Elite junior (mean 6 SD) p Value 5 m (s) m (s) m (s) Experimental Approach to Problem Forty full time rugby union players from a professional club performed 3 jump squats with an external load of 40 kg on a portable force plate and 3 maximal sprints over 30 m. Force time and power time curves from jump squats were analyzed for a number of temporal variables and sprint times TABLE 6. Mean (6SD) force variables and p values for elite vs. elite junior players. Measure Elite Elite junior p Value PF (Nkg) 2, , Rel PF (Nkg) EC TTPF (ms) EC RFD-MA (Ns) 10, ,199 6, , Rel EC RFD-MA (Nskg) EC RC (Nskg) EC-FA30 ms (N) Rel EC-FA30 ms (Nkg) EC-FA100 ms (N) 1, Rel EC-FA100 ms (Nkg) EC-FA200 ms (N) 1, , Rel EC-FA200 ms (Nkg) CO-FA30 ms (N) 2, , Rel CO-FA30 ms (Nkg) CO-FA100 ms (N) 2, , Rel CO-FA100 ms (Nkg) EC-I30 ms (Ns) EC-I100 ms (Ns) EC-I200 ms (Ns) CO-I30 ms (Ns) CO-I100 ms (Ns) *Rel = relative to body weight; EC = eccentric concentric; CO = concentric only; PF = peak force; TTPF = time to peak force; RFD-MA = rate of force development calculated with a moving average; RC = reactivity coefficient; FA = force at, I = impulse. Significant difference between elite and elite junior groups. were recorded from a standing start over 5, 10, and 30 m. Subsequently, group s force time and power time variables were analyzed in 2 ways to ascertain ability of se variables to differentiate performance level in group. Firstly, subjects were ranked from 1 to 40 in speed performance for each of 3 sprint distances investigated. An independent sample t-test was n used to investigate if re were significant differences between fastest 20 and slowest 20 players over each distance in jump squat force time and power time variables. Secondly, group was divided based on ir playing levels using methods similar to those reported by Baker and Newton (7). This involved players being classed as elite or elite junior based on ir playing level. Those who played in first team (premiership squad) were categorized as elite, and those in academy squad yet to play first team rugby were categorized as elite junior. An independent sample t-test was used to investigate if re were significant differences between 2 playing levels in jump squat force time and power time performance and speed performance. Subjects Forty male elite and elite junior rugby union players, between 18 and 34 years of age, volunteered to participate in this study. Mean age, height, and body mass for elite group and elite junior group toger with pooled data for all subjects can be observed from Table 1. All elite subjects had a strength training background of.5 years and thus are described as highly trained using definitions of Rhea (33). All elite junior subjects had a strength training history of between 2 and 5 years and thus can be described as recreationally trained using aforementioned definition system. Testing was conducted as part of subjects preseason strength and conditioning program. All subjects were informed of risks and benefits of participation in research and signed informed consent forms. Procedures were approved by institutional Human Research Ethics Committee. Procedures Subjects attended 2 testing sessions 48 hours apart. Both sessions were performed at VOLUME 0 NUMBER 0 MONTH

6 Force Time and Power Time Measures TABLE 7. Mean (6SD) power and velocity variables and p values for elite vs. elite junior subjects. Measure Elite Elite junior p Value PP (W) 4, , Rel PP (W.kg) PV (ms 21 ) EC TTPP (ms) EC TTPV (ms) EC RPD-MA (Ws) 19, ,212 15, Rel EC RPD-MA (Wskg) EC RC (Wskg) Rel = relative to body weight; EC = eccentric concentric; PP = peak power; PV = peak velocity; TTPP = time to peak power; TTPV = time to peak velocity; RPD-MA = rate of power development calculated with a moving average; RC = reactivity coefficient. Significant difference between elite and elite junior groups. same time of day and were first exercise bout of day. No high exertion training was performed between sessions, but some low-intensity rugby skills training was undertaken by all subjects. Sprint Testing. On day 1 of testing, subjects performed a standardized warm-up consisting of sprint technique drills, dynamic stretching, and submaximal sprints, which lasted approximately 20 minutes. They n performed 3 maximal sprints over 30 m. Sprint times over 5, 10, and 30 m were measured using electronic timing gates (Smart Speed, Fusion Sport, Queensland, Australia). These sprint distances were chosen because y are common in rugby union (18). The Smart Speed timing light system is a double beam modulated visible red-light system with polarizing filters and consists of 4 sets of gates. Athletes started in a 2-point crouched position with left toe 30 cm back from starting line and right toe approximately in line with heel of left foot. All sprints were performed on an indoor rubber based artificial training surface, and all subjects wore rubber-soled track shoes. Approximately 4 minutes of rest was allowed between sprints. The 2 best times for each distance were averaged and used for analysis. Jump Squat Testing. In session 2, after a standardized warm-up, each subject performed 3 jump squats with an external load of 40 kg using a methodology similar to that described by Hori et al. (22). This involved subjects standing at a self selected foot width with an Olympic bar placed on ir upper trapezius immediately below C7. The subject n performed a countermovement to a self-selected depth and immediately performed a maximal jump. Subjects were instructed to keep depth of countermovement consistent between jumps and jump for maximum height on each repetition. All subjects were familiar with jump squat 6 Journal of Strength and Conditioning Research movement because y previously performed it as part of both training and testing programs. All jumps were performed on a portable force plate (Accupower, AMTI, Watertown, MA, USA). Ground reaction force (GRF) data were sampled at 500 Hz via an analog to digital converter (16-Bit, 250 kss 21 National Instruments, Austin, TX, USA.) and collected by a laptop computer using custom-built data acquisition and analysis software (Labview 8.2, National Instruments). Force Time Analysis. From resultant vertical GRF data, PF and time to peak force (TTPF) were determined. Subsequently, a number of force time variables were calculated with analysis commencing at lowest point on force time curve encompassing latter portion of eccentric phase and concentric phase of movement (8). The PF and TTPF were used to calculate RC using formulae of Zatsiorsky and Kraemer (40) (RC = PF/[TTPF 3 Body Mass]). A moving average (MA) was also used to find greatest RFD within a 50-milliseconds interval. This moving average RFD (RFD-MA) was conducted over a window length of 50 milliseconds from start point of analysis until attainment of PF. Impulse was calculated over 30-, 100-, and 200- millisecond time intervals (I30, I100, I200) and absolute force at 30, 100, and 200 milliseconds (FA30, FA100, FA200) from lowest point on force curve (eccentric oncentric [EC]). Additionally, impulse and absolute force variables for concentric phase were also calculated (concentric only [CO]). The concentric phase was defined as starting at lowest point on displacement time curve (8). Both impulse and absolute force were calculated over 30 and 100 milliseconds from start of concentric phase. All force variables were expressed as absolute values and relative to body weight because both approaches have been used previously in literature (37,39). All force-time variables had eir an intraclass correlation coefficient (ICC) of.0.85 or a coefficient of variation (CV) of less than 10% or achieved both of se reliability standards. Power Time Analysis. Power time data were calculated from GRF data using impulse momentum (forwards dynamics) approach to calculate system power as outlined previously in literature (10,17). Because initial velocity of system was zero, at each time point throughout jump, vertical GRF was divided by mass of system to calculate acceleration of system. Acceleration due to

7 Journal of Strength and Conditioning Research gravity was n subtracted so that only acceleration generated by subject was multiplied by time data to calculate instantaneous velocity of systems center of mass. The resultant velocity data were n multiplied by original GRF data to calculate power. From integrated power and velocity data PP, PV, time to PP (TTPP), and time to PV (TTPV) were determined. Additionally, 2 rates of RPD measures were calculated. The calculations were initiated at minimum power encompassing latter portion of eccentric phase and concentric phase of jump. The first variable calculated was RPD using a moving average (RPD-MA), which was calculated over a window length of 50 milliseconds from start point of analysis until PP. The second variable was RC described by Zatsiorsky and Kraemer (40) for force time curve, applied to power time curve (P 2 RC = PP/[TTPP 3 body mass]). As with force time variables, all power variables were expressed as absolute values and relative to body weight because both approaches have been used previously in literature (23). All power-time variables had eir an intraclass correlation coefficient (ICC) of 0.85 or a coefficient of variation (CV) of 10% or achieved both of se reliability standards. Statistical Analyses All statistical analyses for force and power variables were performed on mean of trials 2 and 3 with first trial excluded from analysis (21). Statistical analyses of speed times were performed on mean of 2 fastest trials. Means and SDs were used as measures of centrality and spread of data. The data obtained were analyzed using SPSS statistical software (SPSS 15, Chicago, IL, USA). In first instance, all subjects were ranked from 1 to 40 based on average of ir 2 best sprint times for each distance. An independent sample t-test was n used to ascertain significant differences between groups for force and power variables of interest at each distance. Additionally, independent sample t-tests were conducted between elite group (n = 25) and elite junior group (n = 15), also to ascertain wher se groups differed significantly in force and power variables of interest. An alpha level of 0.05 was used for all statistical comparisons. RESULTS Mean sprint times over 3 distances (5, 10, and 30 m) for fast and slow groups can be observed from Table 2. The difference between 2 groups was significant at all distances (8.2, 8.2, and 8.0% for 5, 10, and 30 m, respectively). Mean values for force variables for fast and slow groups over each distance can be observed from Table 3. The only force time variable to show a significant difference between fast and slow groups was EC I200 where fast group at 10 m was significantly lower (9.1%) than slow group at 10 m. Mean values for power variables for fast and slow groups can be observed from Table 4. Relative PP was significantly greater in 10-m fast group and 30-m fast group (10.8 and 13.9%, respectively). Additionally, PV and relative RPD-MA were significantly greater (7.4 and 24.4%, respectively) in 30-m fast group. Mean sprint times over 3 distances (5, 10, and 30 m) for elite and elite junior groups can be observed from Table 5. There were no significant differences between 2 groups at any of 3 distances. Mean values for force variables for elite and elite junior groups can be observed from Table 6. In terms of absolute values, PF, RFD-MA, EC-FA100, and EC FA200 were all significantly greater (% difference = %) in elite group compared to in elite junior group. In terms of relative values, RFD-MA, EC FA30, and EC FA200 were all significantly different between 2 groups. Relative RFD-MA and FA200 were significantly greater in elite group (34.5 and 19.0%, respectively) compared to in elite junior group. Conversely, relative EC FA30 was significantly greater (25.0%) in elite junior group. Mean values for power variables for elite and elite junior groups can be observed from Table 7. The PP and RPD-MA were significantly greater (12.6 and 21.2%, respectively) in elite group when compared to in elite junior group. DISCUSSION This study aimed to establish discriminative ability of force and power values calculated from force time and power time curve of a loaded rebound jump squat. Specifically, we investigated 2 qualities; ability of se values to differentiate between fastest and slowest sprinters in population of elite rugby union players, and, second, differences in force time and power time parameters between elite and elite junior players. Both absolute and relative force values and absolute power values differentiated playing levels, whereas only power values expressed relative to body weight were able to differentiate speed performance. These are novel findings that have not been published previously with se measures in this population. Our results do not suggest that any force variables expressed as a relative or absolute value are able to differentiate speed performance over any of distances investigated. These findings are similar to or studies that have shown that force variables in a rebound jump squat are not strongly related to speed performance over 30 m in team sport athletes (20,37). The only force variable to be significantly different between fastest and slowest group in this study was I200, which was significantly greater in slow group. Although not statistically significant, a number of force variables were greater in slow group. These results are likely to be a reflection of weight of players in 2 groups with heavier players typically being slower, but because of ir greater mass being able to generate greater absolute force values. A clear strong correlation (r = 0.64) has previously been reported between 30- and 40-m sprint times and body weight in a population of professional rugby union and rugby league players (20) with faster players typically weighing less. This finding may be VOLUME 0 NUMBER 0 MONTH

8 Force Time and Power Time Measures a reflection of body composition of larger players who may carry greater fat mass, although this was not quantified in study of Harris et al. (20) or in this study. The fact that RFD values, even when expressed relative to body weight, were not significantly greater in fast athletes when compared to slow athletes over all sprint distances contradict suggestions of Tidow (36) who postulated that se physical qualities are crucial to athletic performance. This may be related to biomechanical differences between jump squat and sprinting, particularly in acceleration phase of sprint. The literature suggests that a good sprinter is capable of directing GRFs as horizontally as possible (29) in acceleration phase of sprint, whereas a rebound jump squat requires that athlete direct GRFs vertically. Thus, where sprinting is dependent on horizontal impulse, jumping patterns are dependent on vertical impulses. The PP and RPD-MA when expressed relative to body weight and PV were all significantly greater in faster athletes when compared to in slower athletes over 30 m. Additionally, PP relative to body weight was significantly greater over 10 m in fast group. These findings are consistent with previous studies which have reported significant relationships between PP relative to body weight in loaded jump squats and speed performance over similar distances in team sport athletes (5,14,23). The finding that difference in se variables was greatest at 30 m may again be because of movements being functionally more similar over longer distance (10 30 m). That is, as sprint progresses, vertical braking forces during stance phase increase (29), and thus, contribution of stretch shorten cycle (SSC) to sprint performance increases (25). Therefore, a common factor between sprinting (after initial steps) and a rebound jump squat is ability of athlete to use SSC. The most notable difference between 2 movements (sprinting and jumping) being that sprinting requires that resultant force and power must be directed horizontally and jumping requires that y must be directed vertically. These findings have implications for strength and conditioning professional in that relative power, RPD and velocity may be better used to identify talent and monitor training in explosive sports. This also suggests that in sports where running speed is of importance, resistance training should be focused on generating PV, and PP and RPD relative to body mass in training rar than high absolute forces, which has been traditional approach in resistance training for explosive sports. The RPD-MA was only temporal variable able to differentiate fast athletes from slow over any distance. This variable is calculated by conducting a MA over power time curve and thus represents peak RPD over this time period (50 milliseconds). The fact that faster sprinters generated greater values in RPD-MA suggests that unlike force development ability to generate power rapidly or explosively during jumping is functionally similar to ability to generate power and velocity explosively when sprinting. However, it is noteworthy that although RPD-MA was able to differentiate speed performance over 30 m, PP and PV also differentiated speed performance at this distance. Therefore, for practitioner using jump squat to assess lower body muscular function, use of PP and PV which is simpler to calculate and has greater reliability may be sufficient, and calculation of RPD-MA may not be necessary. Noneless, application of RPD-MA to strength and conditioning practice warrants furr investigation. Our results showed no significant difference between elite and elite junior rugby union players in terms of speed performance over 5, 10, and 30 m. Previous research by Baker and Newton (7) reported similar findings in a population of professional rugby league players. Because y are collision sports, it could be argued that momentum is crucial to performance in both rugby union and rugby league and thus ability to generate momentum rar than speed will differentiate performance level. Baker and Newton in aforementioned research reported sprint momentum, calculated by multiplying body mass by average sprint velocity over 10 m. In this quality, re was a significant difference between national level athletes and state level athletes. In this study, elite group was heavier ( kg) than elite junior group ( kg), and thus, it is likely that ir ability to generate momentum would be greater. There were however significant differences between elite and elite junior players in force and power capabilities. Absolute PF plus a number of temporal force variables were found to be significantly greater in elite players. Additionally, absolute PP and RPD-MA were significantly greater in elite group with no significant difference found in relative values. With regards to PP, se findings are consistent with a number of previous studies, which have reported that lower body PP is significantly greater in elite compared to in elite junior athletes (3,7,34). Although a number of force-time values and RPD-MA were significantly different between groups, given that PF and PP were also able to differentiate groups, it may be that as with speed performance, use of se traditional variables is sufficient in strength and power assessment for rugby union and or similar sports. Temporal analysis of force time and power time curves may not be necessary. Although with speed performance only relative values differentiated faster times, absolute values differentiated between elite and elite junior rugby players. This is likely to be principally because of greater mass of elite group when compared to elite junior group. This study did not directly quantify lean mass and fat mass in various groups compared. Noneless, it may be surmised that greater body weight of elite group compared to elite junior group was because of lean mass, leading to greater absolute values in aforementioned measures through an increased ability to generate force. Future research would benefit from quantifying lean mass and fat mass and 8 Journal of Strength and Conditioning Research

9 Journal of Strength and Conditioning Research comparing between groups. From a practical perspective, it can be concluded that, although resistance training for an athlete training for speed should be focused on developing power relative to body mass, a developing rugby union player may be best served to focus on increasing absolute force and power capabilities through increasing lean mass and maximum force production (without compromising speed performance). It should be noted that caution is to be exercised when interpreting se results. In comparing strength and power characteristics between Olympic lifters, power lifters, and sprinters, McBride et al. (28) reported that strength and power profiles reflected training approaches of each group. This being case, fact that absolute force and power values were greater in elite rugby players may simply reflect high training age of se players and strong influence of high resistance training used in rugby union in recent years to increase lean mass and strength in players. Hypotically, should focus shift to a greater emphasis on velocity and relative power in future, physical attributes differentiating elite from elite junior players may also change. PRACTICAL APPLICATIONS One purpose of strength and conditioning assessment is to determine those predictor variables that are fundamental to performance in sport specific tasks, such as sprint ability of rugby union players. For purposes of guiding resistance training prescription and assessing athletic development, it is important for coaches to identify force and power variables crucial to performance. In cohort of rugby union players investigated in this study, PV, and PP and RPD relative to body weight, differentiated fast from slow players. These variables refore can be used by coach to guide programming and track training adaptation during resistance training for speed development. Resistance training programs for speed development should be designed to focus on velocity of movement in training. The mass of player is also a critical consideration given that predictor variables were expressed relative to body weight. Decreasing fat mass will increase power to weight ratio. Accordingly, coach needs to consider ideal anthropometry of players related to ir positional requirements. Anor focus of strength and conditioning assessment is to determine variables that distinguish elite from subelite athletes. This is particularly important in talent identification and serves to focus training prescription around variables that are thought critical to elite performance. For rugby union players used in this study, a number of force and power variables differed significantly between playing levels. These included PF, PP, force at 100 milliseconds from minimum force and force and impulse at 200 milliseconds from minimum force. The additional 6-kg body mass of elite players no doubt affected magnitude of many of se variables and significant differences between groups. When testing and training rugby union players, it would seem most appropriate refore for coach to target absolute force and power measures. For purposes of player development and training strategies for rugby union players to transition to elite status, adding lean mass is likely to be most beneficial. However, given metabolic demands of rugby union, it is likely that this strategy of increasing lean mass is only appropriate to a certain point, which is likely to be position specific. REFERENCES 1. Abernethy, P, Wilson, G, and Logan, P. 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