EFFICACY OF HORIZONTAL JUMPING TASKS AS A METHOD FOR TALENT IDENTIFICATION OF FEMALE RUGBY PLAYERS DANA J. AGAR-NEWMAN1,2

AND

MARC D. KLIMSTRA2

1

School of Exercise Science, Physical & Health Education, Canadian Sports Institute, Performance Services, Victoria, British Columbia, Canada; and 2School of Exercise Science, Physical & Health Education, University of Victoria, Victoria, British Columbia, Canada ABSTRACT Agar-Newman, DJ and Klimstra, MD. Efficacy of horizontal jumping tasks as a method for talent identification of female rugby players. J Strength Cond Res 29(3): 737–743, 2015—The purpose of this study was to explore the relationship between horizontal jumping tasks (standing long jump [SLJ] and standing triple jump [STJ]) and sprint speed (initial sprint speed [ISS] and maximum sprint speed [MSS]) in elite female rugby athletes. Data were collected from provincial, under 20 international fifteens players, in addition to senior sevens international level female rugby athletes (n = 114). Body weight, SLJ, STJ, 10-m sprint speed (ISS), 30- to 40-m sprint speed (MSS), initial sprint momentum, and maximal sprint momentum were analyzed. When categorized by horizontal jumping ability, there was a significant difference in sprint speeds (p , 0.001) between the top 50% and bottom 50% groups. Examining the relationship between horizontal jumping tasks and sprinting speed revealed a stronger correlation in the slowest 50% of athletes compared with the fastest 50%. A linear regression developed from STJ and body weight adequately predicted ISS (r = 0.645, p , 0.001) and MSS (r = 0.761, p , 0.001). In conclusion, horizontal jumping tasks can be used as a valuable performance test to identify differences of sprinting ability in elite female rugby players. However, the relationship between horizontal jumping tasks and sprinting speed seems to decrease in faster athletes. Further, STJ and body weight can be used to predict both ISS and MSS. Based on these data, it is suggested that only STJ be collected when identifying potential sprinting talent in female rugby athletes and caution be used when generalizing results across varying levels of athletes.

KEY WORDS max velocity, acceleration, standing long jump, standing triple jump Address correspondence to Dana J. Agar-Newman, dagar-newman@ csipacific.ca. 29(3)/737–743 Journal of Strength and Conditioning Research Ó 2015 National Strength and Conditioning Association

INTRODUCTION

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ith rugby sevens recent inclusion in the 2016 Olympics, many countries have placed an increased emphasis on the physical development of female rugby sevens athletes. One important physical attribute to develop is sprinting ability, as female sevens athletes have been shown to perform sprints over and around 30 m (22). In other codes of rugby, sprinting ability has been associated with decreased injury risk (8) and tries scored (10). In addition, sprint ability has shown promise for discriminating between positions (7,9,12) and player selection in National Rugby League (11). However, much of the current rugby literature originates from male rugby league and fifteens rugby union. This leaves large gaps in knowledge for strength and conditioning professionals hoping to inform identification, testing, and training for potential female sevens athletes. Although an average measure of speed is a valuable metric, more detailed analysis such as maximum sprint speed (MSS) and initial sprint speed (ISS) over the first 5–10 m may enable a more comprehensive evaluation of athletic ability. Knowledge of these key variables could inform athlete selection, role determination, and exercise prescription for speed development. However, detailed kinematic measures are difficult to ascertain without timely video analysis or expensive and complex equipment. Performance tests commonly collected and evaluated within athletic testing alongside sprint performance are vertical and horizontal jumping. Subsequently, horizontal jumping tasks such as the standing long jump (SLJ) and standing triple jump (STJ) have been used as a proxy for sprint performance due to common performance characteristics (6). These performance characteristics include the coordinated development of lower-body forces while using many of the same muscles involved in sprinting (18,26). Previous studies examining horizontal jumping ability and sprinting speed have been conducted on elite international handball players (5) and college football players (4,21). Specifically, SLJ has been shown to correlate with 9.1, 18.3, and 36.6-m time/speed (4). In addition, STJ had a slightly lower correlation to VOLUME 29 | NUMBER 3 | MARCH 2015 |

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Horizontal Jumping Tasks and Sprint Speed in elite female field-sports athletes. Therefore, the primary TABLE 1. Scale of effect sizes.* purpose of this paper is to determine whether horizontal Trivial Small Moderate Large Very large Nearly perfect Perfect jumping ability is able to differCorrelation 0.0 0.1 0.3 0.5 0.7 0.9 1.0 entiate sprinting ability in Difference in 0.0 0.2 0.6 1.2 2.0 4.0 Infinite female rugby athletes. Furthermeans more, we intend to evaluate *Modified from A Scale of Magnitudes for Effect Statistics (16). Adaptations are themwhether the relationship selves works protected by copyright. So in order to publish this adaptation, authorization must between horizontal jumping be obtained both from the owner of the copyright in the original work and from the owner of tasks and speed changes in fast copyright in the translation or adaptation. and slow athletes and, finally, to determine whether horizontal jumping tasks and basic 0- to 9.1-m time (r = 0.74, p # 0.01) but a higher correlation anthropometric measures are able to predict specific kinematics variables such as ISS and MSS. Based on previous to maximum velocity as assessed by 27.4-–36.6-m interval data from male athletes, and limited data on female athletes, (r = 0.51, p # 0.01) (4). Taken together these results suggest we hypothesize that both SLJ and STJ will have a positive that there may be a differential relationship between the type correlations with ISS and MSS. Furthermore, we hypotheof horizontal jump and the specific sprint performance metsize that SLJ will have stronger correlations to ISS than STJ, ric. In other words, SLJ and STJ may be used to evaluate and STJ will have stronger correlations to MSS than SLJ. separate parameters of sprint performance. Additionally, we hypothesize that as athlete speed increases, Although the majority of studies looking at the relationship STJ will outperform SLJ related to the absolute number of between horizontal jumps and sprint performance are on male steps taken, and the strength of the predictive relationship athletes, only 1 study has examined the relationship between between horizontal jumping task and sprinting ability will horizontal jumping tasks and sprint performance in female decrease related to ceiling effects associated with human athletes. Conducted on adolescent track and field athletes, the physical capacity. study determined that average horizontal power from the SLJ had a very large correlation to the best and average 10-m METHODS sprint time (best: r = 20.89; average: r = 20.87) (20). Although strong correlations between bilateral horizontal Experimental Approach to the Problem jumping tasks and sprinting speed have been reported in Because of the limited research investigating the relationship male athletes, no such data exist to the authors’ knowledge between horizontal jumping tasks and sprinting speed in

TABLE 2. Differences between the top 50% and bottom 50% SLJ groups for anthropometric, horizontal jumping tasks, and sprinting kinematic measures.*†

Anthropometric Body weight (kg) Jumping measures SLJ (m) STJ (m) Sprinting kinematics ISS (m$s21) Initial sprint momentum (kg$m21$s21) MSS (m$s21) Maximal sprint momentum (kg$m21$s21)

Top 50% (n = 57)

Bottom 50% (n = 57)

Bonferroni adjusted p

66.90 6 5.79

67.25 6 7.92

1.000

0.05

Trivial

2.21 6 0.13 6.69 6 0.38

1.91 6 0.10 5.87 6 0.35

,0.001 ,0.001

2.61 2.25

Very large Very large

5.31 6 0.24 355.08 6 32.25

5.09 6 0.29 341.74 6 38.35

,0.001 0.329

0.83 0.38

Moderate Small

7.7 6 0.39 514.98 6 51.48

7.14 6 0.44 478.78 6 52.37

,0.001 0.002

1.35 0.70

Large Moderate

Effect size

Magnitude

*SLJ = standing long jump; STJ = standing triple jump; ISS = initial sprint speed; MSS = maximal sprint speed. †Values are expressed as mean 6 SD. Effect size is expressed as Cohen’s d. The magnitude of effect size was calculated using

Will Hopkins’ scale (16).

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TABLE 3. Differences between the top 50% and bottom 50% standing triple jump groups for anthropometric, horizontal jumping tasks, and sprinting kinematic measures.*†

Anthropometric Body weight (kg) Jumping measures SLJ (m) STJ (m) Sprinting kinematics ISS (m$s21) Initial sprint momentum (kg$m21$s21) MSS (m$s21) Maximal sprint momentum (kg$m21$s21)

Top 50% (n = 57)

Bottom 50% (n = 57)

Bonferroni adjusted p

Effect size

67.07 6 6.26

67.07 6 7.57

1.00

0.00

Trivial

2.20 6 0.14 6.73 6 0.35

1.92 6 0.11 5.84 6 0.32

,0.001 ,0.001

2.24 2.66

Very large Very large

5.36 6 0.22 358.94 6 31.06

5.05 6 0.26 337.88 6 37.57

,0.001 0.010

1.29 0.61

Large Moderate

7.75 6 0.34 519.72 6 50.35

7.08 6 0.39 474.04 6 49.63

,0.001 ,0.001

1.84 0.91

Large Moderate

Magnitude

*SLJ = standing long jump; STJ = standing triple jump; ISS = initial sprint speed; MSS = maximal sprint speed. †Values are expressed as mean 6 SD. Effect size is expressed as Cohen’s d. The magnitude of effect size was calculated using

Will Hopkins’ scale (16).

elite female athletes, a causal-comparative cross-sectional design was used. To evaluate horizontal jumping tasks (SLJ and STJ) capacity to differentiate sprinting ability, horizontal jumping ability was used as the grouping variables, and sprinting speed was the independent behavior. The relationship between sprinting ability and horizontal jumping tasks was further investigated using sprinting speed (ISS and MSS) as the grouping variable and jumping ability (SLJ and STJ) as the independent behavior. Finally, to determine whether

horizontal jumping tasks and basic anthropometric measures are able to predict sprinting speed, SLJ, STJ, and body weight were used as independent variables, whereas ISS and MSS were used as the dependent variables. Subjects

One hundred and fourteen elite female athletes volunteered to take part in the testing at 1 of the 3 locations: National Youth Festival (Inter-provincial fifteens competition), Under 20 National Team Fifteens Training Camp, or as part of regular training for the National Senior Women’s Sevens team. All subjects were injury-free female athletes with a mean age of 17.91 6 3.06 years (age range 14–30 years) and body weight of 67 6 6.91 kg. Before participation, all procedures and testing protocols were explained clearly to the participants. Because this data set was anonymized secondary data and the records were kept by the National Sports Organization (NSO), we obtained ethical approval from University of Victoria Human Research Ethics Board Figure 1. Correlation between standing triple jump and maximum sprint speed. An example of the changing relationship between horizontal jumping ability and sprinting speed. (Protocol Number 14-069) for the use of anonymized VOLUME 29 | NUMBER 3 | MARCH 2015 |

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Horizontal Jumping Tasks and Sprint Speed distance was measured from the heel of the athletes’ closest TABLE 4. Pearson’s correlations and magnitude of correlation among maximal foot to the starting line and sprint speed, initial sprint speed, and horizontal jumping tasks.*† rounded down to the nearest SLJ Magnitude STJ Magnitude centimeters. The athletes were given 3 attempts for ISS both jumps and required to Total group (n = 114) 0.513 Large 0.605 Large stick the landings. If athletes Slow ISS (n = 57) 0.347 Moderate 0.400 Moderate Fast ISS (n = 57) 0.036 Trivial 0.183 Small fell backward or moved their MSS feet on landing, they were Total group (n = 114) 0.695 Large 0.746 Very large given a zero. While performSlow MSS (n = 57) 0.552 Large 0.607 Large ing the STJ, the participants Fast MSS (n = 57) 0.325 Moderate 0.403 Moderate were required to minimize *SLJ = standing long jump; STJ = standing triple jump; ISS = initial sprint speed; MSS = the time on the ground maximal sprint speed. between jumps (no †The magnitude of a correlation is calculated using Will Hopkins’ scale (16). reset allowed). The best jump for each test was taken for analysis. Previous research has shown a typical error of secondary data where direct consent is not required. Addimeasurement (TEM) and coefficient of variation (CV) of tionally, consent was obtained from the NSO to use the 0.04 m and 7% for the SLJ and 0.12 m and 7% for the triple secondary use of information from the NSO. This study broad jump (TBJ) (1). was approved by the University of Victoria Ethics CommitStatistical Analyses tee and complied with the principles outlined in the DeclaAll data were tested for normality using a Sharpiro-Wilks ration of Helsinki. test. To assess the hypothesis that horizontal jumping ability is able to differentiate sprinting speed, the participants were Procedures split into a top 50% group (n = 57) and bottom 50% group (n = All tests were conducted on the same day and in the same 57) using SLJ and STJ as the independent variables. These order: body weight, 40-m sprint, SLJ, and STJ. Participants groups were then compared for body weight, ISS, MSS, initial wore minimal clothing for the collection of body weight and sprint momentum, and maximal sprint momentum. A 2athletic clothing and cleats for the remainder of the tests. All sample t-test with Bonferroni adjustment was used to compare participants were given 30 minutes to warm up before the top 50% and bottom 50% groups, alpha was set at p # testing and recommended to include 3 broad jumps (SLJ), 0.05, and effect sizes were calculated using Cohen’s d and 3 triple broad jumps (STJ), and 3 sprints of increasing evaluated using Will Hopkins’ scale of effect magnitude (14). intensity. All participants were allowed to conduct their own To determine whether the relationship between horizonwarm-ups. tal jumping ability and running speed changes between fast and slow participants, Pearson’s correlations were calculated Speed Assessment. The speed assessment was conducted using the whole group of subjects (n = 114) first and then by using Brower Timing TC-System (Draper, UT, USA). The dividing subjects into fast (n = 57) and a slow (n = 57) groups testing consisted of a 40-m sprint with splits taken at 10 using ISS and MSS. Both the magnitude of the correlations and 30 m. Participants started with the middle of their and the differences in the group mean values was assessed front foot positioned 0.75 m behind the first set of timing using Hopkins’ scale of effect sizes (14), which uses a Likertgates. The first set of timing gates was set to a height of scale approach (Table 1). 0.50 m with the remainder of the gates set to a height of Finally, to determine whether horizontal jumping tasks 1.00 m. Each participant was given 3 attempts and allowed were able to adequately predict running speed, a multiple to see their previous score between repetitions. The best regression was conducted. This model contained the inde40-m time was taken for analysis and divided into the 0- to pendent variable body weight, SLJ, and STJ and was used to 10-m split (ISS) and the 30- to 40-m split (MSS). The predict 1 of the 2 dependent variables: ISS or MSS. All of the measurements of ISS and MSS have previously been statistical tests were conducted using MYSTAT version 12.0 shown to be reliable with an intraclass correlations of r = (Systat Software Inc., San Jose, CA, USA). 0.91 and 0.94, respectively (2). Horizontal Jump Assessment. Standing long jump and an STJ comprised the horizontal jump assessment. The participants started with their toes behind the starting line, and

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RESULTS There were significant differences (p , 0.001) in both ISS and MSS between the top 50% and bottom 50% SLJ and STJ

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Journal of Strength and Conditioning Research groups (Table 2 and 3). There were also significant differences (p = 0.002) in maximal sprint momentum when examining the SLJ and in both initial sprint momentum (p = 0.010) and maximal sprint momentum (p , 0.001) when examining the STJ. When examining all participants, there was a large correlation between ISS and SLJ (r = 0.51) and STJ (r = 0.61); furthermore, MSS had a very large correlation with SLJ (r = 0.70) and STJ (r = 0.75). However, when examining the slow group, ISS was moderately correlated with SLJ (r = 0.35) and STJ (r = 0.40). Furthermore, MSS had a large correlation to both SLJ (r = 0.55) and STJ (r = 0.61) in the slow group. When examining ISS in the fast group, there was only a trivial correlation to SLJ (r = 0.04) and a small correlation to STJ (r = 0.18). The correlation coefficient also decreased when examining MSS in the fast group with moderate correlations to SLJ (r = 0.33) and STJ (r = 0.40). Multiple regression analysis revealed that the best predictive model for ISS used STJ (b = 0.305, p , 0.001) and body mass (b = 20.009, p = 0.003). Equation 1 explained 41.6% of the variance (r = 0.645, SEE = 0.221, F2,111 = 39.47, p , 0.001). Similarly, the best predictive model of MSS used body mass (b = 20.011, p = 0.017) and STJ (b = 0.661, p , 0.001) as well. Equation 2 explained 57.9% of the variance (r = 0.761, SEE = 0.325, F2,111 = 76.414, p , 0.001).

    ISS  m$s21 ¼ 3:9120:0093body  mass kg   þ 0:3053STJ m

(1)

    MSS  m$s21 ¼ 3:9920:0113body  mass kg   þ 0:6613STJ  m :

(2)

DISCUSSION To the authors’ knowledge, this is the first study to evaluate the relationship between sprint performance measures and bilateral horizontal jumping ability in elite female rugby athletes. The present results demonstrate that there is a robust relationship between horizontal jumping ability and measures of sprint performance in elite female rugby athletes. These findings have implications for performance testing and tracking where ongoing athlete categorization and evaluation is required. Furthermore, our results suggest that STJ is a better performance test than SLJ because of its higher correlation and ability to predict ISS and MSS. However, an important caveat is that the relationship between jumping ability and sprint ability may diminish in faster athletes. It is plausible to suggest that horizontal jumping tests are better suited for use in the development of lower-level athletes, where high-level athletes require more specific and detailed performance analysis.

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Significant differences in ISS and MSS between the bottom 50% and top 50% of participants categorized by horizontal jumping ability support the relationship between similar performance factors influencing sprinting and jumping ability. Specifically, the ground reaction forces (GRF) generated, the gravitational force, and wind resistance (15); of these 3 factors, the athlete will have the most influence over the GRF. During acceleration, the goal of the athlete is to optimize horizontal forces (19), as a large horizontal impulse has been shown to correlate with velocity at 16 m (15). This requirement of horizontal force development is similar to the SLJ and STJ. Once the athlete has reached maximum velocity, the goal switches to producing large vertical forces (19). Therefore, to improve sprint velocity, it is important to optimize both the GRF’s magnitude and direction during different phases of the sprint performance, similar to the force optimization during horizontal and vertical jumping. Furthermore, the musculature used while completing horizontal jumping tasks (13) and sprinting seems to be similar (23,26). Interestingly, the difference between the top 50% and bottom 50% groups for ISS was moderate when the group was divided by SLJ, whereas there was a large difference when the groups were divided by STJ ability. A possible explanation for this difference may be in the requirement of absorbing and redirecting force combined with the limiting factor of ground contact time in the STJ making the movement more specific to ISS. Building on this idea, other studies such as Barr and Nolte (3), in addition to Holm et al. (13), have noted large to very large and moderate to large correlations, respectively, between forms of drop jumping and sprinting ability. Another possible explanation for this difference in effect magnitude is because of the fact that the STJ is essentially 3 SLJ performed consecutively, possibly magnifying the differences in horizontal jumping ability and therefore magnifying the correlation. These group differences could also mean that there is a critical threshold of horizontal jump performance that should be present if developing speed is a goal. As shown in Figure 1 and Table 4, the relationship between horizontal jumping ability and sprinting speed decreases in faster athletes. Similarly, Kale et al. (16) found no relationship between 100-m time and horizontal jumping tasks (SLJ and STJ). This is consistent with the current findings as the athletes used in the study of Kale et al. (16) were significantly faster (mean V_ max = 9.44 m∙s21 6 0.41). The poor relationship between horizontal jumping tasks and sprinting ability in faster athletes could suggest that developing “general athleticism” is important in slower athletes whereas faster athletes will suffer from a ceiling effect. In already fast athletes, small increases in sprinting speed should consider specific constrains such as restriction in time to apply large, mass-specific forces because of increasing velocities (24,25). As such, measuring and improving very specific qualities related to improving sprinting ability such as the direction of force application, tendon stiffness, and/or a high rate of force development take precedence over VOLUME 29 | NUMBER 3 | MARCH 2015 |

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Horizontal Jumping Tasks and Sprint Speed general tasks such as horizontal jumping, and these specific constraints may not be well correlated to horizontal jumping ability. These results highlight the risk of generalizing findings from low-level athletes to high-level athletes, as the relationship between tasks may change as the athlete improves. Therefore, faster athletes may need to use other forms of kinematic analysis such as optical imaging systems and switch mats to evaluate specific characteristics related to improving sprinting ability. In addition, when the data from the fast and slow categories of athletes were combined, the correlation between horizontal jumping tasks and sprinting speed increased; superficially, this seems to be a similar phenomenon to the Simpson’s paradox (17), where the correlations are improperly assessed because of improper coupling of groups. This fact further highlights the risk of interpreting data from multiple levels of athletes. Despite these difficulties, an equation using body weight and STJ adequately predicted ISS and MSS. This suggests that a simple test of body weight and STJ can be used as an initial metric to identify sprint talent. This is similar to Moresi et al. (20), who determined that a horizontal jump, consisting of the SLJ, was a good predictor of 10-m sprint time. However, the present results show that SLJ did not significantly contribute (p = 0.194) to our prediction of ISS and MSS when STJ was incorporated. Therefore, it is suggested that only STJ be tested when initially identifying athletes as it seems to have a higher correlation to both ISS and MSS than SLJ. In conclusion, the preceding data provide evidence of a relationship between horizontal jumping tasks and sprinting speed. It is suggested that athletes categorized by greater jumping ability are generally faster athletes. However, caution should be taken when interpreting horizontal jump data as it seems that the relationship between horizontal jumping ability and sprinting speed decreases in faster athletes. Finally, an equation using body weight and STJ adequately predicted ISS and MSS adding support to the use of horizontal jumping tasks as control tests for female athletes. In conclusion, this cross-sectional study provides a starting point for future longitudinal research to build upon using differing populations of female athletes.

PRACTICAL APPLICATIONS This research suggests that simple horizontal jumping tasks may be a simple way to identify sprinting talent. Furthermore, an equation using body weight and STJ seems to be an adequate predictor of both ISS and MSS if the practitioner is limited in timing equipment or space. Based on these data, it is redundant to collect SLJ when identify potential sprinting talent for female rugby athletes and caution should be used when generalizing results across varying levels of athletes.

ACKNOWLEDGMENTS We thank Rugby Canada for their cooperation on this project.

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Efficacy of horizontal jumping tasks as a method for talent identification of female rugby players.

The purpose of this study was to explore the relationship between horizontal jumping tasks (standing long jump [SLJ] and standing triple jump [STJ]) a...
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