Relationship between Reactive strength index modified and other variables to the measures of speed and change of directionAbstractThe purpose of this study was to examine the relationship of reactive strength index modified (RSImod), and other variables derived from an unloaded counter movement jump (CMJ), to the measures of speed and change of direction (COD) among field-based sport athletes. Sixteen male collegiate athletes performed two trials of CMJ’s, 0 -10m sprints and COD tests. Intraclass correlation coefficients and typical error as coefficient of variation (CV) were used to establish the reliability of the CMJ variables, sprint and COD tests. Pearson correlation coefficients were used to identify the relationships between the CMJ variables to the 0-10m and COD times. Independent sample t-test were used to identify the relationships of CMJ variables among the fast and slow athletes. Statistically significant correlations existed between ‘relative peak force’ and ‘relative peak power’ (p?.05, p?.01) in the fast sprint group, but no correlations existed to the COD times. Relative peak force and other Relative peak power can be used as a measurement of lower body explosiveness among field-based sport population.IntroductionThe stretch shortening cycle (SSC) is thought to be active in most athletic activities (i.e. sprinting, jumping, change of direction). The characteristics of SSC is further classified by Schmidtbleicher to fast (<250 milliseconds; sprinting, jumping) or slow (>250 milliseconds; change of direction, CMJ’s) (15). Plyometric activities often use these mechanisms to improve SSC performance, like in a countermovement jump (CMJ) for example (15). Substantial evidence proves that, addition of plyometrics in a training program is an effective way of improving SSC function for tasks like the CMJ, sprinting and change of direction (3,7,10). The monitoring of these performance components for the athletes is also an important aspect to the overall training process.  The ability of the musculotendinous unit to provide a fast-eccentric contraction before an explosive concentric contraction is known as Reactive Strength (1).  Reactive strength index (RSI) as a metric is more easily derived, compared to other force derived variables and provides us with quality information on an athlete’s neuromuscular and SSC function, than jump height alone (5). In fact, strong relationship exists between RSI, change of direction speed and acceleration speed (20). However, the limitation of RSI as a metric is that this can only be attained and calculated during tasks which requires jumps that have an identifiable ground contact time. In a recent study conducted by Ebben and Petushek, an alternative option was provided in the form of RSI modified (RSImod) (4). This allowed the use of countermovement initiated jumping tasks such as the CMJ’s, which replace the ground contact time like in a depth jump with time to take off (TTT) (4). The RSImod calculated during the unloaded CMJ, is a very reliable performance measurement of lower body explosiveness with intraclass correlation coefficient (ICC = 0.96) and is related to force-time variables such as peak force and peak power (16,17). As previous studies have shown that relationship exists between RSImod to force and power characteristics of the unloaded CMJ, such as rate of force development (RFD) (r=0.56-0.66), peak force (r= 0.37- 0.50), peak power (r=0.47- 0.69) and jump height (r=0.37-0.40) (16,11) this study included measures such as ‘relative peak force’ (RPF) and ‘relative peak power (RPP)’ in its analysis and was correlated to the measures of 0-10m sprint time and change of direction (COD) tests. Previously, the performance of multidirectional speed has been closely associated to vertical, horizontal and reactive power with contribution of lateral power (9). The change of direction acceleration test (CODAT) was chosen due to its sufficient lateral power involvement, as it features four changes in direction and more explosive cuts when compared to the T-tests. (12,9)Further, to provide sport scientists, strength and conditioning practitioners working in field-based sports, selecting a performance measuring tool that provides information on reactive strength qualities of their athletes needs to be reliable. Although only one previous study has been conducted assessing the reliability of RSImod among subjects of sprint and endurance-based sport population (2), no previous studies has assessed the relative qualities of RSImod and other variables derived from the CMJ for linear speed and COD separately. Therefore, the primary aim of this study was to assess the relationship of RSImod derived using an unloaded CMJ to the measures of linear speed and COD among field-based sport population. A secondary purpose of this study was to investigate other variables such as peak power, relative peak power, jump height, peak force and relative peak force obtained from the CMJ, is a reliable measurement and holds a relationship to the measures of linear speed and COD.   MethodsExperimental approach to the problemThisstudytested the relationship between RSImod and other variables such Peak Force (N), relative peak force(kg/m), jump Height(m), peak power(W), relative peak power(W/kg) which were calculated using the CMJ, to the measures of speed and change of direction. The speed and change of direction tests were a linear 10-m sprint, and CODAT respectively. A reliability analysis was conducted using an Intraclass co-relation coefficients (ICC) was set at >0.80 and a typical error as Co-efficient of variation (CV) limit was set at <10% (6). Pearson’s co-relation analysis was used to evaluate the degree of relationship obtained in the performance of the jump test, 0-10m time and change of direction test times. SubjectsSixteen male collegiate athletes participated in this study. Subject’s anthropometric data are presented in Table 1. Inclusion criteria required participant involvement in any team-based field sport such as gaelic football, hurling, soccer and rugby; were above the age of eighteen; were available for both testing sessions; were without any medical conditions that resulted in a compromise to the maximal performance of the tests. This study had institutional ethics approval from the university research ethics committee and all subjects volunteered, and were consented. Table 1: Descriptive Statistics*  Variables AthletesAge (y)Mass (kg)Height (cm)n = 1622.35 ± 3.779.6 ± 11.7178.7 ± 5.5Values are mean ± SD.       ProceduresTesting was conducted over two separate days. Testing for the CMJ was conducted at the University of Limerick’s bio-mechanics lab, the speed and change of direction components at the sports hall. All subjects performed a familiarisation session prior to data collection. Before participation, subjects had their anthropometric data recorded. As a specific warm-up, all subjects completed 3 mins of jogging paired with dynamic stretching of lower body and 10 body weight squats. This was followed by unloaded CMJ’s at increasing intensities of 50, 75 and 100% respectively with a wooden dowel. Five minutes after completion of CMJ testing, a specific warm-up comprising of light jogging for 3 minutes followed by progressive speed runs at increasing intensities of 70, 80, 90 & 100% over the testing distances for both the tests was conducted (10m sprint, CODAT). Adapted from Lockie et.al 2014Figure 1: Change of Direction Test set up. m = metersCMJFollowing a specific warm-up, one-minute recovery was provided before the start of the test. Subjects then performed two maximum effort CMJ’s with one minute of rest between each jump. All CMJ’s were performed with the athletes holding upon a wooden dowel resting on their upper trapezius muscle behind their neck (16). This was done to isolate the performance of lower extremities, standardise jumping conditions, and to eliminate the use of an arm swing, which may greatly affect jump height and other force-time variables during the CMJ (16).All CMJ’s were recorded on a force platform (AMTI OR 6-5) sampled at 1,000HZ and Bio-soft software (Version 2.3.2). Subjects were instructed to stand still for one second of data collection, to provide the determination of body weight (14). Vertical force-time data were exported and analysed using a customised Microsoft excel spreadsheet. RSImod was calculated as jump height divided by TTT (i.e. the time between the onset of movement and take off) Figure 2 (4). Other variables such as peak force (N), relative peak force(kg/m), peak power(W), relative peak power(W/kg) were calculated with the highest force-time value obtained from the CMJ. In order to calculate Jump Height(m), the vertical force trace was single integrated (13).Adapted from Suchomel et.al 2015Figure 2: Force-time record of the CMJ. TTT = Time to take off; FT = flight time10m sprint  A 10-m sprint was used to measure linear speed. 0-10m time was recorded by using dual beam timing gates (Microgate, Bolzano, Italy). Gates were set-up at 0 m and 10m. Subjects were given verbal instructions as to not slow down before the timing gates and to give their maximum efforts for the both the trials. Subjects began the sprint test behind a line 70 cm from the first timing gate with a standard two point (standing) start set-up (19). This was done to not trigger the timing gates before the start of each sprint (19). Two maximum efforts were recorded with 2 minutes of recovery between each effort. CODATThe CODAT was chosen due to its common movement pattern in most field-based sports (linear acceleration and lateral cutting) has been proven to be a very reliable and a valid assessment of change of direction (9). The test features two linear sprints of 5m and 10m, and 3 sprints between four changes in direction presented in Figure 1. Start to finish time was recorded using dual beam timing gates (Microgate, Bolzano, Italy). Gates were set-up at 0 m and finish line. Subjects began the sprint test behind a line 70 cm from the first timing gate with a standard two point (standing) start set-up (19). This was done to not trigger the timing gates before the start of each sprint (19). Verbal instructions were given to them which emphasised on staying outside the markers throughout the test. If subjects cut across or over the top of a marker, the trial was stopped and a separate test was conducted after an appropriate rest period (8). Two maximum efforts were recorded with 2 minutes of recovery between each effort. Statistical AnalysisAll CMJ data were collected and analysed with the help of a customised Microsoft excel spreadsheet. The RSImod value for each subject was calculated by dividing the jump height by the time to take off (4).Data was normally distributed for all conditions, as assessed by the Shapiro-Wilk’s test (p>0.05). Intraclass correlation coefficient (ICC) and typical error (CV) were derived used the Hopkins spreadsheet and was expressed in percentage presented in Table 2 (6).Additional analysis included a median split by speed, with subjects being grouped into fast and slow athletes (n=14) with an aim of investigating relative qualities derived from the CMJ among them. Two tailed independent sample T-tests were conducted to assess the differences between the fast and slow groups. All statistical analysis was conducted using the SPSS 25 (IBM, New York, USA). Pearson’s zero order correlations were calculated between each of the CMJ variable and assessed to the 0-10m time and COD. ResultsRelationship between CMJ variables with measures of Speed and CODAT.Pearson correlation coefficients between CMJ variables and Speed, CODAT measures are presented in Table 4. Relative Peak force RPF (kg/m) and Relative peak power RPP(w/kg) showed a large negative correlation with measures of speed at (r = -.53, p?.05) and (r= -.62, p?.01) respectively. However, there was no significant correlation between RSImod to the measures of Speed and CODAT.  Fast and slow between-groups comparison Differences between the relatively fast athletes and slow athletes are presented in Table 5. Relative Peak force RPF (kg/m) and relative peak power RPP (w/kg) showed a large negative correlation among the fast group with the measures of 0-10m sprint time at (r= -.84, p?0.5) and (r= -.91, p?0.1) respectively. However, there was no significant correlation between the CMJ variables to the groups for CODAT.  Table 2: Reliability statistics*VariablesICC              CV (%) RSImod0.897.5PP0.963.3RPP 0.953.4PF0.924.6RPF0.814.70 – 10m sprint0.941.5CODAT0.772.5      Abbreviations: RSImod, Reactive strength index modified; PF, Peak force; RPF, Relative peak force; JH, jump height; PP, Peak power; RPP, Relative peak power; CODAT, change of direction acceleration test.   Table 3: Descriptive CMJ, Speed & COD data* CMJVariablesSpeed Athletes RSImod PF(n) RPF(kg/m) JH(m) PP(w)  RPP(w/kg) 0-10m CODATN=160.40 ± 0.071900.9 ± 262.223.9 ± 2.10.31 ± 0.043734.8 ± 571.347.1 ± 6.71.84 ± 0.15.94 ± 0.3Abbreviations: RSImod, Reactive strength index modified; PF, Peak force; RPF, Relative peak force; JH, jump height; PP, Peak power; RPP; Relative peak powerValues are mean ± SDMeasures RSImod PF(n)CMJVariablesRPF(kg/m)JH(m)PP(w)RPP(w/kg) Speed -.27 .15 -.53* -.33 -.17 -.62** CODAT-.22-.06-.21-.02-.09-.27Table 4: Pearson correlations between CMJ variables and Speed, CODAT.Abbreviations: RSImod, Reactive strength index modified; PF, Peak force; RPF, Relative peak force; JH, jump height; PP, Peak power; RPP; Relative peak power*Significant at P ?.05. ** Significant at P ? .01 CMJ VariablesSprint CODAT  Fast  Slow Fast SlowRSImod-.16-.45.56-.31PF(n)-.62.52.01.56RPF (kg/m)-.84*-.36.23-.30JH(m).27-.61.15.17PP(w)-.50.03.31-.53RPP(w/kg)-.91**-.59.63-.70Table 5: Fast and slow between groups comparisonAbbreviations: RSImod, Reactive strength index modified; PF, Peak force; RPF, Relative peak force; JH, jump height; PP, Peak power; RPP; Relative peak power*Significant at P ?.05. ** Significant at P ? .01DiscussionThis study investigated the relationships of the CMJ variables, compared them to the measure of 0-10m time and COD during an unloaded CMJ. The results of this study found significant correlations between RPF and RPP to the 0-10m time during an unloaded CMJ. Second, there were no significant correlations between RSImod and other CMJ variables to the times of CODAT. Finally, significant correlations existed only between RPF and RPP in fast sprint group and that no correlations were found between any of the CMJ variables to the sprint times of the slow group, CODAT times of the fast and slow group.The intraclass correlation coefficients showed that RSImod is a reliable performance measurement between the 2 CMJ trials. This study was in line to the ICC values previously reported by Ebben and Petushek (4).Further, RSImod has been suggested as a measure of explosiveness in athlete profiling, due to its abilities in developing quick maximal force (4,16,). Previous research reported significant correlations to JH and TTT among the sprint population (2). Based on large correlations between relative peak force and relative peak power during both the unloaded CMJ’s (r= -.53 and r= -.62) and between fast and slow sprint groups (r= -.84 and r= -.91) the results from this study supports this hypothesis. Statistically no significant correlations were observed between the fast and slow groups when compared to the jump performance to the CODAT times. It must also be noted that the sample size of this study is comparatively lesser than previous studies that looked upon RSImod and other variables derived from CMJ performance on field-based sport population (16,11). Hence affecting the strength of the results.The current findings from the study indicate that athletes who were able to generate greater force and power in a shorter time during an unloaded CMJ had a quicker timing in the 0-10m sprint, when compared to fast and slow groups. Future research must consider specific field-based sport and must be individualised to player positions.Based on large relationships that were found with RPF and RPP to the sprint group within this study, RPF and RPP can be used as a measure of lower body explosiveness for monitoring the reactive strength of field-based sport athletes. It can further be suggested that research should investigate RSImod values among professional sporting teams and determine the changes in its values with response to training stimulus and fatigue accumulated during the course of a competitive season. Practical ApplicationResults from this study proves that RSImod has no correlation to the measures of speed and agility. However, RPF and RPP can be used as a reliable performance measure of lower body explosives among collegiate team sport athletes. Sport scientists, strength and conditioning coaches must consider using it in the monitoring of their athletes. This extensive information helps the practitioner not only provide the athlete with a high-quality feedback but also to the coaching staff (Head coach, skill coaches). Hence, helping both the practitioner and the coaching staff to take important steps in constructing sessions and outcomes with respect to training specificity on and of the field. ReferencesBeattie, K., Carson, B.P., Lyons, M. and Kenny, I.C., 2017. The relationship between maximal strength and reactive strength. International journal of sports physiology and performance, 12(4), pp.548-553Comyns, T., McNamara, C. and White, O., Reactive-strength index modified as an explosive measurement in male sprint and endurance athletes.De Villarreal, E.S., Requena, B. and Cronin, J.B., 2012. The effects of plyometric training on sprint performance: A meta-analysis. The Journal of Strength & Conditioning Research, 26(2), pp.575-584.Ebben, W.P. and Petushek, E.J., 2010. 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Physical qualities predict change-of-direction speed but not defensive agility in Australian rules football. The Journal of Strength & Conditioning Research, 29(1), pp.206-212.Get Help With Your EssayIf you need assistance with writing your essay, our professional essay writing service is here to help!Find out more