Abstract
Background and Purpose
Lower extremity athletic injuries result in impairments in balance, power, and jump-landing mechanics. Unilateral injury has bilateral effects and the literature supports that it is important to assess neuromuscular impairments such as balance, power, and jumping mechanics following injury and for safe return to sport after injury rehabilitation. Currently, individual tests are established in the literature, but no combined approach or clinical tool exists for this purpose. The purpose of this study is to describe and provide the initial data for the Lower Extremity Grading System (LEGS), comprised of three neuromuscular components for use as a baseline pre-season assessment for high school athletes to assess lower extremity performance. Furthermore, this study focuses on the differences in baseline lower extremity performance outcomes between male and female soccer and basketball athletes.
Methods
One hundred and eighty-five high school basketball, and soccer athletes (94 female, 91 male; mean age = 15.6 ± 4.4) participated. The participants were administered the LEGS assessment during the preseason for their respective sports, which includes three component tests: (1) Y-balance test, (2) drop vertical jump test, (3) triple-crossover-hop-for-distance test. Participants’ scores on each test were recorded, and then totaled to present an overall LEGS composite score. Participants’ baseline LEGS scores were then analyzed according to sex and sport, and standard normal distribution was calculated for all scores to enable percentile rankings to be established.
Results
Mean scores and standard deviation for each functional performance test are presented. Furthermore, a LEGS composite score combining the test scores was established and presented as a normal distribution curve allowing for further comparison and analysis. The mean LEGS composite score for males was 700.3 ( ± 76.6), while the mean LEGS composite score for females was 587.4 ( ± 51.6). Statistically different LEGS composite scores were found between males and females.
Conclusion
The current findings present descriptive data for the utility of the LEGS as a neuromuscular baseline assessment before high school sports participation and/or as a tool for assessing return to sports after injury rehabilitation. The LEGS may augment current assessment tools and may serve as a composite score and combined approach to the assessment of lower extremity risk of injury and readiness to return to sports.
Level of evidence
3
Keywords: Adolescent, lower extremity, baseline screening, return to play
INTRODUCTION
In the United States of America, over seven million adolescent high school students participate in athletics.1 These student-athletes sustain an estimated 1.5 million injuries each year with the lower extremity (ankle and knee) being the most common site of injury.2-5 Previous authors have reported relationships between factors such as demographics, anthropometrics, balance, and physical performance measures that may contribute to increased risk of suffering lower extremity injuries (or re-injury) in sports.6-8
Barber-Westin, et al. have suggested that it is important and recommended to assess neuromuscular impairments such as balance, power, and jumping mechanics following injury and for safe return to sport activities after injury and rehabilitation.6 Functional performance tests have been used to assess components of sport performance, determine readiness for return to sport, evaluate effectiveness of neuromuscular training interventions, and evaluate potential for injury of the lower extremity.7-11 An advantage of functional tests are that they require minimal personnel, are simple in administration, require only minimal equipment, and can be combined into a single score to assess overall physical performance and lower extremity injury risk.9,12 However in singularity these tests may provide only one dimension of an athlete's function or performance. Furthermore, normative data for these individual tests as well as a composite scoring system to describe the baseline neuromuscular function of high school athletes have not been described.
The Lower Extremity Grading System (LEGS) is presented in this study as a measure to help clinicians identify the neuromuscular status of the lower extremity using a standardized approach. Additionally the LEGS may also add utility as a preseason baseline indicator of lower extremity neuromuscular components which may be beneficial for the growing, adolescent athlete for assessing both risk of injury and performance potential. Baseline assessments with LEGS could provide valuable pre-injury data on an annual basis, and could also offer a practical clinical data tool which would allow for comparison during the rehabilitation phases of injury management of lower extremity acute non-contact injuries and for return to sport decision making.
The LEGS combines individual functional test scores in centimeters from the Y-balance test (YBT), drop vertical jump test (DVJT), and triple crossover hop for distance test (TXHD) into a single baseline LEGS composite score to provide a simplified metric reflecting a combination of lower extremity characteristics that can be used in percentile rankings. Similar scales are used in the Scholastic Assessment Test (SAT) where raw scores in sections such as reading, writing, and math are combined to provide scaled scores for percentile ranking and interpretation.
The functional tests selected for combination for the LEGS have been presented in the literature as reliable and valid assessments for jump-landing mechanics, dynamic balance, and lower limb strength and power.13-15 The reliability for the DVJT has been reported with intraclass correlation coefficients (ICCs) of 0.94 to 0.96, has been shown to be valid, and has been used to identify risks factor for noncontact acute lower extremity injuries.7,8,13,16 The YBT has been proposed as a tool utilized before, during, and after injury to assessment functional improvements and risk of injury (reliability ICCs ranging from 0.80 to 0.85).17 The reliability and validity of hop tests as performance-based outcome measures and for patients undergoing rehabilitation after anterior cruciate ligament (ACL) reconstruction has been reported (reliability ICCs ranging from 0.84 to 0.93).15
Therefore, the purpose of this study is to describe and provide the initial data for the Lower Extremity Grading System (LEGS), comprised of three neuromuscular components for use as a baseline pre-season assessment for high school athletes to assess lower extremity performance. Furthermore, this study focuses on the differences in baseline lower extremity performance outcomes between male and female soccer and basketball athletes.
METHODS
Participants
One hundred and eighty-five male and female athletes (15.6 ± 4.4 years) participated in this study. Sample size was determined by performing a priori power analysis using G*Power statistical software (Version 3.1.9.2) with power set at 0.8 and alpha level (p = .05). It was determined that a maximum number of approximately 40 participants was needed in order to demonstrate differences between groups. All participants played at least one of two high school sports: soccer or basketball. These sports were selected based upon the common occurrence of noncontact acute lower extremity injuries involved with sport participation and the performance of several high-risk maneuvers.2
All participants completed pre-participation health history questionnaires to rule out current pathological conditions (any condition that would prohibit clearance to participate in athletics) and contraindications to study participation, which were evaluated by a physician. Exclusionary criteria included: incomplete pre-participation physical exam, and/or inability to physically perform any of the required assessments. No participants were excluded from this study due to previous injury. Prior to study participation all procedures were explained to each participant. Participants and their parents/guardians read and signed assent and consent forms and video use consent forms that were approved by the institutional review board for human subjects.
Procedures
Data were collected by the same examiners at all testing sessions. All examiners were NATABOC professional certified athletic trainers at the master's degree level with education and experience familiarizing them with the assessments and testing procedures. Anthropometric data were recorded before all testing procedures and included height, body mass, body mass index (BMI), age, date of birth, grade, sport, and level of sport participation (freshman, junior varsity, or varsity) by the principal investigators. All testing was performed in a school gymnasium. Before testing, participants conducted a 10 minute dynamic warm-up led by the principal investigators. The dynamic warm up included jogging, backpedaling, side-stepping, and walking stretches. Three testing stations (balance, power, jumping mechanics) were established and participants were assigned randomly to the stations and proceeded with synchronous clockwise rotation until as stations were completed. Standardized oral instructions for each test were rehearsed and read by the examiners to all test groups. Standardized instructions were designed to maintain consistency of testing procedures, decrease instructional time, and allow concise and precise data collection. Incorrect test performance required that the test be restarted after a minimum 30-second rest period. No corrective feedback was given to subjects.
The Lower Extremity Grading System (LEGS)
The LEGS was developed to assess neuromuscular function of the lower extremities for use as a pre-participation baseline screening and as a tool for evaluating return to sports following injury rehabilitation. The LEGS employed in this study consisted of previously described assessments of the following three components: (1) dynamic balance, (2) jump-landing mechanics, and (3) lower limb power as measured by the YBT, DVJT, and TXHD, respectively. A copy of the LEGS form is provided in Appendix I. A visual depiction representing each test is provided in Figure 1.
Figure 1.
The LEGS tests used in this study (from left to right): Y-Balance Test (YBT), Drop Vertical Jump Test (DVJT), and Triple Crossover Hop for Distance Test (TXHD).
The YBT was used to assess dynamic balance of the stance leg by recording single-leg reach distance in cm(s) on each leg with a standard FMS™ Y-balance kit. Participants stood on the center of the testing kit with one limb and reached with their contralateral limb in the anterior, posteromedial, and posterolateral directions. Participants were given one practice trial on each limb and engaged in one test trial per limb. Participants started on the left limb and repeated the test with a stance on the right limb. The average of the maximum reach distances from the three directions (MaxD) was recorded in centimeters and normalized according to leg length of the stance leg in order to adjust for variances of different anthropometric variables. Leg length was measured with a Gulick tape measure from the anterior superior iliac spine to the distal medial malleolus. The YBT scores were expressed as a percentage of leg length.18
The DVJT was performed as described by Noyes et al.13 An Apple iPad (Apple, Inc., Cupertino, CA) was used to record jump landing mechanics, placed on a 102 cm high stand, positioned approximately 366 cm in front of a box that was 30 cm in height and 38 cm in width. Camera resolution was 1080P at 24 frames per second. Immediately before each subject performed the DVJT, the same examiner placed two sets of 4 × 4 cm florescent pink reference markers over the ASIS and center of patella for each limb. Jump landing mechanics were analyzed post-testing session via Dartfish Motion Analysis Software (ProSuite version 4.0.9.0) where lower limb separation distances at the hip and knee were measured.
Hip separation distance (HSD) was measured while standing erect on top of the box and defined as the distance between the most prominent points of each anterior superior iliac spine which were marked with fluorescent tape markers. Knee separation distance (KSD) was measured at the lowest point of each jump landing prior to transition to takeoff into the vertical jump and was defined as the distance between the centers of the patellae, which were marked with fluorescent tape markers. Participants were instructed to jump maximally (“as high as possible”) upon dropping from the box. The average absolute KSD during three successful trials was recorded in centimeters and then normalized relative to HSD to yield a percentage for each subject.13
The TXHD evaluated maximal hopping distance on a single leg and was assessed in centimeters (cm) with a standard tape measure fixed to the ground, perpendicular to the starting line.15 Participants stood on the designated testing leg with the great toe on the starting line and performed three consecutive maximal hops forward on the same limb, crossing over the tape measure with each hop. Participants started on the left limb and repeated the test with the right limb. Each participant initiated the hops by hopping in the lateral (outside) direction. Each participant was given one practice trial per limb and two test trials per limb. Arm swing was allowed, and the investigator measured the distance hopped from the starting line to the point where the toe struck the ground upon completing the third hop. The maximum distance achieved of the two test trials was recorded in centimeters and used for analysis.
STATISTICAL METHODS
All data were analyzed using SPSS Statistics Version 22.0.0.0 (IBM, Armonk, New York, USA), and Microsoft Excel. Participants were divided into groups according to independent variables such as sex (male or female), and sport (basketball or soccer). Variables of interest included performance on the independent functional performance tests as well as the LEGS composite score. Unpaired t-test were used to compare means between sexes and sports with an alpha level set at p =.05 to determine statistical significance.
The LEGS composite score is presented as a total, and was calculated using the following equation:
Normal distribution curves were calculated using the mean LEGS composite scores and standard deviations.
RESULTS
Participant demographic characteristics, individual functional test scores, and LEGS composite scores are provided in Table 1. Female functional test scores and LEGS composite scores grouped by sport are presented in Table 2. Male functional test scores and LEGS composite scores grouped by sport are presented in Table 3. Mean test scores between males and females are graphically presented in Figure 2.
Table 1.
Demographics, functional test scores, and LEGS composite scores (mean ± SD).
| Demographics | Total (N = 185) | Females (n = 94) | Males (n = 91) | |
|---|---|---|---|---|
| Age (years) | 15.6 ± 4.4 | 15.2 ± 1.0 | 15.4 ± 1.1 | |
| Height (cm) | 170 ± 9.6 | 164.7 ± 6.5 | 175.8 ± 8.7 | |
| Weight (kg) | 62.7 ± 11.9 | 59.6 ± 10.7 | 66.4 ± 11.9 | |
| Body Mass Index (kg/m2) | 21.6 ± 3.0 | 21.9 ± 3.3 | 21.3 ± 2.7 |
| Functional Test | Total (N = 185) | Females (n = 94) | Males (n = 91) | p-Value |
|---|---|---|---|---|
| YBT average score (cm) | 93.8 ± 9.0 | 95.0 ± 9.3 | 92.4 ± 8.5 | 0.0399* |
| DVJT score (%) | 80.2 ± 15.3 | 76.0 ± 15.2 | 83.9 ± 14.5 | 0.0008* |
| TXHD average score (cm) | 470.7 ± 80.5 | 416.4 ± 49.8 | 524.0 ± 69.8 | 0.0001* |
| LEGS Composite Score | Total (N = 185) | Females (n = 94) | Males (n = 91) | p-Value |
|---|---|---|---|---|
| LEGS Composite Score | 628.2 ± 92.9 | 587.4 ± 51.6 | 700.3 ± 76.6 | 0.0001* |
YBT = Y-balance test; DVJT = Drop vertical jump test; TXHD = triple crossover hop for distance; LEGS = lower extremity grading system
Statistically significantly different at p<0.05 level.
Table 2.
Test scores (females) by sport (mean ± SD).
| Females | |||
|---|---|---|---|
| Functional Test | Basketball (n = 42) | Soccer (n = 52) | p-Value |
| YBT average score (cm) | 92.1 ± 8.8 | 97.5 ± 9.0 | 0.0045* |
| DVJT score (cm) | 79.2 ± 14.7 | 74.3 ± 15.4 | 0.1184 |
| TXHD score (cm) | 423.4 ± 58.9 | 416.0 ± 45.8 | 0.4961 |
| Limb Symmetry Index (%) | 98.1 ± 4.4 | 98.4 ± 4.8 | 0.8646 |
| LEGS Composite Score | Basketball (n = 42) | Soccer (n = 52) | p-Value |
|---|---|---|---|
| LEGS composite score | 595.0 ± 61.2 | 588.0 ± 49.2 | 0.5403 |
YBT = Y-balance test; DVJT = Drop vertical jump test; TXHD = triple crossover hop for distance; LEGS = lower extremity grading system
Statistically significantly different at p<0.05 level.
Table 3.
Test scores (males) by sport (mean ± SD).
| Males | |||
|---|---|---|---|
| Functional Test | Basketball (n = 41) | Soccer (n = 50) | p-Value |
| YBT average score (cm) | 91.9 ± 8.3 | 92.8 ± 8.7 | 0.6212 |
| DVJT score (cm) | 85.7 ± 15.0 | 82.4 ± 14.0 | 0.2714 |
| TXHD score (cm) | 537.6 ± 65.8 | 511.9 ± 71.6 | 0.0675 |
| Limb Symmetry Index (%) | 100.3 ± 4.8 | 101.6 ± 5.6 | 0.0786 |
| LEGS Composite Score | Basketball (n = 41) | Soccer (n = 50) | p-Value |
|---|---|---|---|
| LEGS composite score | 715.6 ± 70.6 | 687.3 ± 79.7 | 0.0786 |
YBT = Y-balance test; DVJT = Drop vertical jump test; TXHD = triple crossover hop for distance; LEGS = lower extremity grading system
Figure 2.
Mean test scores females vs. males on Y-Balance Test (YBT) in cm; Drop Vertical Jump Test (DVJT) knee separation distance/hip separation distance (cm) as a percentage; Triple Crossover Hop for Distance Test (TXHD) in cm; and Limb Symmetry Index (LSI) as a percentage. The LSI is calculated as the difference between limb data from both the YBT and TXHD.
The mean LEGS composite score for males was 700.3 with a standard deviation of 76.6, while the mean LEGS composite score for females was 587.4 with a standard deviation of 51.6. These data were utilized to create standard normal distribution curves of the LEGS composite scores for females and males which are presented in Figure 3.
Figure 3.
Normal distribution curve for LEGS composite scores of males and females.
Each athlete's individual YBT, DVJT, and TXHD scores were subtracted from the mean score and divided by the standard deviation to create standard normal distributions curves. These standardized scores can then be summed to provide one total z-score for each athlete. These z-scores can be analyzed further as a percentile ranking score based on the total sample. The percentage scores in this study ranged from 8% to 89%. This scoring system may allow interpretation regarding readiness for sport participation similar to how the SAT test is intended to assess intellectual readiness for college.
Statistically significant differences were found between male and female scores on all individual functional tests and the LEGS composite score. Interestingly, males demonstrated higher scores on all functional tests except the YBT. Female soccer athletes demonstrated the highest YBT scores amongst the sports groups, while male basketball athletes demonstrated the highest DVJT and TXHD scores. For male athletes, differences between the LEGS composite scores of basketball and soccer athletes were not significantly different. Similarly, for female athletes, the LEGS composite scores of basketball and soccer athletes were not significantly different.
Limb symmetry index (LSI) was calculated as a percentage by dividing scores of the left and right limbs for all participants. The mean LSI for male basketball athletes was 100.3 ( ± 4.8), while the mean LSI for male soccer athletes was 101.6 ( ± 5.6). The mean LSI for female basketball athletes was 98.1 ( ± 4.4), while the mean LSI for female soccer athletes was 98.4 ( ± 4.8).
DISCUSSION
Using a systematic approach to combining objective functional scores from three performance test outcomes, the LEGS composite score was established. The main result of the present study is the provision of descriptive data regarding baseline lower extremity function in high school athletes competing in soccer and basketball using the LEGS composite score and standardized curves for percentile rankings. Establishing standard normal distribution curves presents this data in a format that may allow for age, sex, or sport-matched comparisons to be made in decision making and rehabilitative planning. Furthermore, differences in baseline lower extremity performance between male and female soccer and basketball athletes is also elucidated.
The advantages of utilizing the LEGS composite scores and functional performance tests described in the present study is the simplicity of administration, the systematic approach to combining functional test scores, and the objective nature of the analysis. The creation of the LEGS composite score is of clinical importance since it allows for an assessment that yields objective data in the form of a single metric, which can be compared to age-related distribution or baseline scores to inform clinical decisions. Previous literature has presented combined functional performance test measurements into a single score to assess overall physical performance and lower extremity injury risk.12
In previous studies, the functional performance tests used in the LEGS application have been shown to be reliable and valid.13-15 Evidence in previous literature found no difference in YBT performance between male general college students and male college athletes, while noting the validity of the tool for purposes of preparticipation screening and injury prediction.19 Results in the current study show statistically significant differences between high school female and male YBT scores, with females scoring higher during baseline screening.
The YBT has been proposed as a tool utilized before, during, and after injury to assessment functional improvements and risk of injury.17 Other evidence in the literature describes the inter-rater test-retest reliability of the YBT as well as the utility of dynamic balance as a screening and rehabilitation tool for female collegiate volleyball players.14,20 Butler et al. examined YBT scores in high school, college, and professional soccer players and proposed the need for further establishing normative values for both male and female athletes of all ages, levels of competition, and sports.21 The present study presents data in an attempt to establish normative values for the high school athlete.
Barber-Westin et al. reported on the utility of the DVJT as an indicator of an athlete's lower limb control, while other researchers have reported the simplicity of the DVJT administration for identifying risk for injury.22,23 The results of the present study show significant differences in male and female DVJT scores when used as a baseline screen in basketball and soccer athletes. This may indicate decreased lower limb control in high school-aged female sports participants when compared to their male counterparts and may result in an increased potential risk of injury.
Previous literature has noted the need for normative data on limb symmetry indices and hop test performance grouped by age, sports, sex, etc.24 The results of the present study may contribute to this need by indicating the significant differences between male and female single leg hopping power via the TXHD. The reliability and validity of hop tests as performance-based outcome measures for patients undergoing rehabilitation after anterior cruciate ligament (ACL) reconstruction has also been reported.15
In a systematic review, Barber-Westin et al. demonstrated the need for objective measurements of strength, stability, and neuromuscular function in return to play decision-making models.6 Similarly, the 2016 consensus statement on return to sports outlines the need for focused research on defining, measuring, and reporting return to sport outcomes using a standardized approach.25 The results of the current study provide a systematic approach for combining data from multiple reliable and valid tests into a singular metric which can be translated into comparative ranking.
The outcomes of this study are relevant particularly for the high school athletic population for establishing normative data to describe lower extremity function and symmetry in baseline preparticipation screening. In this study, both sexes demonstrated limb symmetry indices near 100% demonstrating that baseline evaluation of healthy high school athletes indicates symmetry between limbs. Limb symmetry is often used as a clinical indicator for return of function of the lower extremity after injury or surgical intervention. The LEGS composite score could be utilized for comparing LSI measures during rehabilitation to baseline LSI measures for return to sport decision making.
Future direction and research with LEGS should include larger sample sizes and the inclusion of baseline LEGS composite scores from athletes participating in other sports. Furthermore, validation studies comparing baseline scores to post-injury scores for return to play decisions may also further assess the utility of the LEGS.
CONCLUSION
The current study presents descriptive data for the utility of the LEGS as a neuromuscular baseline assessment before high school sports participation and/or as a tool for assessing return to sports after injury rehabilitation. The LEGS may augment current assessment tools and may serve as a composite score and combined approach to the assessment of lower extremity risk of injury and readiness to return to sports. The LEGS composite score and standardized curves for percentile rankings establishes standard normal distribution curves which allow for age, sex, or sport-matched comparisons to be made in decision making and rehabilitative planning.
APPENDIX I.
REFERENCES
- 1.Centers for Disease Control and Prevention. Guidelines for school and community programs to promote lifelong physical activity among young people. J Sch Health. 1997;67(6):202-19. [DOI] [PubMed] [Google Scholar]
- 2.Darrow CJ, et al. Epidemiology of severe injuries among United States high school athletes. Am J Sports Med. 2009;37(9):1798-805. [DOI] [PubMed] [Google Scholar]
- 3.Rechel JA Yard EE Comstock RD. An epidemiologic comparison of high school sports injuries sustained in practice and competition. J Athl Train. 2008;43(2):197-204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Le Gall F Carling C Reilly T. Injuries in young elite female soccer players: an 8-season prospective study. Am J Sports Med. 2008;36(2):276-84. [DOI] [PubMed] [Google Scholar]
- 5.Nelson AJ, et al. Ankle injuries among United States high school sports athletes 2005-2006. J Athl Train. 2007;42(3):381-7. [PMC free article] [PubMed] [Google Scholar]
- 6.Barber-Westin SD Noyes FR. Factors used to determine return to unrestricted sports activities after anterior cruciate ligament reconstruction. Arthroscopy. 2011;27(12):1697-1705. [DOI] [PubMed] [Google Scholar]
- 7.Noyes FR, et al. A training program to improve neuromuscular and performance indices in female high school basketball players. J Strength Cond Res. 2012;26(3):709-19. [DOI] [PubMed] [Google Scholar]
- 8.Noyes FR, et al. A training program to improve neuromuscular and performance indices in female high school soccer players. J Strength Cond Res. 2013;27(2):340-51. [DOI] [PubMed] [Google Scholar]
- 9.Brumitt J, et al. Lower extremity functional tests and risk of injury in division iii collegiate athletes. Int J Sports Phys Ther. 2013;8(3):216-27. [PMC free article] [PubMed] [Google Scholar]
- 10.Hegedus EJ, et al. Clinician-friendly lower extremity physical performance measures in athletes: a systematic review of measurement properties and correlation with injury, part 1. The tests for knee function including the hop tests. Br J Sports Med. 2015:49(10):642-8. [DOI] [PubMed] [Google Scholar]
- 11.Hegedus EJ, et al. Clinician-friendly lower extremity physical performance tests in athletes: a systematic review of measurement properties and correlation with injury. Part 2-the tests for the hip, thigh, foot and ankle including the star excursion balance test. Br J Sports Med. 2015:49(10):649-56. [DOI] [PubMed] [Google Scholar]
- 12.Smith J DePhillipo N Kimura I, et al. Prospective functional performance testing and relationship to lower extremity injury incidence in adolescent sports participants. Int J Sports Phys Ther. 2017:12(2): 206-218. [PMC free article] [PubMed] [Google Scholar]
- 13.Noyes FR, et al. The drop-jump screening test: difference in lower limb control by gender and effect of neuromuscular training in female athletes. Am J Sports Med. 2005;33(2):197-207. [DOI] [PubMed] [Google Scholar]
- 14.Shaffer S Teyhen D Lorenson C, et al. Y-balance test: a reliability study involving multiple raters. Mil Med. 2013:178(11): 1264-1270. [DOI] [PubMed] [Google Scholar]
- 15.Reid A, et al. Hop testing provides a reliable and valid outcome measure during rehabilitation after anterior cruciate ligament reconstruction. Phys Ther. 2007;87:337-349. [DOI] [PubMed] [Google Scholar]
- 16.Sigward S Havens K Powers C. Knee separation distance and lower extremity kinematics during a drop land: implications for clinical screening. J Athl Train. 2011:46(5):471-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Teyhen DS, et al. Clinical measures associated with dynamic balance and functional movement. J Strength Cond Res. 2014;28(5):1272-1283. [DOI] [PubMed] [Google Scholar]
- 18.Kendall F McCreary E Provance PG, et al. Muscles Testing and Function With Posture and Pain 5th ed. Baltimore, MD: Williams & Wilkins; 2005. [Google Scholar]
- 19.Engquist KD, et al. Performance comparison of student-athletes and general college students on the functional movement screen and the Y-balance test. J Strength Cond Res. 2015;29(8):2296-2303. [DOI] [PubMed] [Google Scholar]
- 20.Hudson C Garrison JC Pollard K. Y-balance normative data for female collegiate volleyball players. Phys Ther Sport. 2016;61-65. [DOI] [PubMed] [Google Scholar]
- 21.Butler RJ, et al. Differences in soccer players’ dynamic balance across levels of competition. J Athl Train. 2012;47(6):616-620. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Barber-Westin SD, et al. The drop-jump video screening test: retention of improvement in neuromuscular control in female volleyball players. J Strength Cond Res. 2010;24(11)3055-3062. [DOI] [PubMed] [Google Scholar]
- 23.Redler LH, et al. Reliability of a field-based drop vertical jump screening test for ACL injury risk assessment. Phys Sportsmed. 2016;44(1):46-52. [DOI] [PubMed] [Google Scholar]
- 24.Myers, et al. Normative data for hop tests in high school and collegiate basketball and soccer players. Int J Sports Phys Ther. 2014;9(5):596-603. [PMC free article] [PubMed] [Google Scholar]
- 25.Ardern CL, et al. 2016 consensus statement on return to sport from the first world congress in sports physical therapy, Bern. Br J Sports Med. 2016;0:1-12. [DOI] [PubMed] [Google Scholar]