THE USE OF FUNCTIONAL TESTS TO PREDICT SAGITTAL PLANE KNEE KINEMATICS IN NCAA‐D1 FEMALE ATHLETES

Abstract

Background

Landing with the knee in extension places increased loads on ligamentous restraints at the knee versus landing in flexion. Unfortunately, existing methods to predict landing kinematics require sophisticated equipment and expertise. The purpose of this study was to develop predictive models for sagittal plane tibiofemoral landing kinematics from the results of functional tests.

Methods

Twenty‐nine female, NCAA‐D1 college athletes (mean ± standard deviation, age = 19.03 ± 1.09; mass=66.56 ± 13.47 kg; height = 171.16 ± 7.92 cm) participated in a descriptive, laboratory study. Participants performed five unilateral, dominant lower extremity (LE) landings from a 35cm platform onto a forceplate. LE three‐dimensional kinematics were captured with electromagnetic sensors interfaced with motion analysis software. Then in a randomized order, participants performed three standardized functional tests: single limb triple hop (SLTH), countermovement vertical jump (CMVJ) and the Margaria‐Kalamen (MK) test. Sagittal plane tibiofemoral joint angle at initial contact (IC) and excursion (EXC) in the first 0.1s after ground contact were entered into a statistical software package. Multiple linear regression analyses generated one model predicting IC and one predicting EXC from the independent variables. Alpha levels were set a priori at p ≤ .05.

Results

A two variable (MK, SLTH) linear regression model that predicted EXC was significant (Adjusted R² = .213, p = .017), however the model that predicted IC was not (p = .890).

Conclusion

Knee flexion excursion following a single leg landing task may be predicted with the MK and SLTH. The use of functional tests provides a practical means to predict landing kinematics to clinicians working with an active, athletic population.

Level of Evidence

3, cohort study

INTRODUCTION

Anterior cruciate ligament (ACL) injuries remain common amongst female athletes. Despite efforts from medical professionals,^1-3 ACL injury frequency continues to increase in female intercollegiate athletes.⁴ Once torn, ACL reconstruction with a six⁵ to more than 12 month⁶ rehabilitation is the standard protocol in an attempt to restore preoperative function.

Even with a reconstruction, repercussions from ACL injuries are substantial. Individuals who have undergone an ACL reconstruction have 17%^7,8‐23%⁹ increased likelihood of re‐injury and of developing knee osteoarthritis.⁷ In fact, history of previous knee injury in females increases the adjusted odds ratio of knee osteoarthritis to 3.17 versus females without a previous knee injury.¹⁰ Additionally, the athlete often faces psycho‐sociological challenges during their time away from participation.^11,12 Considering the deleterious long term effects, prevention rather than management of ACL injuries should be the preferred strategy.

While numerous ACL injury risk factors have been identified, laboratory research has consistently noted females exhibit suboptimal lower extremity (LE) landing kinematics when compared to males. Females make ground contact closer to tibiofemoral joint extension^13-16 followed by less sagittal plane flexion immediate after contact^1,17,18 than males. ACL bundles achieve their greatest length and should therefore be under greatest load as the knee approaches full extension.¹⁹ Indeed, research has shown that an extended tibiofemoral joint at and immediate after landing was the most common mechanism for injury in an athletic sample.¹ Additional load placed on the ACL with the knee closer to full extension then is more likely to have a deleterious effect on the tissue.

Until recently, sophisticated instrumentation was required to detect faulty landing kinematics. A few years ago, Padua and colleagues developed the Landing Error Scoring System²⁰ and Landing Error Scoring System ‐ Real Time²¹ as a means by which experienced clinicians could examine landing kinematics in athletes. Though clearly more practical compared to three‐dimensional motion analysis, it remains challenging to implement this type of system in clinical settings due to the professional training and expertise that is required to administer. Hence, even a more practical method of predicting LE landing kinematics would be of value to those with limited clinical experience and/or landing assessment expertise.

Previously published work suggests an individual's ability to rapidly produce LE muscular force is related to tibiofemoral landing kinematics.²² Carcia et al identified the longer it took a subject to produce peak force, not only was there a greater tendency for the subject to land in more of a valgus position but there was also a greater tendency for the subject to undergo a greater amount of valgus excursion during a single leg landing task.²² The time to peak force measure illuminated the relationship between rapid generation of muscle force on landing kinematics at the knee. Theoretically, rapid force generation of the local musculature promotes active stiffness thereby enhancing joint stability and limiting excursion. Furthermore, the ability to quickly produce force provides not only a means by which joint stability may be improved but also a means by which force can be controlled and dissipated via the muscular system thereby limiting stress on the passive restraints. Given the preliminary work by Carcia and colleagues, it is plausible landing kinematics may be predicted from the results of tests in which force is rapidly produced. If the use of easy to administer clinical functional tests are capable of predicting lower extremity kinematics, this approach could provide a low cost and practical model to identify female athletes who are at increased risk of non‐contact ACL injury during landing.

Therefore the purpose of this study was to develop regression equations that predict sagittal plane tibiofemoral landing kinematics from the results of select functional tests that require rapid force generation. The hypotheses for this investigation was that the regression models would explain a substantial amount of the variance associated with tibiofemoral sagittal plane landing kinematics.

METHODS

Participants

A sample of healthy, National Collegiate Athletic Association Division I intercollegiate female athletes between 18 and 24 [(19.03 ± 1.09 years, mass = 66.56 ± 13.47 kg; height = 171.16 ± 7.92 cm), five left LE dominant, 24 right LE dominant] were recruited for participation. Females were currently active on the basketball, lacrosse, or soccer team roster. Athletes from these sports were targeted to participate as they are at increased risk for non‐contact ACL injury.^23-25 Participants were excluded from the study if within the last six months they had: 1) utilized crutches for any LE injury or 2) missed a regularly scheduled intercollegiate competition due to a LE injury, 3) engaged in a rehabilitation program for a LE injury or 4) could not perform the landing technique due to pain. In addition, participants were excused if they were allergic to tape adhesive or if they utilized an implanted medical device such as an insulin pump, hearing aid or pacemaker. They also were excused from participation if they reported that they may be, or are trying to become pregnant or otherwise should not be exposed to an electromagnetic field.

Procedures

All data acquisition took place in the Kristen L. McMaster Memorial Motion Analysis Laboratory at Duquesne University and each participant followed identical procedures. This quasi‐experimental study utilized a randomized descriptive laboratory design. An a priori analysis (G*Power, v3.1.3) based on pilot data indicated a sample size of 36 was needed to obtain a power of .80. Upon arrival to the laboratory, inclusion and exclusion criteria were reviewed to ensure eligibility. Those that met the criteria were provided with a Duquesne University Institutional Review Board approved Consent to Participate form which was completed before progressing further. Height and mass of the participant were assessed with a scientific grade medical beam balance scale (Jarden Corporation; Rye, NY). Participant age and intercollegiate sport played were recorded.

The participant was then asked to step off a 35 cm high wooden platform and land on only one limb without an additional secondary hop. This procedure was repeated two additional trials. The foot the participant preferred for landing two out of three trials was defined as the dominant LE. This operational definition of dominance has been previously described²⁶ and recently shown to identify the LE at greatest risk for ACL injury.²⁷

Landing Kinematic and Kinetic Data Collection

Participants performed a ten minute warm up on a stationary bike at a self‐selected pace. Next, three electromagnetic sensors (Ascension Technology; Milton, VT) coupled with The MotionMonitor software (Innovative Sports Training; Chicago, IL) were utilized to measure three dimensional LE kinematics. Prior work has established the reliability of the motion analysis system.^28-30 Published research has also established the position and orientation accuracy of the motion analysis system in the specific laboratory environment.³¹ Metal mapping was performed prior to the study to minimize the effect of metal in the testing environment.³²

A force plate (Bertec Corporation; Columbus, OH) identified ground contact. Ground contact was operationally defined as when a force greater than or equal to 20N was recorded by the forceplate above a quiet baseline. The forceplate was countersunk into the floor so as to be flush with the testing surface. The motion analysis system and force plate were synchronized and data collected at 100 and 1000 Hertz respectively. Electromagnetic sensors were placed over the L5‐S1 junction, mid‐lateral thigh and lateral leg just distal to the fibular head. Each of the three sensors were secured using prefabricated neoprene cuffs [Figure 1] and a 5x5 cm piece of double‐sided carpet tape (3M; St. Paul, MN) between the cuff and the participant.

Figure 1.

3D motion capture sensor placement for single LE drop landing.

The electromagnetic sensors were activated and the segments digitized using a Grood‐Suntay coordinate system with the participant standing in the anatomical position. The participant then stood on the 35 cm high wooden platform. The platform edge was located five cm away from the force plate. The participant stood with toes on the leading edge of the platform and hands on their iliac crests. Participants were asked to perform a single limb drop landing onto the forceplate utilizing only the dominant LE while keeping their hands on their iliac crests as kinematic and kinetic data were recorded. Placement of the participant's hands on their iliac crests sought to control for upper extremity motion during the landing task. A trial was discarded if the participant's foot did not land fully on the forceplate, if the landing resulted in a secondary hop, or if the hands were removed from the iliac crests. After five successful trials, participants were given a five minute recovery. Upon removal of the electromagnetic sensors, the participants then completed the three LE functional tests in a random order with a five‐minute recovery period between each test.

Single Limb Triple Hop (SLTH)

Participants were asked to place the heel of their dominant LE at the leading edge of a marked line and to keep their hands on their iliac crests throughout the trials. As per previously reported protocol,³³ no other restrictions were placed on the upper extremities. They were then instructed to perform three sequential, dominant LE only hops [Figure 2] while achieving the greatest horizontal distance possible. Participants were encouraged to spend the least amount of time possible in contact with the ground until landing the third hop. Four practice trials were performed prior to measured trials. The first practice trial was performed at self‐perceived 50% effort, the second at 75% effort, and the third and fourth trial at maximal effort. With each trial, the individual held the landing from the third hop for at least 1s.³³ The individual then performed three maximal trials with a 15 second recovery between trials. The trial was invalidated if the hands were removed from the hips during the trial or if the third landing was not held for 1s. The procedures and trials as described were consistent with previously established practice.³³ Upon completion of each test trial, the investigator measured the horizontal distance hopped from the starting line to the heel of the third landing with a standard tape measure (American Guidance Service, Inc.; Circle Pines, MN). The mean of the three measured trials was utilized for data analysis.^33-35 The SLTH test is an explosive test that requires the athlete to rapidly produce and absorb force similar to what would be required during sport. Hamilton et al identified the SLTH was a predictor of muscular power as measured by an isokinetic device.³⁶ Additionally, the SLTH has been previously studied to assess function after ACL injury in collegiate‐aged females.³⁴ The test‐retest reliability of the SLTH has been previously established with ICC values ranging from 0.80‐0.97.^37,38

Figure 2.

Foot placement for performance of the Single Limb Triple Hop (SLTH).

Countermovement Vertical Jump (CMVJ)

The participant stood, facing perpendicular to a Vertec™ device (Sports Imports; Columbus, OH) with the dominant LE nearest the device. A standing reach value was measured and recorded using the Vertec™ device with the participant's arm overhead and both feet flat on the ground. The participant was then instructed to jump and touch the highest possible plastic tab on the Vertec™. To perform an optimum jump, the participant was told to bend at their knees, hips, and ankles; then move their arms forward and upward while jumping [Figure 3]. The depth of squat and amount of arm swing that occurred with the CMVJ was determined by the participant. No step or pre‐jump was allowed. After the first trial, all the tabs below the highest moved tab were pushed aside. Participants performed three trials with a 15 second recovery between trials with this established and previously reported protocol.³⁹ The CMVJ height was calculated as the difference between the maximal height jumped on the best trial and the standing reach height. As with the SLTH, the CMVJ has also been investigated for assessing return to function after ACL injury.⁴⁰ Likewise, several authors have calculated power values from results of the CMVJ test suggesting it reflects in some capacity the ability of an individual to rapidly generate force.^41,42 CMVJ test‐retest reliability has been established as ‘good’⁴³ with reported ICC values 0.82‐0.99^44,45

Figure 3.

Performance of the Countermovement Vertical Jump (CMVJ).

Margaria‐Kalamen Test (MK)

The participant stood on a marked line, six meters from and level with an 11 step staircase that had a rise of 16.6 cm per step. A pressure switch triggered digital timer (Lafayette Instrument; Lafayette, IN) was placed on the third and ninth step. On the researcher's signal, the participant ran from the starting mark and bound up the stairway taking the steps three at a time (third, sixth, ninth) [Figure 4]. The time was recorded between when participant contacted the third step (first pressure switch) and the ninth step (second pressure switch). The participant completed three trials with a 20 second rest between each trial. The best performance time (t) was used to calculate the participant's power (P = [Mass x Vertical distance between 9^th & 3^rd step] x 9.8 ÷ t).⁴⁶ The MK test is a true measure of power which can be defined as the rate of performing work.⁴⁷ Test‐retest reliability of the MK has been established as good (ICC = 0.73).⁴⁸

Figure 4.

Performance of the Margaria‐Kalamen (MK) Test.

Statistical Methods

Kinematic data were exported from The Motion Monitor software into an Excel spreadsheet where the five landing trials for each participant were aligned and signal averaged. Next, sagittal plane tibiofemoral joint angles at initial contact (IC) and excursion (EXC) values were determined for each participant. IC was defined as the sagittal plane tibiofemoral angle when the vertical ground reaction force was equal or greater than 20N. EXC was operationally defined as the maximum sagittal plane tibiofemoral angle (up to 0.1s after IC) minus the IC angle. One‐tenth of a second was chosen as the upper limit in which kinematic data were retrieved as ACL injury has been shown to occur in this temporal envelope.^49,50

Data were then entered into a statistical software package (SPSS‐22, IBM; Armonk, NY) for analysis. Descriptive statistics were compiled for the participants. The inter‐correlations amongst and between the independent and dependent variables were assessed. Step‐wise linear regression models to predict IC angle and to EXC angle were generated. Both models used the results from the independent variables (functional tests) as the predictors. The coefficient of determination and analysis of variance of regression from each model were examined along with an analysis of residuals and outliers. Alpha levels for all analyses were set a priori at p ≤ .05.

RESULTS

Twenty‐nine female NCAA Division I athletes from the sports of basketball (n=3), lacrosse (n=12), and soccer (n=14) participated. Descriptive data from the dependent and independent variables are reported in Table 1. A correlation matrix displaying the correlations amongst and between the independent and dependent variables is presented in Table 2. The step‐wise linear regression analysis to predict IC from the three LE functional tests was not significant (p=.890) (Table 3).

Table 1.

Variable value Means, Standard Deviations and Range

	Mean and Standard Deviation	Range
IC	10.99 ± 5.64°	‐0.73 to 22.90°
EXC	34.66 ± 5.89°	22.94 ° to 46.35°
CMVJ	42.79 ± 5.08 cm	34.92 cm to 52.71 cm
SLTH	536.98 ± 48.41 cm	426.33 cm to 614.00 cm
MK	1035.92 ± 202.05 Watts	753.85 Watts to 1698.67 Watts

IC= Sagittal plane tibiofemoral angle when the vertical ground reaction force was equal or greater than 20N

EXC= Maximum sagittal plane tibiofemoral angle (up to 0.1s after IC) minus the IC angle

CMVJ= Countermovement Vertical Jump test

SLTH= Single Leg Triple Hop test

MK= Margaria-Kalamen test

Table 2.

Correlation Matrix for the Independent and Dependent Variables

	MK	SLTH	CMVJ	IC	EXC
MK	r = 1.00	r = .008	r = .069	r = .081	r = ‐.404
		P = .966	P = .723	P = .677	P = .026*
SLTH		r = 1.00	r = .363	r = .132	r = .309
			P = .053	P = .494	P = .102
CMVJ			r = 1.00	r = .033	r = .150
				P = .865	P = .436
IC				r = 1.00	r = .060
					P = .757
EXC					r = 1.00

IC= Sagittal plane tibiofemoral angle when the vertical ground reaction force was equal or greater than 20N

EXC= Maximum sagittal plane tibiofemoral angle (up to 0.1s after IC) minus the IC angle

CMVJ= Countermovement Vertical Jump test

SLTH= Single Leg Triple Hop test

MK= Margaria-Kalamen test

Table 3.

Regression Table for Stepwise Multiple Linear Regression Analysis for IC

Multiple Linear Regression
Variable	Coefficient	Error	T	P	Adjusted R2	Model P
Constant	0.989		0.07	0.95	0.093	0.89
SLTH	0.016	0.14	0.66	0.52
MK	0.002	0.081	0.41	0.69
CMVJ	−0.026	−0.02	−0.11	0.91

IC= Sagittal plane tibiofemoral angle when the vertical ground reaction force was equal or greater than 20N

CMVJ= Countermovement Vertical Jump test

SLTH= Single Leg Triple Hop test

MK= Margaria-Kalamen test

Results from the step‐wise linear regression analysis utilizing the three functional tests to predict EXC were significant (p = .043). However, further evaluation of the step‐wise regression indicated that inclusion of only MK and SLTH provided the most robust model (Adjusted R² = .213; p=.017) (Table 4). The use of MK and SLTH then, was able to explain twenty‐one percent of the variance in the model. The EXC model is expressed with the equation: EXC = 26.79 ‐ .012(MK) + .038(SLTH). The addition of CMVJ was not significant in the regression to predict EXC. The MK test was inversely related to sagittal plane EXC (r = ‐0.404; p = .026) indicating that power as measured by the MK test went up, EXC went down. No other significant relationships amongst or between the variables were identified.

Table 4.

Regression Table for Stepwise Multiple Linear Regression Analysis for EXC

Multiple Linear Regression
Variable	Coefficient	Error	T	P	Adjusted R2	Model P
Constant	26.79		2.22	0.04	0.213	0.017
MK	−0.012	−0.42	−2.49	0.02
SLTH	0.038	0.313	1.87	0.07

EXC= Maximum sagittal plane tibiofemoral angle (up to 0.1s after IC) minus the IC angle

CMVJ= Countermovement Vertical Jump test

SLTH= Single Leg Triple Hop test

MK= Margaria-Kalamen test

DISCUSSION

ACL injury risk has been shown to increase with the knee near full extension and or with decreased knee flexion excursion immediately after a single leg landing.^1,17 As females have been shown to land with their tibiofemoral joint closer to full extension compared to males,^1,17,18 this sagittal plane kinematic difference during landing may partially explain the gender difference in ACL injury rates. Given this, the purpose of this study was to determine if sagittal plane tibiofemoral kinematics during a single LE landing could be predicted by measurements of three functional clinician friendly tests. In doing so, the predictive equations could provide a practical identification method for female collegiate athletes who exhibit poor sagittal plane landing kinematics. By identifying female collegiate athletes who demonstrate poor sagittal plane landing kinematics, implementation of existing ACL injury prevention programs for those athletes who demonstrate this risk factor, rather than to all female athletes on the respective team, would optimize the use of staff, facility space and student time. This is especially important in situations with limited staff and facilities as one might find in the smaller collegiate setting. Unfortunately, the results from this investigation provide only limited evidence in support of the previously stated hypotheses.

Predicting Sagittal Plane Initial Contact Angle

Based on the current investigation, the results of the three selected functional tests were unable to predict sagittal plane IC angle. Not only were these functional tests unable to produce a significant regression equation predicting IC angle, but sagittal plane IC angle was not significantly correlated to any of the independent variables. A recent study by Nagai et al⁵¹ identified a significant two variable linear regression equation was capable of predicting sagittal plane IC during a stop, jump task. Specifically, the investigators explained 21.3% of the variance associated with IC angle from joint positioning awareness and knee flexion peak torque values. While the authors were able to report a significant regression equation predicting IC angle, the vast majority of the variance remained unexplained. Further, sophisticated equipment needed to assess these outcome measures are unavailable to most practitioners. While other studies have attempted to predict lower extremity landing kinematics^{17,22,26,51-54} each of these studies were similar to the work by Nagai et al in that they utilized sophisticated instrumentation and required technical expertise. To the best of the authors’ knowledge, only one other method of analysis that incorporated practical, low‐tech instrumentation to predict LE landing kinematics has been developed.^20,21,55 In these studies, a 30cm platform was utilized in a clinical setting by clinicians with more than five years of experience who were also familiar with visual analysis of landing kinematics. The authors believe that the current study is the only exploration into the utilization of practical tests to predict LE landing kinematics capable of being proctored by those without a clinical background. Additional work that seeks to predict IC angle using practical measures in female athletes is warranted.

Predicting Sagittal Plane Excursion

Although this investigation did not identify a significant equation to predict sagittal plane IC angle, two (two‐ and three predictor variable) significant equations using multiple linear regression were identified to predict sagittal plane EXC. The equation that incorporated three predictor variables while statistically significant explained less of the variance when compared to the two variable equation. One could contend, CMVJ as a predictor variable was a more vertically biased movement when compared to the MK and certainly the SLTH. The CMVJ was also the only selected functional test which did not take into account landing as a component of the test result. The test score (maximal jump height) was achieved before the participant prepared for landing. Further, the majority of athletes that participated in the present study do not routinely employ straight vertical jumps as part of their sport activity. Precisely why with the CMVJ variable removed the strength of the regression equation improved is not well understood and would require in‐depth study directly comparing these two tests on multiple levels in distinct populations.

Closer inspection of the two‐predictor variable regression equation for EXC however raises additional questions. Specifically, as power for the MK test increased, EXC decreased, but as distance for the SLTH increased, EXC increased. The fact that these two relationships are in opposing directions [though the latter relationship (SLTH:EXC) is not statistically significant (p = .102)] suggests the tests are measuring different constructs. The MK test quantifies power while it is less clear exactly what the SLTH quantifies. Both tests require explosive motion and each require three single‐leg foot contacts before the recorded test measure. Likewise, each of these foot contacts require efficient absorption of energy in a limited time window. Furthermore, both tests require rapid horizontal and vertical displacement of the subject's mass comparable to what occurs in many sport environments. Hamilton et al suggested the SLTH is a measure of both strength and power.³⁶ Sapega and Drillings however strongly advocated that a true measure of power must meet the strict definition of power.⁴⁷ As such, they indicated the units associated with a test should be consistent with that of a power measure (e.g. Watts).

Increased EXC is believed to be an effective strategy by which force can be dissipated thereby lowering the risk of ACL injury.^52,56 Teaching athletes to flex their hips, knees and ankles upon landing has been advocated by several investigators as a strategy to reduce force over time.^55,57,58 This strategy may be effective in a lab environment or during sports when adequate time periods for such joint motion are allowed. Limited time to disperse energy however more realistically reflects what occurs in competition for the targeted sports. Hence, increased power instead of greater EXC in this context appears to be a valuable characteristic from a competitive standpoint. Additional investigation as to how true LE power measures affect kinematics and kinetics and ultimately injury is certainly warranted.

While the study by Carcia et al identified a relationship between the rapid generation of muscle force and landing kinematics,²² the manner in which the variables were quantified differed substantially from this investigation. The time to peak force measure as reported by Carcia et al. was isometric while the current study's measures were dynamic. As most ACL injuries occur during rapid decelerations and accelerations,^23,59 functional tests that exhibited these characteristics were deliberately selected. While the MK generates a power (strength / time) value, the CMVJ and SLTH also require rapid generation of a high magnitude of force but do not result in a power value. To escape the pull of gravity, the force generated in the CMVJ on the body's center of mass must be rapid. Likewise, the SLTH distance is optimized when the time spent in contact with the ground is minimized due to the myotatic response.

Additionally, given that the current investigation focused on predicting sagittal plane landing kinematics, motion during the chosen functional tests were deliberately sagittal plane biased. The functional tests utilized in this study were also selected due to the ease of administration, the familiarity of these tests in most collegiate environments, and their established reliability. Each selected test also incorporated landing as a component of the test. Furthermore, to enhance the performance on two out of three of the functional tests (MK, SLTH), subjects appeared to minimize the stretch‐shortening cycle duration thereby limiting the time available for knee flexion excursion. The limitation in knee flexion excursion may have been a strategy to maximize use of the stretch‐shortening cycle and improve performance during the test. This test strategy, which was qualitatively observed, further justifies the use of the abbreviated temporal window used during the landing task when quantifying subjects’ kinematics. Though subjects’ knee flexion range of motion was not overtly limited nor was the time it took a subject to achieve peak knee flexion during the functional tests directly quantified, results from the MK test provide some objective insight. The mean MK time to completion for the sample was 0.663±.070 s. During that time, the participants made two airborne bounds, two landings where energy was absorbed and two landings where take‐off forces were generated. In doing so, the sample performed the MK that included six phases in 0.66s approximating the landing observation time window of 0.1s.

Other investigators have reported power may be indirectly calculated from the results of the CMVJ⁴¹ and SLTH⁶⁰ tests. To ensure the current data analysis was thorough, the authors’ reanalyzed the data post‐hoc after converting the CMVJ and SLTH values with the formulae identified by Sayers et al⁴¹ and English et al⁶⁰. The step‐wise regression model to predict IC with the work and power measures remained statistically insignificant (R² = .196; p = .135). The step‐wise regression model to predict EXC utilizing the power and work values changed from being statistically significant to non‐significant for both the three predictor variable model (R² = .177; p = .174) and the two predictor variable model (R² = .171; p = .087). These findings suggest there are some components unique to the MK and SLTH that better describe sagittal plane landing behaviors than described by measures of muscular power alone.

Limitations

The current study, like all studies has some limitations that should be acknowledged. Based on the a‐priori power analysis, 36 subjects were needed to achieve 80% power. Unfortunately, only 29 subjects chose to participate. Essentially, the limited pool of athletes in the targeted sports at the university were exhausted. Despite this, the authors are confident a Type II error was not committed as it relates to the inability to identify a significant regression equation for IC angle given the p value of 0.890 and effect size of .024 for sagittal plane IC angle.

Additionally, it should be appreciated that while the authors did identify a significant regression equation for sagittal plane excursion following a unilateral landing task, only 21% of the variance was explained by the regression equation. The remaining 79% of the variance associated with EXC is due to other variables not explored in the current study. Previous work has suggested that these variables might include the amount of hip joint excursion at landing,¹⁶ hip muscle involvement,⁶¹ lower extremity joint stiffness,⁶² trunk posture,⁶³ available motion at the ankle joint,⁶⁴ and lower extremity muscular strength ratios.⁶¹

Also, the current results are only generalizable to the studied population and are specific to the employed methodology. Future investigations should examine whether other practical tests are capable of predicting sagittal and or frontal plane landing kinematics. Hopefully, future study will reveal regression equations that explain a greater amount of the variance associated with landing kinematics in this population. Of course, other at risk populations participating at various levels of competition would benefit from the development of similar predictive type of equations.

CLINICAL RELEVANCE

The ability to predict landing kinematics from practical low‐tech tests such as those utilized in the current study would be invaluable to coaches, clinicians and sports medicine professionals. The results of the current study, if validated, could dramatically increase the feasibility of screening female athletes for sub‐optimal landing kinematics. Female athletes identified by such a screening could be recommended to partake in an intervention program thereby lowering their risk of ACL injury.

CONCLUSION

The utilization of clinical functional tests explained a small but statistically significant amount of variance in tibiofemoral joint excursion in the sagittal plane following a single leg landing task. It was also noted that as power from the MK test increased, EXC following a single leg land decreased. The functional tests utilized in the current study however were not able to predict tibiofemoral joint angle at IC. Future research is needed to develop a practical and cost effective predictive method that explains a greater amount of the variance associated with these measures and to further explore how power is related to landing kinematics.