Relationships Between Absolute and Relative Strength and Power in Male Police Officers of Varying Strength Levels

  • J. Jay DawesEmail author
  • Robert G. Lockie
  • Charles L. Kornhauser
  • Ryan J. Holmes
  • Robin M. Orr
Original Article


Strength and power are important traits for law enforcement officers, but the relationship between these measures has yet to be determined in a law enforcement population. Furthermore, the nature for these relationships between officers of varying strength is not known. The purpose of this study was to investigate the relationship between strength and measures of power and to determine whether stronger officers portrayed greater power. Retrospective data for 543 male (age = 39.07 ± 8.04 years; height = 180.02 ± 15.14 cm; body mass = 92.73 ± 16.37 kg) officers from one agency were provided. Measures included isometric leg/back dynamometer (LBD) strength, a counter movement jump (CMJ) and further determined measures of lower body power [estimated anaerobic power in watts (PAPw)] and power to body mass ration (P:BM). Following an analysis by cohort, subgroup quartiles were created based off LBD strength [absolute (LBDa) and relative (LBDr)]. The strongest quartile (Q1) performed significantly better in CMJ and PAPw than the other groups, but not in P:BM. Significant (P ≤ 0.001) low-to-moderate positive correlations were found between LBDa and CMJ height (r = 0.388), PAPw (r = 0.606) and P:BM (r = 0.272) and between LBDr and CMJ (r = 0.556), P:BM (r = 0.642) and PAPw (r = 0.149). Only LBDr was significantly related to all power measures across all sub groups. The development of relative lower body strength may best prepare officers for power assessments (such as vertical jump assessments) as well as for occupational tasks that require power.


Vertical jump Tactical athlete Law enforcement Fitness Performance 


The job of a police officer can be physically demanding and may require physical exertions at or near an officers’ age-predicted maximal heart rate (Dawes et al. 2018). In the line of duty, officers may be required to lift and move heavy objects, pursue and apprehend a suspect, perform hand-to-hand combat, jump and climb over fences and barriers, and lift or push heavy objects [2, 11, 28]. Furthermore, these tasks must be performed while wearing personal protective equipment (PPE) that can weigh approximately 10 kg [4, 17, 21]. This additional load increases the physical burden placed on the officer and has been shown to negatively impact physical performance [15, 17, 26]. Indeed, an officer must have the requisite lower body strength and power to perform these critical tasks in a safe, efficient, and effective manner to maintain public safety and protect themselves from injury, and in some cases death [7, 24]. As such, leg strength and power are frequently assessed within police populations to ensure that appropriate levels of lower body muscular fitness have been attained [5, 11, 12, 20, 25].

Lower body power tests are frequently performed and have been investigated in numerous studies within the law enforcement community. Dawes et al. [10] examined the relationship between selected measures of power [e.g., countermovement jump (CMJ) height, peak anaerobic power in watts (PAPw), power-to-body mass ratio (P:BM), and sprint speed over 5 m, 10 m, and 20 m] among members of a part-time Special Weapons and Tactics (SWAT) team. These researchers found significant correlations between all of the selected speed distances and power measures (i.e., CMJ height: r = 0.572 to 0.602; PAPw: r = 0.686 to 0.959; P:BM: r = − 0.561 to − 0.696). Other studies have reported significant relationships between measures of lower body power and body drag velocity [22], as well as performance on an occupationally specific physical ability test [11]. Based on these results, the need for lower body strength and power in tactical populations is evident. However, the relationships between these two measures have yet to be fully explored.

Several studies have reported significant relationships between measures of relative lower body strength using the 3RM back squat (Anderson et al. 2018) and the Hex Bar deadlift [29], with no relationship between absolute strength and jump performance among Division II female athletes. Although the relationships between absolute strength and power have not been explored in a law enforcement population, the relationship between lower body strength and occupational performance has been investigated. Absolute strength as measured by an isometric leg/back dynamometer (LBDa) was found to not differentiate between high and low performers in a group of officers performing an occupationally specific physical agility test (PAT) [11]. In contrast, Muirhead et al. (2019) reported that LBDa scores were associated with a positive identification shooting scenario (r = 0.344, P < 0.05) and the officers’ total score across the three marksmanship scenarios (i.e., static marksmanship, move and shoot, positive identification) performed in this study (r = 0.350, P < 0.05). Based on these findings, it is evident that the relationships between relative strength by an isometric leg/back dynamometer (LBDr) and an lower body power among law enforcement officers of varying strength levels has not been fully explored. This information may be of value considering the need for lower body power to perform occupational tasks efficiently and effectively [10, 11, 22].

Noting that power is essential for occupational performance and to maintain safety, the impact of absolute, and relative strength on lower power performance in this population warrants further investigation. These relationships may be of importance when seeking to develop optimal conditioning practices for officers. As such, the aim of this investigation was to determine if significant relationships between strength and power exist in male police officers of varying strength levels. It was hypothesized that significant positive correlations would exist between measures of lower body power among stronger and weaker officers. In addition, it was hypothesized that stronger officers would also have significantly greater power production capabilities compared to weaker officers in all three measures of power.



Archival data collected by the training staff of one law enforcement agency in the USA was released with consent to the primary investigator for the purpose of conducting this retrospective cohort study. A sample of convenience comprising 543 male (age = 39.07 ± 8.04 years; height = 180.02 ± 15.14 cm; body mass = 92.73 ± 16.37 kg) officers from one agency was utilized for this analysis. This sample represented approximately 75% of the total number of uniformed officers belonging to this agency. Based on the archival nature of this analysis, the institutional ethics committee approved the use of pre-existing data for analysis. Nonetheless, this study still conforms to the recommendations of the Declaration of Helsinki [3].

Study Design

A cross-sectional retrospective analysis of existing data was conducted to investigate the relationships between isometric leg/back strength and measures of lower body power in a group of USA highway patrol officers from a single law enforcement agency. The data utilized for this analysis were collected by two officers from the training staff at the agency. These officers were both certified Tactical Strength and Conditioning Facilitators (TSAC-F). All tests were conducted indoors at the law enforcement agency’s training facility. Prior to testing, all officers performed a self-selected 5–10 min warm-up. Due to the large number of officers employed by the agency, multiple testing data were scheduled throughout the calendar year of 2016. The specific descriptions and protocols for each of these tests are provided in the following section.

Height and Body Mass

Both height (HT) and body mass (BM) were self-reported. Self-report data on anthropometric variables have been utilized in the previous law enforcement research [11, 12] and have been found to be an accurate method of assessing HT and BM in this population [14]. HT and BM data were provided to the primary investigator in standard units of measure (i.e., inches and pounds) and were converted to metric units [i.e., centimeters (cm) and kilograms (kg)] for analysis.

Countermovement Jump (CMJ)

Similar to other research within law enforcement populations [9, 11, 12], CMJ height was measured using a 27-in × 27-in (68.58 cm × 68.58 cm) electronic contact mat (Just Jump, ProBotics Inc, Huntsville, AL). This device has been validated in the previous research [18], and uses flight time/contact time to calculate vertical jump height. All officers were instructed to step on the contact mat and when ready perform a maximal effort countermovement jump with an arm swing. The best of three attempts were taken and maximal jump height was recorded to the nearest 0.5 inch. The data were then converted to metric units (cm) and used to estimate PAPw using the following equation developed by Sayers et al. [27]: PAPw (W) = 60.7 × [jump height (cm)] + 45.3 × [body mass (kg)] − 2055.

PAPw was also calculated relative to body mass to provide a power-to-body mass ratio (P:BM) via the equation: P:BM = PAPw/BM (Anderson et al. 2018).

Leg/Back Chain Dynamometer (LBD) Strength

An LBD (Medico Inc., Phoenix, AZ, USA) was used to assess isometric strength of the lower back and legs. Procedures for performing this assessment have been described in the previous research [9, 10, 11]. The chain, which connects the scale on one end and a handle on the other, was adjusted, so that the officer’s knees were bent at approximately 120°. While maintaining proper spinal alignment and feet flat on the base of the dynamometer, the officers were instructed to keep the arms straight and pull the LBD handle upward as hard as possible by extending through the hips and knees. Each officer completed one trial on this test due to time constraints. Absolute LBD strength (LBDa) was recorded as the amount of isometric force produced measured in kilograms. Relative LBD strength (LBDr) was then calculated by dividing LBDa by the officer’s self-reported BM.

Statistical Analysis

Statistical analyses were processed using the JASP Statistics Package (Version 9.0.1; University of Amsterdam, Amsterdam, NL). Descriptive data [mean ± standard deviation (SD)] were calculated for each variable. Officers were then stratified into quartiles based on LBDa and LBDr strength [e.g., strongest 25% (Q1), second strongest (Q2), second weakest (Q3), and weakest 25% (Q4)]. Levene’s test for equality of variances were checked to determine whether equal variances were to be assumed or not assumed. A one-way analysis of variance (ANOVA), with Tukey post hoc for multiple pairwise comparisons, was used to calculate any differences between the quartile groups. Effect sizes (d) were also calculated for the between-group comparisons for LBDa and LBDr, where the difference between means was divided by the pooled SD. In accordance with Hopkins [16], a d less than 0.2 was considered a trivial effect; 0.2 to 0.6 a small effect; 0.6 to 1.2 a moderate effect; 1.2 to 2.0 a large effect; 2.0 to 4.0 a very large effect; and 4.0 and above an extremely large effect. Pearson’s correlations were then used to relate absolute (LBDa) and relative (LBDr) isometric leg/back strength to lower body power (CMJ, PAPw, P:BM) for the entire sample, as well as by quartiles. The statistical analysis for the correlations was set, a priori, at the P < 0.05 level. The strength of each correlation value was as follows: 0 to 0.30, or 0 to − 0.30 was considered low; 0.31 to 0.49, or − 0.31 to − 0.49 moderate; 0.50 to 0.69, or − 0.50 to − 0.69 large; 0.70 to 0.89, or − 0.70 to − 0.89 very large; and 0.90 to 1.0, or − 0.90 to 1.0 a near perfect correlation [6]. Statistical significance was again set at P < 0.05.


Descriptive data for the entire sample are displayed in Table 1. The descriptive data for each quartile group based on LBDa, as well as pairwise comparisons, are shown in Figs. 1, 2, 3. Furthermore, effect size (ES) data for this sample can be found in Table 2. Significant interactions between groups for LBDr (F3 = 68.20, P < 0.001), CMJ (F3 = 17.29, P < 0.001) and PAPw (F3 = 66.68, P < 0.001) were discovered. In regard to CMJ height, Q1 jumped significantly higher than all other groups (Q2: P < 0.01, Q3 and Q4: P < 0.001; ES: small-moderate), Furthermore, Q2 displayed greater CMJ heights compared to Q4 (ES: moderate). PAPw was also significantly greater in Q1 compared to all other groups (P < 0.001; ES: moderate–large). Q2 displayed greater lower body power compared Q3 (P < 0.01; ES: small), and Q4 (P < 0.001; ES: large), while Q3 had significantly greater power outputs compared to Q4 (P < 0.001; ES: moderate). No significant differences were observed between any groups on P:BM.
Table 1

Descriptive data for entire sample (n = 543)




Mean ± SD

Age (years)



39.28 ± 7.96

HT (cm)



180.02 ± 15.14

BM (kg)



93.59 ± 15.92

LBDa (kg)



174.00 ± 29.46

LBDr (kg/kg)



1.90 ± 0.38

CMJ (cm)



20.05 ± 3.46

PAPw (W)



5277 ± 724.4

P:BM (W/kg)



57.01 ± 6.63

Fig. 1

Differences in CMJ (cm) height by quartile (LBDa)

Fig. 2

Differences in PAPw (w) by quartile (LBDa)

Fig. 3

Differences in P:BM (W/kg) by quartile (LBDa)

Table 2

Pairwise effect size data between officers by LBDa groups








Age (years)

− 0.02

− 0.167

− 0.131

− 0.151



HT (cm)




− 0.140

− 0.085


BM (kg)







LBDr (kg/kg)







CMJ (cm)







PAPw (W)







P:BM (W/kg)







aSmall effect for the pairwise comparison

bModerate effect for the pairwise comparison

cLarge effect for the pairwise comparison

Descriptive data for each quartile group based on LBDr, in addition to pairwise comparisons, can be found in Figs. 4, 5, 6. Pairwise comparisons based on ES for this sample are displayed in Table 3. Significant interactions between LBDr groups for CMJ (F3 = 66.12, P < 0.001) and PAPw (F3 = 48.72, P < 0.01) were discovered. In regard to CMJ height, Q1 jumped significantly higher (P < 0.001; ES: large–very large), and a more favorable P:BM (P < 0.001; ES: moderate–large) when compared to all other groups. In contrast, Q1 displayed significantly lower PAPw (ES: small) compared to all other groups. Q2 displayed significantly greater CMJ scores (P < 0.001; ES: moderate–large), and P:BM (P < 0.001; ES: small–large) compared to Q3 and Q4. However, PAPw was found to be significantly lower when compared to groups Q3 (ES: small) and Q4 (P < 0.01; ES: small). Finally, Q3 performed significantly better on the CMJ (P < 0.01; ES: moderate), and PAPw (ES: small) and P:BM (P < 0.001; ES: moderate).
Fig. 4

Differences in CMJ (cm) height by quartile (LBDr)

Fig. 5

Differences in PAPw (W) by quartile (LBDr)

Fig. 6

Differences in P:BM (W/kg) by quartile (LBDr)

Table 3

Pairwise effect size data between officers by LBDr groups








Age (yrs)

− 0.670b

− 0.0897

− 1.303§

− 0.107

− 0.426a

− 0.356a

HT (cm)


− 0.650b

− 0.981b

− 0.288a

− 0.426a

− 0.342a

BM (kg)

− 0.703b

− 1.362c

− 1.816c

− 0.866

− 1.453c

− 0.526a

LBDa (kg)







LBDr (kg/kg)







CMJ (cm)







PAPw (W)

− 0.002

− 0.265a

− 0.393a

− 0.264a

− 0.382a

− 0.102a

P:BM (W/kg)







aSmall effect for the pairwise comparison

bModerate effect for the pairwise comparison

cLarge effect for the pairwise comparison

dVery large effect size for pairwise comparisons

eExtremely large effect size

When analyzing the entire sample, a Pearson’s correlation coefficient reveled significant low-to-moderate positive correlations between LBDa and CMJ height (r = 0.388, P < 0.001), as well as P:BM (r = 0.272, P < 0.001). Furthermore, a large positive correlation was observed between PAPw and LBDa (r = 0.606, P < 0.001). Significant moderate-to-large relationships were also found between LBDr and CMJ (r = 0.556, P < 0.001) and P:BM (r = 0.642, P < 0.001). In addition, low significant relationships were also discovered between LBDr and PAPw (r = 0.149, P < 0.001). When separated into stronger and weaker groups based on LBDa, the results of the Pearson’s moment correlation revealed low significant relationships between LBDa and PAPw in the strongest group, as well as CMJ and P:BM in the weakest group (Table 4). No other significant correlations were observed. When separated into groups by LBDr, significant associations between stronger and weaker officers were discovered (Table 5). Significant moderate–very large relationships between LBDr and all measures of power were discovered in each quartile group.
Table 4

Correlations between LBDa and selected measures of power by group


CMJ (cm)

PAPw (W)

P:BM (W/kg)

Q1 (n = 137)




Q2 (n = 157)

− 0.010


− 0.033

Q3 (n = 129)




Q4 (n = 120)




*P < 0.05

**P < 0.01

Table 5

Correlations between LBDr and selected measures of power by group


CMJ (cm)

PAPw (W)

P:BM (W/kg)

Q1 (n = 30)


− 0.488***


Q2 (n = 253)


− 0.700***


Q3 (n = 133)


− 0.661***


Q4 (n = 127)


− 0.463***


***P < 0.001


The purpose of this study was to investigate the relationships between absolute and relative strength and selected measures of lower body power in a population of law enforcement officers, and to investigate differences between stronger and weaker subgroups. Significant low-to-moderate positive relationships were discovered between LBDa and CMJ height and P:BM. In addition, a large positive relationship was discovered between LBDa and PAPw. Based on these results, the first hypothesis, that significant relationships would exist between lower body power and strength among male law enforcement officers, was accepted. Furthermore, significant differences in CMJ height and PAPw were observed between the strongest officers (Q1) and all other groups. The second strongest group (Q2) performed significantly better on the CMJ than the weakest group and produced significantly more power than weaker groups (Q3 and Q4). Finally, Q3 displayed better PAPw only when compared to the weakest group (Q4). Based on these findings, the authors also accepted the second hypothesis that stronger officers would display greater power than weaker officers. These results suggest that increasing lower body strength, in general, may help improve jumping ability and PAPw among male law enforcement officers. Considering the relationships between LBDa and LBDr and power measures across the groups, only LBDr was significantly and moderately correlated to all power measures. As such, the development of relative strength specifically may improve power output in male law enforcement officers.

The correlations between strength (LBDa) and power reported in this study were moderate. These results are not unexpected, given that strength is a component of power, and relationships have been found in athletic populations. Similar findings were observed by Wisloff et al. (2004) in which strong correlations (r = 0.78, P < 0.02) were observed between maximal strength (1RM squat), sprinting, and jumping height in elite soccer players. However, the results of this study do contrast with those of Dawes et al. [10], who likewise employed a CMJ measure, but did not find a significant relationship between leg/back absolute strength and jump scores (r = 0.425, P > 0.05). A potential reason for these differences may be explained by the sample size differences in the research, especially given that the correlation was higher in the study by Dawes et al. [11]. Although the mean LBDa data for both this study (174.00 ± 29.46 kg) and that reported by Dawes et al. [10] (177.2 ± 29.4 kg) were similar, as were the mean jump heights (50.93 ± 8.78 cm and 55.40 ± 6.7 cm, respectively), the group sizes were notably different (n = 543 and n = 21, respectively). Considering this, when subgroup data were analyzed in this study and the groups became smaller (n = 137, n = 157, n = 129, n = 120), no significant relationships were found. The size of the sample may influence the results, whereby cohort sizes need to be relatively large to find significant differences. Furthermore, only Q3 was significantly different from Q1, suggesting that even though quartiled, there were minimal differences among all the groups. Thus, these results suggest that while significant, LBDa when isolated may have a limited impact on actual changes in CMJ height.

Conversely, the relationships between LBDr and CMJ were significantly different between all subgroups, with both measures also significantly and moderately related within the subgroups. These findings are similar to those observed in athletic populations [1, 29]. The current results suggest that relative strength may be of greater importance than absolute strength in optimizing CMJ height in state patrol officers. Given that vertical jump assessments are common among law enforcement agencies and have been found to be related to risk of injury, illness, academy graduation [13, 24], occupational performance (e.g., sprint ability; body drag velocity; an physical agility test performance) [10, 13, 14, 22], these results are notable.

Finally, it was discovered that, in general terms, stronger officers in both the LBDa and LBDr groups achieved significantly greater CMJ heights and PAPw compared to their weaker counterparts. To the authors’ knowledge, this is the first time that officers of varying strength levels have been compared on measures of lower body performance measured by jump tests. Given the differences observed in lower body power between officers that were stronger in both absolute and relative terms, it is evident that engaging in some form of resistance training to optimize lower body power is warranted. While training studies are limited in this population, Cocke et al. [5] found that a 6-month randomized training program consisting of high intensity–interval style training, plyometrics, and resistance training leads to improvements in lower body power as measured by the CMJ among police cadets [5]. However, while research in this area is limited, engaging in lower body strength training exercises, performing plyometric training and improving one's P:BM is common practice for improving athletic performance [8] and it stands to reason that these methods may also enhance occupational performance in this population.

While the results of this study highlight the importance of strength in relation to lower body power among male law enforcement officers, it is not without limitations. Based on the archival nature of the data collected, the authors were limited to only measuring isometric lower body strength. Future research should aim to use more dynamic measures of strength (i.e., back squat, deadlift, etc.) and their relationships to lower body power in this population. Furthermore, upper body strength (e.g., grip strength) and power may be a limiting factor in performance of the LBD. Future research should investigate the relationships between both upper and lower body strength to determine their impact on occupational performance. Another limitation in this study was a lack of female participants. Due to the low number of female officers that performed this assessment (n = 27), quartile rankings based on sex could not be made. Future investigations should seek to determine if similar relationships exist among female officers. Finally, although self-reported weight has been shown to be an accurate measure of BM in a similar population [14], the ability to actually measure BM using a scale would further ensure the accuracy of this information (especially as it pertains to relative measures).

In conclusion, the findings of the present study suggest that the development of lower body strength may improve jump performance and lower body power among male law enforcement officers due to significant relationships between these qualities. Tactical Strength and Conditioning Coaches (i.e., TSAC-F) can utilize this information to support the incorporation of training methods that will increase both absolute and relative strength within this population. It is important to recognize that although relative strength demonstrates stronger correlations to the CMJ height and PAPw performance than absolute strength, other qualities, such as the ability to rapidly produce force, may have influenced performance in these measures. Therefore, it is recommended that officers also use other forms of resistance training, such as plyometrics, which emphasize the development of reactive strength and eccentric loading via short ground contact times in addition to traditional weight training.


  1. 1.
    Andersen E, Lockie R, Dawes J. Relationship of absolute and relative lower-body strength to predictors of athletic performance in collegiate women soccer players. Sports. 2018;6:106. Scholar
  2. 2.
    Anderson GS, Plecas D, Segger T. Police officer physical ability testing—re-validating a selection criterion. Policing. 2001;24:8–31.CrossRefGoogle Scholar
  3. 3.
    World Medical Asssocaiton. Declaration of Helsinki. Recommendations guiding physicians in biomedical research involving human subjects. J Am Med Assoc. 1997;277:925–6.CrossRefGoogle Scholar
  4. 4.
    Baran K, Dulla J, Orr RM, Dawes J, Pope RR. Duty loads carried by LA Sheriff’s Department deputies. J Aust Strength Cond. 2018;26:34–8.Google Scholar
  5. 5.
    Cocke C, Dawes J, Orr RM. The use of 2 conditioning programs and the fitness characteristics of police academy cadets. J Athl Train. 2016;51(11):887–96.CrossRefGoogle Scholar
  6. 6.
    Cohen P, West SG, Aiken LS. Applied multiple regression/correlation analysis for the behavioral sciences. Maywah: Psychology Press; 2014.CrossRefGoogle Scholar
  7. 7.
    Davis MR, Easter RL, Carlock JM, Longo EA, Smith LM, Dawes JJ, Schilling BK. Self-reported physical tasks and exercise training in Special Weapons and Tactics (SWAT) teams. J Strength Cond Res. 2016;30(11):3242–8.CrossRefGoogle Scholar
  8. 8.
    Dawes J, Lentz D. Methods of developing power to improve acceleration for the non-track athelte. Strength Cond J. 2012;34(6):44–51.CrossRefGoogle Scholar
  9. 9.
    Dawes J, Orr R, Elder C, Rockwell C. Association between body fatness and measures of muscular endurance among part-time swat officers. J Aust Strength Cond. 2014;22(4):33–7.Google Scholar
  10. 10.
    Dawes JJ, Orr R, Elder C, Krall K, Stierli M, Schilling B. Relationship between selected measures of power and strength and linear running speed amongst Special Weapons and Tactics police officers. J Aust Strength Cond. 2015;23(3):23–8.Google Scholar
  11. 11.
    Dawes JJ, Lindsay K, Bero J, Elder C, Kornhauser C, Holmes R. Physical fitness characteristics of high vs. low performers on an occupationally specific physical agility test for patrol officers. J Strength Cond Res. 2017;31(10):2808–15.CrossRefGoogle Scholar
  12. 12.
    Dawes JJ, Orr RM, Flores RR, Lockie RG, Kornhauser C, Holmes R. A physical fitness profile of state highway patrol officers by gender and age. Ann Occup Environ Med. 2017;29:16. Scholar
  13. 13.
    Dawes JJ. Initial fitness testing scores as a predictor of police academy graduaiton. J Aust Strength Cond. 2019;27(4):30–7.Google Scholar
  14. 14.
    Dawes JL, Kukic F, Cvorovic A, Kornhauser C, Holmes R, Orr R. The validity of self-reported measures of height, body mass and BMI in a population of police officers. J Crim Law. 2019;2:4. Scholar
  15. 15.
    Dempsey PC, Handcock PJ, Rehrer NJ. Impact of police body armour and equipment on mobility. App Ergo. 2013;44(6):957–61.CrossRefGoogle Scholar
  16. 16.
    Hopkins WG. Estimating sample size for magnitude-based inferences. Sportscience 2006;10:63–70.
  17. 17.
    Joseph A, Wiley A, Orr R, Schram B, Dawes JJ. The impact of load carriage on measures of power and agility in tactical occupations: a critical review. Int J Environ Res Public Health. 2018;15:1. Scholar
  18. 18.
    Leard JS, Cirillo MA, Katsnelson E, Kimiatek DA, Miller TW, Trebincevic K, Garbalosa JC. Validity of two alternative systems for measuring vertical jump height. J Strength Cond Res. 2007;21(4):1296–9. Scholar
  19. 19.
    Lockie RG, Dawes JJ, Jones MT. Relationships between linear speed and lower-body power with vhange-of-direction speed in National Collegiate Athletic Association Divisions I and II women soccer athletes. Sports. 2018. Scholar
  20. 20.
    Lockie RG, Dawes JJ, Kornhauser CL, Holmes RJ. Cross-sectional and retrospective cohort analysis of the effects of age on flexibility, strength endurance, lower-body power, and aerobic fitness in law enforcement officers. J Strength Cond Res. 2019;33(2):451–8. Scholar
  21. 21.
    Marins EF, Cabistany L, Farias C, Dawes J, Del Vecchio FB. Effects of personal protective equipment on metabolism and performance during an occupational physical ability test for federal highway police officers. J Strength Cond Res. 2018. (Epub ahead of print).CrossRefPubMedGoogle Scholar
  22. 22.
    Moreno MR, Dulla JM, Dawes JJ, Orr RRM, Cesario K, Lockie RG. Lower-body power and its relationship with body drag velocity in law enforcement recruits Int. J Exer Sci. 2019;12(4):847–58.Google Scholar
  23. 23.
    Muirhead HOR, Schram B, Kornhauser C, Holmes R, Dawes JJ. The relationship between fitness and marksmanship in Police Officers. Safety. 2019;5(3):54. Scholar
  24. 24.
    Orr R, Pope R, Peterson S, Stierli SM, Hinton B. Leg power as a predictor of injury & illness risk in police recruits Int. J Environ Res Public Health. 2016;13(2):237.CrossRefGoogle Scholar
  25. 25.
    Orr RM, Dawes JJ, Pope R, Terry J. Assessing differences in anthropometric and fitness characteristics between police academy cadets and incumbent officers. J Strength Cond Res. 2018;32(9):2632–41. Scholar
  26. 26.
    Orr RM, Kukić F, Čvorović A, Koropanovski N, Janković R, Dawes J, Lockie R. Associations between fitness measures and change of direction speeds with and without occupational loads in female police officers. Int J Enviro Res Pub Hlth. 2019;16(11):1947.CrossRefGoogle Scholar
  27. 27.
    Sayers SP, Harackiewicz DV, Harman EA, Frykman PN, Rosenstein MT. Cross-validation of three jump power equations. Med Sci Sports Exerc. 1999;31:572–7.CrossRefGoogle Scholar
  28. 28.
    Sörensen L, Smolander J, Louhevaara V, Korhonen O, Oja P. Physical activity, fitness and body composition of Finnish police officers: a 15-year follow-up study. Occup Med. 2000;50:3–10.CrossRefGoogle Scholar
  29. 29.
    Tramel W, Lockie RG, Lindsay KG, Dawes JJ. Associations between absolute and relative lower body strength to measures of power and change of direction speed in Division II female volleyball players. Sports. 2019;7:160.CrossRefGoogle Scholar
  30. 30.
    Wisløff U, Castagna C, Helgerud J, Jones R, Hoff J. Strong correlation of maximal squat strength with sprint performance and vertical jump height in elite soccer players. Br J Sports Med. 2004;38(3):285–8.CrossRefGoogle Scholar

Copyright information

© Beijing Sport University 2019

Authors and Affiliations

  • J. Jay Dawes
    • 1
    Email author
  • Robert G. Lockie
    • 2
  • Charles L. Kornhauser
    • 3
  • Ryan J. Holmes
    • 3
  • Robin M. Orr
    • 4
  1. 1.School of Kinesiology, Applied Health, and RecreationOklahoma State UniversityStillwaterUSA
  2. 2.Department of KinesiologyCalifornia State University, FullertonFullertonUSA
  3. 3.Colorado State Patrol, Training AcademyLakewoodUSA
  4. 4.Tactical Research UnitBond UniversityRobinaAustralia

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