Konstantin Warneke1,2*
Carl-Maximilian Wagner3
Michael Keiner3
Martin Hillebrecht4
Stephan Schiemann1
David George Behm2
Sebastian Wallot5
Klaus Wirth6
- 1Department for Exercise, Sport and Health, Leuphana University Lüneburg, Lüneburg, Germany
- 2School of Human Kinetics and Recreation, Memorial University of Newfoundland, St. Johns, NL, Canada
- 3Department of Training Science, German University of Health and Sport, Berlin, Baden-Württemberg, Germany
- 4University Sports Center, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
- 5Institute of Psychology, Leuphana University Lüneburg
- 6Faculty of Training and Sports Science, University of Applied Science Wiener Neustadt, Vienna, Austria
Measuring maximal strength (MSt) is a very common performance diagnoses, especially in elite and competitive sports. The most popular procedure in test batteries is to test the one repetition maximum (1RM). Since testing maximum dynamic strength is very time consuming, it often suggested to use isometric testing conditions instead. This suggestion is based on the assumption that the high Pearson correlation coefficients of r ≥ 0.7 between isometric and dynamic conditions indicate that both tests would provide similar measures of MSt. However, calculating r provides information about the relationship between two parameters, but does not provide any statement about the agreement or concordance of two testing procedures. Hence, to assess replaceability, the concordance correlation coefficient (ρc) and the Bland-Altman analysis including the mean absolute error (MAE) and the mean absolute percentage error (MAPE) seem to be more appropriate. Therefore, an exemplary model based on r = 0.55 showed ρc = 0.53, A MAE of 413.58 N and a MAPE = 23.6% with a range of −1,000–800 N within 95% Confidence interval (95%CI), while r = 0.7 and 0.92 showed ρc = 0.68 with a MAE = 304.51N/MAPE = 17.4% with a range of −750 N–600 N within a 95% CI and ρc = 0.9 with a MAE = 139.99/MAPE = 7.1% with a range of −200–450 N within a 95% CI, respectively. This model illustrates the limited validity of correlation coefficients to evaluate the replaceability of two testing procedures. Interpretation and classification of ρc, MAE and MAPE seem to depend on expected changes of the measured parameter. A MAPE of about 17% between two testing procedures can be assumed to be intolerably high.
Introduction
Producing high maximal strength is of crucial importance to reach high level performance in many sports such as American football and rugby (1–6), basketball (7–11) handball (12–14), soccer (15–20) swimming (21–23), track and field in sprints, jumps, and throws (24–26) or powerlifting and weightlifting (27–29). Additionally, previous research showed differences regarding strength and speed strength capacities between elite, sub-elite, amateur, and youth athletes (30, 31). Commonly, strength training leads to improved maximal strength and speed strength performance (e.g., sprinting, jumping, rapidly performed directional changes) (24, 32–35).
Especially in elite sports and competitive sports, the effectiveness of training routines is evaluated with performance testing (36) to monitor training progress (24) and, if necessary, adapt training routines. Various methods have been utilized to measure maximal strength using a maximal voluntary contraction (MVC), among which isometric (MVIC) or dynamic testing procedures using the one repetition maximum (1RM) are most common (24, 27, 37).
Advocates of isometric testing highlight the supposed advantages regarding the quantification of various force-time characteristics (1, 38–40), a simple and time efficient administration (1) and a good standardization of test conditions with high test-retest reliability (36, 41). Furthermore, isometric strength tests are considered highly sensitive to changes in strength while possessing minimal coordination requirements, minimal injury risk, and being supposedly less fatiguing than 1RM test protocols (27, 36, 42).
Additionally, measuring force-time characteristics like rate of force development (RFD) or isometric impulse is considered to provide information on various dynamic strength qualities (24, 43). However, dynamic strength measurements using the one repetition maximum (1RM) is stated as the most popular strength assessment method, because no expensive equipment such as a force plates or strain gauges are required (44). Since good reliability can be assumed (Seo et al., 2012), there are a substantial number of studies investigating the 1RM in bench press, back squat or the clean (18, 45–61). To date, there is conflicting evidence about the external validity of various strength testing methods (62), especially when considering the associations between isometric and dynamic performances (43, 63–66). Training and testing specificity (i.e., testing should involve tasks similar to the task or type of training) has been a hallmark of sport and exercise science (67).
Accordingly, a potentially higher transfer of dynamic testing measures towards speed strength performances like sprinting, jumping, rapidly performed directional changes (e.g., agility) seems rational (63, 64, 68). Additionally, 1RM testing provides comparable reliability to isometric testing, with a higher validity to estimate maximal strength capacity (36).
Problem
Still, based on the supposed advantages of isometric testing conditions and the additional information on force-time characteristics testing has led multiple authors to suggest substituting 1RM testing with isometric testing to monitor athletes' training progress (1, 24) McGuigan et al. (69) state; “Given that the test seems to indicate to a large extent the dynamic performance characteristics of athletes, it may not be necessary to perform 1RM testing on a large number of exercises”. While isometric tests appear to provide valuable information on force-time characteristics, the replaceability of dynamic testing conditions through isometric testing is primarily justified by “high” Pearson's correlation coefficients (r) or intraclass correlation coefficients (ICC). McGuigan et al. (1) also proposed that “Strength and conditioning coaches and other practitioners with access to a force plate can consider using the isometric mid-thigh pull test as a potential alternative to traditional 1RM testing. In recreationally trained subjects, it appears to correlate extremely well with both the 1RM squat and bench press”. Therefore, a high number of studies were found (see Table 1) highlighting the correlation between isometric and dynamic testing conditions. However, to validly claim the potential substitution of dynamic testing conditions for isometric testing within performance diagnostic protocols, a high concordance between methods must be assumed. But none of the studies in the literature calculated concordance correlation coefficients between isometric and dynamic measurements to verify whether one measurement can actually reproduce the results of the other. This is especially of high importance if the replacement of 1RM bench press testing by isometric mid-thigh pull is suggested (69), which seems to be of questionable validity. Hence, the primary aim of this study is to assess the validity of replacing 1RM with isometric testing by comparing Pearson and concordance correlation coefficients. Moreover, to provide more detailed information the mean absolute error (MAE) and mean absolute percentage error (MAPE) will be provided to detect differences between isometric and dynamic testing.
Table 1. studies showing significant correlation coefficients between isometric and dynamic strength testing.
Table 2. Correlation coefficients in combination with concordance and variance analysis including MAE, MAPE and maximal percentage error.
Table 3. Examples of angle specificity of squat force output
Critical evaluation of commonly performed concordance determination
Investigating the concordance between two measurement devices is a well-known problem in medicine (85–88). In the literature, just stating correlation coefficients seems to be insufficient, since agreement and correlations are two different concepts (89). Since they can be assumed to be conceptually different, using the method to calculate correlations must be considered inappropriate or inadequate to investigate agreement “Agreement is a concept that is closely related to, but fundamentally different from and often confused with correlation.” (89). To investigate the agreement of measurements, a high reproducibility is required. The assumption that both measurement devices measure the same parameter needs to be validated with the deviation between the two devices determined to estimate the concordance or lack of concordance. Pearson correlation coefficients only describe the relationship between two parameters but do not provide any information about the agreement between two testing conditions (85, 88). The concordance correlation coefficient can be used instead, assuming a 45° line crossing the origin of the coordinative system and determining the concordance to the regression line of the Pearson correlation (88, 90–92). Furthermore, assuming two testing methods would measure the same parameter, there should be very little variance between them. To illustrate the level of variance between two testing conditions, Bland-Altman Analysis is recommended (85–87, 89, 90, 93). Since the Bland-Altman Plot can be used only for qualitative and visual analysis of variance, the MAE and MAPE are used for quantitative calculation error between both testing conditions. The MAE is stated as a measuring of errors between paired observations evaluating the same parameter (94, 95), while the MAPE (96–98) can be seen as an expression of accuracy, providing quantitative information about the deviation between two measuring techniques. Therefore, both parameters can be stated to investigate the difference between a measured and predicted parameter and were further used to validate testing batteries (99, 100). In other research fields, such as pharmacology and medicine, using the concordance correlation coefficient and Bland-Altman analysis is very common to evaluate the accuracy, validity, and reliability of blood pressure or heart rate devices (91, 92, 101). Since there are no common classifications in high, moderate, and low concordance as found with Pearson correlations (e.g., r = 0.2–0.5 small, r > 0.5–0.7 moderate, r > 0.7 high correlation) (102), it is suggested to classify those effects dependent on content. Assuming moderate increases in maximal strength of for example, 10%–12% within six weeks of training (103), 13.3% within 10 months in elite soccer player (U19) (35) or 12 ± 2%–19 ± 2% in elite cross-country skiers following 12 weeks of strength training (104), the possibility of replacing 1RM testing with isometric testing requires a high concordance with very little variance, rived from the MAPE. If two tests have a concordance variation of 6% but the training-induced change was 12%–13%, there would be an approximate 50% difference in the strength estimate between the two measures, which would not provide acceptable sensitivity or validity. Accordingly, Dominguez-Jiménez et al. (105) described poor concordance in blood sample measuring devices with concordance correlation coefficients of 0.68–0.8, suggesting that the border for poor agreement with concordance correlation coefficients would be <0.9 (106).
Consequently, assuming high correlation coefficient, the calculation of the concordance correlation coefficient and Bland-Altman analysis including MAPE, and MAE were carried out assuming r = 0.9 and r = 0.7. Data were compiled and added from previous investigations. The MAE was determined using, n = number of participants, xi = the isometric strength value, and yi = dynamic strength value
and the mean absolute percentage error (MAPE) using
Results of this exemplary calculation shows that correlations stated as high (r ≥ 0.7), which are partially higher than the stated correlations in literature with r = 0.52–0.97 (7, 48, 69, 79, 80, 107) seem not to be sufficient to evaluate the replaceability of dynamic testing conditions with isometric testing. Expecting increases between 10%–19% with a strength training program of 6–24 weeks, a MAPE between isometric and dynamic testing of 7%–17% seems to be intolerably high, considering scientific quality criteria (see Table 2). Therefore, both measurement techniques seem to be reliable and valid to estimate specific metrics of maximal strength capacity, however, it must be assumed that they estimate the maximal strength capacity in different ways, providing different results. The rationale to replace 1RM tests with isometric testing conditions (69, 69) must therefore be rejected. The Bland-Altman analysis in Figure 1 showing a variation of values from −200–450 N for r = 0.92, in Figure 2 with −750 N–600 N for r = 0.7 and −1,000–800 N for r = 0.55 within the 95% CI, underpin the assumption of substantially different strength value estimates by isometric vs. dynamic testing conditions. Although Pearson correlation coefficients and ICC values examine the relationship between two parameters, using these common correlation classifications to examine the replaceability of two measurements must be described as a misinterpretation of statistics and should be avoided. In accordance with Cohen (1988), classification of effect sizes should be considered in the light of content. Accordingly, stated substantial higher borders made by Cataldi et al. (106) considering a cutoff of poor (<0.90), moderate (0.90–0.95), substantial (0.95–0.99), and almost perfect (>0.99) seems more appropriate because of reduced errors between the different measurements.
Figure 1. An exemplary dataset to calculate the concordance correlation coefficient (CCC) of 0.9 with n = 273 showing high Pearson correlation with r = 0.92, representing magnitude of correlation usually found between dynamic and isometric testing.
Figure 2. An exemplary dataset to calculate the concordance correlation coefficient (CCC) of 0.68 with n = 273 showing high Pearson correlation with r = 0.7, representing magnitude of correlation usually found between dynamic and isometric testing.
Figure 3. An exemplary dataset to calculate the concordance correlation coefficient (CCC) of 0.53 with n = 273 showing moderate Pearson correlation with r = 0.55, representing magnitude of correlation usually found between dynamic and isometric testing.
There are few studies that include a concordance analysis to investigate minimizing differences in maximal strength testing batteries. Warneke et al. (108) examined the plantar flexors, showing moderate to high correlation coefficients of 0.63–0.77 leading to ρc = 0.62–0.77 Accordingly, Wagner et al. (109) pointed out that there was only little agreement between isometric and dynamic squat, determining correlations of τ = 0.54, MAE of 2080.87 N and MAPE of 67.4%. However, correlated maximal strength values were assessed using different joint angles, so the influence of contraction type could not be excluded. No further investigations could be detected using concordance analyses to assess the agreement between two testing conditions.
To conclude, if the expected change in maximal strength due to the intervention is smaller than the mean (percentage) error between two testing methods, it cannot be assumed that both testing method measure the same parameter and a replacement of one of both testing methods should be avoided. Therefore, the objective of an investigation and the chosen procedure to evaluate strength capacity should be selected carefully, as it can be assumed that 1RM and isometric testing conditions will not measure the same parameter. There are some hypotheses explaining differences in strength values dependent on measurement procedure.
Explanation of high variation of correlation coefficients and limited agreement between isometric and dynamic testing procedure
From a physical and mechanical point of view, force is defined as F = m * a, so force capability can be described as the ability of the body to accelerate a mass. Maximal strength in a dynamic strength measurement is only assumed to be maximal if the gravitational force acting on the resistance and the force output exerted on the resistance by the individual are equal, so no movement or acceleration of the mass (resistance) would be present. With isometric force measurements, Newton's third principle [for every action (force) in nature there is an equal and opposite reaction] is used to measure the opposing force to an insurmountable resistance. Since performing a one repetition maximum involves moving a surmountable resistance through a range of motion, it is not the same as assessing maximal strength/MVC, leading to the assumption that the 1RM performance would be lower than MVIC. Furthermore, when performing a 1RM, once the initial sticking point is surpassed, the force to move the weight decreases due to inertia (110). In contrast, there are limitations of isometric testing conditions, described in the following.
Angle specificity in isometric testing conditions
In science and diagnostics, there are high demands on standardization to ensure equal testing conditions and exclude external factors influencing the results. Angle specificity of maximal isometric strength produces different maximal strength values when performed at different joint angles (44, 62, 71, 111, 112). Angle specific differences in maximal strength were reported for the squat (44, 113–116), bench press (65), plantar flexion (115) and deadlift/mid-thigh pull (81). It seems that strength capacity using isometric squat and leg press increases with increasing knee joint (44, 113–116). Examples are stated in Table 3.
The 1RM bench press, back squat and clean are the most common methods of assessing maximum strength in athletes (116–120). Using dynamic testing conditions, standardization is mostly performed for range of motion (69). The squat ROM varies between different studies (mostly 70–110°) (Table 1), (36, 44, 73, 121, 122).
Using different joint angles to standardize movements is of questionable validity as similar levels of flexibility and anthropometrics would be assumed. Participants lacking flexibility could reach maximal muscle length in a smaller joint angle compared to flexibility trained participants. Consequently, assuming a muscle length-maximal strength relationship with highest strength capacity in the “mid-range of motion” (126), standardization in joint angles lead to differences in starting muscle length, if participants demonstrate heterogeneity in flexibility. Furthermore, there are angle dependent differences in EMG- activity, contributing to differences in strength performance (127). Obviously, joint angle dependency for MVIC values leads to a joint angle dependency for correlations between isometric and dynamic MVC testing. Accordingly, Bazyler et al. (107) reported an angle specific high correlation (r = 0.79–0.86) in maximal isometric strength with 1RM in the squat indicating that “these findings demonstrate a degree of joint angle specificity to dynamic tasks for rapid and peak isometric force production” (107). However, obviously, there are numerous other factors influencing the force output. The aforementioned difficulties with standardization of testing range of motion and angles with indivuduals with varying levels of flexibility would be problematic not only for closed chain activities (e.g., squat, cleans, deadlifts) but also open kinetic chain exercises such as found with machines for knee extension (quadriceps) and flexion (hamstrings) or elbow flexion (biceps brachii) and extension (triceps brachii). Furthermore, compared to these uni-articular (e.g, knee extensions, bicep curls and others) resistance exercises, the complexity, co-ordination, balance, and stability associated with multi-joint movements will influence the force production leading to higher standardization problems.
Familiarization with testing conditions
Another possible explanation is a lack of familiarization to isometric testing conditions (23, 76) due to structural, neural, and biomechanical differences within isometric and dynamic testing conditions associated with the distinct movement patterns and contraction modes (63, 64, 128). Accordingly, Baker et al. (43) suggested that isometric and dynamic muscle actions must be understood as different physiological phenomenon as motor unit recruitment and rate coding (firing frequency) may differ between both contraction forms. Authors pointed out that three familiarization sessions or a large number of trials (129) were required to get a high stability and reliability for peak force measurement. Palmer et al. (130) reported the relatively high coefficients of variation of 6.6%–19.4% for isometric squat strength were dependent on the knee angle. These high coefficients of variation may be the result of learning to contract under isometric conditions. Unfamiliar testing conditions can influence test quality criteria, consequently, reliability of isometric testing is not always reached (131). Since it can be assumed that most athletes are familiar with dynamic conditions because of daily use in training context, it can be hypothesized that for most athletes there is habituation regarding unfamiliar testing conditions. Lum et al. (24) point out that many studies investigating relationships between dynamic and isometric conditions do not provide any information about the number of familiarization sessions prior to isometric testing. This may explain the nearly perfect correlations shown by McGuigan et al. (1) when testing wrestlers, where a high proportion of daily training involves isometric work. Taken together, the range of correlation (r = 0.35–0.99) (25, 80) can be attributed to several limitations in standardization and familiarization of participants. The familiarization of testing conditions and contraction velocity specificity (67) might influence the differences in correlations between testing conditions in different sports such as soccer (18–20), basketball (8, 132) and weightlifting (133–134). Therefore, it could be hypothesized that the type of contraction used in daily training routines would influence the force output in isometric and dynamic testing, and therefore the resulting correlations between both contraction types. However, the sports-dependency regarding the force output of isometric vs. dynamic testing conditions requires further research.
Relevance for the testing practice
Several factors influencing the estimation of maximal strength can lead to significant errors dependent on testing conditions in cross sectional study designs. Since high specificity in training regimes can be assumed (67) a question arises about the impact on results of longitudinal testing designs. Accordingly, using isometric testing conditions, Yahata et al. (115) showed significant increases in MVIC using an extended muscle length in response to long-term stretch training. As it can be assumed that the training routine took place with longer muscle length, training adaptations and strength changes were also specific to training conditions. However, comparing isometric and dynamic testing conditions, significant differences in response to training stimuli would be expected. Warneke et al., (135) showed significant increases in strength capacity under isometric as well as dynamic conditions using six weeks of daily stretch training in the calf muscles. However, under isometric testing conditions there was a significant increase of 16.8%, while 1RM testing showed significant increases of about 25.1%. Furthermore, in 1RM testing a significant contralateral force transfer was present (+11.4%), which was not significant under isometric conditions (+1.4%). Wirth (136) investigated the effects of different weekly training frequencies on maximal dynamic and isometric maximal strength with the biceps brachii muscles. While dynamic testing conditions showed significant increases in 5 of 6 training groups, only one group showed significant increases in MVIC.
Consequently, if Yahata and colleagues (115) would test MVIC exclusively using small joint angles or Wirth (136) tested only MVIC, both studies would underestimate effects of the training routine because of inappropriate testing conditions. Furthermore, Warneke et al. (135) were not able to show a significant contralateral force transfer using daily stretch training, if following the advice to replace 1RM testing by isometric testing. Therefore, the different tests should not be replaceable, but supplement one testing condition with the other. Thus, both testing conditions only estimate MSt capacity, since in both procedures, limitations avoid a “real” maximal force output. Therefore, it is strongly recommended to keep in mind high specificity of testing and training conditions considering the physiological background of each when figuring out the research hypothesis and the following testing protocol.
Conclusion
The use of correlation coefficients to justify the replaceability of 1RM testing with isometric testing seems invalid, since the MAPE and MAE between both measurement procedures is intolerably high, even when high correlation coefficients with high sample sizes were used. Investigating the agreement between two measurement conditions requires further analytic approaches, such as concordance- and Bland-Altman analyses with classification of MAPE and MAE values. Investigations considering adequate analyses are very rare in exercise science. Results showing that both 1RM and MVIC present a different estimation of the maximal strength capacity of the participant. Therefore, assuming there are equivalent measures between dynamic performance and isometric testing conditions (24, 84) should be questioned. This estimation can be assumed to be influenced by very different factors such as tested muscle lengths in isometric testing, complexity of the movement in dynamic testing as well as familiarization with the testing conditions considering the type of contractions used in daily training practice.
Practical applications
Using maximal strength tests in practice—performance diagnostics in sports or pre-post-test designs in scientific studies—authors should consider limitations which should be minimized. Since a higher transfer of 1RM to sport specific movements can be assumed and most athletes using dynamic movements in their daily training routines, a higher application of dynamic testing protocols can be hypothesized in field tests (64, 109) “From this, it could be recommended to use dynamic strength testing and avoid isometric strength testing, if the athletes training routine includes only low level of isometric contractions, and vice versa.” (109). However, under laboratory conditions and dependent on the research questions, isometric procedures can also be useful, especially because of time-saving aspects. Whether, and to what extent isometric testing conditions can considered safe might depend on the tested movement. Safety benefits of the isometric squat, pushing the spine against an unyielding resistance may be questionable, while in other movements such as the plantar flexion, the isometric measurement seems to be a safe testing condition. High test specificity (often involves dynamic testing) and relevant physiological issues (often necessitates isometric testing) should be included in the testing design to answer research questions adequately. To avoid missing potential training effects, authors and coaches should be aware of the underlying physiological mechanisms of their training to determine target-oriented testing programs, otherwise there are too many parameters (e.g., different joint angles) to consider, if all possible movement executions should be tested.
Author contributions
KW1 performed the analytic calculations and took the lead in writing the manuscript with support from CMW and MK, KW1, MH and KW2 conceived the main conceptual ideas in consultation with DB and SS. KW2 and SW supervised the statistical analysis and provided critical feedback to the design of the study and the statistical analysis. All authors discussed the results and contributed to the final version of the manuscript. All authors contributed to the article and approved the submitted version.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
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References
1. McGuigan MR, Newton MJ, Winchester JB, Nelson AG. Relationship between isometric and dynamic strength in recreationally trained men. Strength Cond Res. (2010) 24(9):2570–3. doi: 10.1519/JSC.0b013e3181ecd381
2. Fry AC, Kreamer WJ. Physical performance characteristics of American collegiate football players. J Appl Sport Sci Res. (1991) 5(3):126–38. https://secure.footprint.net/gatorade/prd/gssiweb/sf_libraries/sse-docs/hoffman_sse_143-4-27-15-final.pdf?sfvrsn=4
3. Wang R, Hoffman JR, Tanigawa S, Miramonti AA, la Monica MB, Beyer KS, et al. Isometric mid-thigh pull correlates with strength, sprint, and agility performance in collegiate rugby union players. J Strength Cond Res. (2016) 30(11):3051–6. doi: 10.1519/JSC.0000000000001416
4. Barr MJ, Sheppard JM, Agar-Newman DJ, Newton RU. Transfer effect of strength and power training to the sprinting kinematics of international rugby players. J Strength Cond Res. (2014) 28(9):2585–96. doi: 10.1519/JSC.0000000000000423
5. Barr MJ, Sheppard JM, Agar-Newman DJ, Newton RU. Transfer effect of strength and power training to the sprinting kinematics of international rugby players. J Strength Cond Res. (2014) 28(9):1585–2596. doi: 10.1519/JSC.0000000000000423
6. Comfort P, Haigh A, Matthews MJ. Are changes in maximal squat strength during preseasion training reflexted in changes in sprint performance in rugby league players? J Strength Cond Res. (2012) 26(3):772–6. doi: 10.1519/JSC.0b013e31822a5cbf
7. Spiteri T, Nimphius S, Hart NH, Specos C, Sheppard JM, Newton RU. Contribution of strength characteristics to change of direction and agility performance in female basketball athletes. J Strength Cond Res. (2014) 28(9):2415–23. doi: 10.1519/JSC.0000000000000547
8. Warneke K, Keiner M, Lohmann LH, Hillebrecht M, Wirth K, Schiemann S. The influence of maximum strength performance in seated calf raises on counter movement jump and squat jump in elite junior basketball players. Sport Mont. (2022) 20:3–8. doi: 10.26773/smj.220610
9. Alemdaroğlu U. The relationship between muscle strength, anaerobic performance, agility, sprint ability and vertical jump performance in professional basketball players. J Hum Kinet. (2012) 31:149–58. doi: 10.2478/v10078-012-0016-6
10. Yáñez-García JM, Rodríguez-Rossel D, Mora-Custodio R, González-Badillo JJ. Changes in muscle strength, jump, and sprint performance in young elite basketball players: the impact of combined high-speed resistance training and plyometrics. J Strength Cond Res. (2022) 36(2):478–85. doi: 10.1519/JSC.0000000000003472
11. Guimarães E, Maia JAR, Williams M, Sousa F, Santos E, Tavares F, et al. Muscular strength spurts in adolescent male basketball players: the INEX study. Int J Environ Res Public Health. (2021) 18(2):776. doi: 10.3390/ijerph18020776
12. Bragazzi NL, Rouissi M, Hermassi S. Resistance training and handball players’ isokinetic, isometric and maximal strength, muscle power and throwing ball velocity: a systematic review and meta-analysis. Int J Environ Res Public Health. (2020) 17(8):2663. doi: 10.3390/ijerph17082663
13. Hermassi S, Chelly MS, Fieseler G, Bartels T, Schulze S, Delank KS, et al. Effects of in-season explosive strength training on maximal leg strength, jumping, sprinting, and intermittent aerobic performance in male handball athletes. Sportverletzung-Sportschaden. (2017) 31(3):167–73. doi: 10.1055/s-0043-103469
14. Pereira LA, Nimphius S, Kobal R, Kitamura K, Turisco LAL, Orsi RC, et al. Relationship between change of direction, speed, and power in male and female national olympic team handball athletes. J Strength Cond Res. (2018) 32(10):2987–94. doi: 10.1519/JSC.0000000000002494
15. Requena B, González J, González-Badillo G, Saez E, de Villareal S, Ereline J, et al. Functional performance, maximal strength and power characteristics in isometric and dynamic actions of lower extremities in soccer players. J Strength Cond Res. (2009) 23(5):1391–401. doi: 10.1519/JSC.0b013e3181a4e88e
16. Beato M, Maroto-Izquierdo S, Turner AN, Bishop C. Implementing strength training strategies for injury prevention in soccer: scientific rationale and methodological recommendations. Int J Sports Physiol Perform. (2021) 1(3):456–61. doi: 10.1123/ijspp.2020-0862
17. Fousekis K, Tsepis E, Poulmedis P, Athanasopolous S, Vagenas G. Intrinsic risk factors of non-contract quadriceps and hamstring strains in soccer: a prospective study of 100 progressional players. Br J Sports Med. (2011) 45(9):709–14. doi: 10.1136/bjsm.2010.077560
18. Keiner M, Kadlubowksi B, Hartmann H, Wirth K. The influence of maximum strength performance in squats and standing calf raises on squat jumps, drop jumps, and linear and change of direction sprint performance in youth soccer players. Int J Sports Exerc Med. (2021) 7(2):190. doi: 10.23937/2469-5718/1510190
19. Kadlubowski B, Keiner M, Stefer T, Kapsecker A, Hartmann H, Wirth K. Influence of linear-sprint performance, concentric power and maximum strength on change of direction performance in elite youth soccer players. Ger J Exerc Sport Res. (2021) 51(1):116–21. doi: 10.1007/s12662-020-00692-5
20. Keiner M, Brauner T, Kadlubowski B, Sander A, Wirth K. The influence of maximum squatting strength on jump and sprint performance: a cross-sectional analysis of 492 youth soccer players. Int J Environ Res Public Health. (2022) 19(10):5835. doi: 10.3390/ijerph19105835
21. Crowley E, Harrison AJ, Lyons M. The impact of resistance training on swimming performance: a systematic review. Sports Med. (2017) 47:2285–307. doi: 10.1007/s40279-017-0730-2
22. Lum D, Barbosa TM. Effects of strength training on olympic time-based sport performance: a systematic review and meta-analysis of randomized controlled trials. Int J Sports Physiol Perform. (2019) 14(10):1318–30. doi: 10.1123/ijspp.2019-0329
23. Wirth K, Keiner M, Fuhrmann S, Nimmerichter A, Haff GG. Strength training in swimming. Int J Environ Res Public Health. (2022) 19(9):5369. doi: 10.3390/ijerph19095369
24. Lum D, Haff GG, Barbosa TM. The relationship between isometric force-time characteristics and dynamic performance: a systematic review. Sports. (2020) 8(5):63. doi: 10.3390/sports8050063
25. Nuzzo JL, McBride JM, Cormie P, McCaulley GO. Relationship between countermovement jump performance and multijoint isometric, and dynamic tests of strength. J Strength Cond Res. (2008) 22(3):699–707. doi: 10.1519/JSC.0b013e31816d5eda
26. Ojanen T, Rauhala T, Häkkinen K. Strength and power profiles on the lower and upper extremities in master throwers at different ages. J Strength Cond Res. (2007) 21(1):216–22. doi: 10.1519/00124278-200702000-00039
27. Beckham G, Mizuguchi S, Carter C, Sato K, Ramsex M, Lamont H, et al. Relationships of isometric mid-thigh pull variables to weightlifting performance. J Sports Med Phys Fitness. (2013) 53(5):573–81. PMID: 23903539
28. Vizcaya FJ, Viana O, Del Olmo MF, Acero RM. Could the deep squat jump predict weightlifting performance? J Strength Cond Res. (2009) 23(3):729–34. doi: 10.1519/JSC.0b013e3181a04dc3
29. Stone MH, Sands WA, Pierce KC, Carlock J, Cardinale M, Newton R. Relationship of maximum strength to weightlifting performance. Med Sci Sports Exerc. (2005) 37(6):1037–43. PMID: 1594773
30. Keiner M, Sander A, Wirth K, Hartmann H. Differences in the performance tests of the fast and slow stretch and shortening cycle among professional, amateur and elite youth soccer players. J Hum Sport Exerc. (2015) 10(2):563–70. doi: 10.14198/jhse.2015.102.03
31. Keiner M, Kapsecker A, Stefer T, Kadlubowski B, Wirth K. Differences in squat jump, linear sprint, and change-of-direction performance among youth soccer players according to competitive level. Sports. (2021) 9(11):149. doi: 10.3390/sports9110149
32. Suchomel TJ, Nimphius S, Stone MH. The importance of muscular strength in athletic performance. Sports Med. (2016) 46:1419–49. doi: 10.1007/s40279-016-0486-0
33. Thomas C, Comfort P, Chiang CY, Jones PA. Relationship between isometric mid-thigh pull variables and sprint and change of direction performance in collegiate athletes. J Trainology. (2015) 4(1):6–10. doi: 10.17338/trainology.4.1_6
34. Keiner M, Sander A, Wirth K, Schmidtbleicher D. Long-term strength training effects on change-of-direction sprint performance. J Strength Cond Res. (2014) 28(1):223–31. doi: 10.1519/JSC.0b013e318295644b
35. Keiner M, Kadlubowski B, Sander A, Hartmann H, Wirth K. Effects of 10 months of speed, functional, and traditional strength training on strength, linear sprint, change of direction, and jump performance in trained adolescent soccer players. J Strength Cond Res. (2022) 36(8):2236–46. doi: 10.1519/JSC.0000000000003807
36. Lynch AE, Davies RW, Jakeman PM, Locke T, Allardyce JM, Carson BP. The influence of maximal strength and knee angle on the reliability of peak force in the isometric squat. Sports. (2021) 9(10):140. doi: 10.3390/sports9100140
37. Buckner SL, Jessee MB, Mattocks KT, Grant Mouser J, Counts BR, Scott JD, et al. Determining strength: a case for multiple methods of measurement. Sports Med. (2016) 47:193–5. doi: 10.1007/s40279-016-0580-3
38. Lum D, Haff GG, Barbosa TM. The relationship between isometric force-time characteristics and dynamic performance: a systematic Review. Sports. (2020) 8(5):63. doi: 10.3390/sports8050063
39. Vitalsalo JT, Aura O. Seasonal fluctuations of force production in high jumpers. Can J Appl Sport Sci. (1984) 9(4):209–13. PMID: 6525754
40. Häkkinen K, Komi PV, Kauhanen H. Electromyographic and force production characteristics of leg extensor muscles of elite weight lifters during isometric, concentric and varoius stretch.shortening cycle exercises. Int J Sports Med. (1986) 7(3):144–51. doi: 10.1055/s-2008-1025752
41. Drake D, Kennedy R, Wallace E. The validity and responsiveness of isometric lower body multi-joint tests of muscular strength: a systematic review. Sports Med Open. (2017) 3(1):23. doi: 10.1186/s40798-017-0091-2
42. Young KP, Haff GG, Newton RU, Sheppard JM. Reliability of a novel testing protocol to assess upper-body strength qualities in elite athletes. Int J Sports Physiol Perform. (2014) 9(5):871–5. doi: 10.1123/ijspp.2013-0332
43. Baker D, Wilson G, Carlyon B. Generality versus specificity: a comparison of dynamic and isometric measures of strength and speed-strength. Eur J Appl Physiol. (1994) 68(4):350–5. doi: 10.1007/BF00571456
44. McMaster DT, Gill N, Cronin J, McGuigan M. A brief review of strength and ballistic assessment methodologies in sport. Sports Medicine. (2014) 44:603–23. doi: 10.1007/s40279-014-0145-2
45. Keiner M, Sander A, Wirth K, Caruso O, Immesberger P, Zawieja M. Strength performance in youth: trainability of adolescents and children in the back and front squats. J Strength Cond Res. (2013) 27(2):357–62. doi: 10.1519/JSC.0b013e3182576fbf
46. Delgado J, Drinkwater EJ, Banyard HG, Haff GG, Nosaka K. Comparison between back squat, Romanian deadlift, and barbell hip thrust for leg and hip muscle activities during hip extension. J Strength Cond Res. (2019) 33(10):2595–601. doi: 10.1519/JSC.0000000000003290
47. Kompf J, Arandjelović O. The sticking point in the bench press, the squat, and the deadlift: similarities and differences, and their significance for research and practice. Sports Medicine. (2016) 47(4):631–40. doi: 10.1007/s40279-016-0615-9
48. Markovic G, Dizdar D, Jukic I, Cardinale M. Reliability and factorial validity of squat and countermovement jump tests. J Strength Cond Res. (2004) 18(3):551–5. doi: 10.1519/1533-4287(2004)18%3C551:RAFVOS%3E2.0.CO;2
49. Styles WJ, Matthews MJ, Comfort P. Effects of strength training on squat and sprint performance in soccer players. J Strength Cond Res. (2016) 30(6):1534–9. doi: 10.1519/JSC.0000000000001243
50. Kasovic J, Martin B, Fahs CA. Kinematic Differences Between the Front and Back Squat and Conventional and Sumo Deadlift. (2019). Available from: www.nsca.com
51. Barbalho M, Coswig V, Souza D, Serrao JC, Campos MH, Gentil P. Back squat vs. hip thrust resistance-training programs in well-trained women. Int J Sports Med. (2020) 41(5):306–10. doi: 10.1055/a-1082-1126
52. Case M, Knudosn DV, Downey DL. Barbell squat relative strength as an identifier for lower extremity injury in collegiate athletes. J Strength Cond Res. (2020) 34(5):1249–53. doi: 10.1519/JSC.0000000000003554
53. Möck S, Mickel C, Rosenkranz G, Hartmann R, Wirth K. Maximal strength in the deep back squat correlates with sprinting performance over short distances. IJASS. (2018) 30(2):199–206. doi: 10.1519/JSC.0000000000002860
54. Nigro F, Bartolomei S. A comparison between the squat and the deadlift for lower body strength and power training. J Hum Kinet. (2020) 73:145–52. doi: 10.2478/hukin-2019-0139
55. Keiner M, Sander German Bobsled A, Association L, Hartmann H, Sander A, Wirth K, et al. Correlations between maximal strength tests at different squat depths and sprint performance in adolescent soccer players. Am J Sports Sci. (2014) 2(1):1–7. doi: 10.11648/j.ajss.20140201.11
56. Chelly MS, Fathloun M, Cherif N, ben Amar M, Tabka Z, van Praagh E. Effects of back squat training program on leg power, jump, and sprint performance in junior soccer player. J Strength Cond Res. (2009) 23(8):2241–9. doi: 10.1519/JSC.0b013e3181b86c40
57. 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) 38:285–8. doi: 10.1136/bjsm.2002.002071
58. Ogasawara R, Loenneke JP, Thiebaud RS, Abe T. Low load bench press training to fatigue results in muscle hypertrophy similar to high-load bench press training. Int J Clin Med. (2013) 4(2):114–21. doi: 10.4236/ijcm.2013.42022
59. Hori N, Newton R, Andrews WA, Kawamori N, McGuigan MR, Nosaka K. Does performance of hang power clean differentiate performance of jumping, sprinting and changing of direction? J Strength Cond Res. (2008) 22(2):412–8. doi: 10.1519/JSC.0b013e318166052b
60. Rossi SJ, Justice B, Stone MH. Peak Force and Rate of Force Development during Isometric and Dynamic Mid-Thigh Clean Pulls Performed at Various Intensities. (2006). Available from: https://www.researchgate.net/publication/49280114.
61. Kawamori N, Rossi SJ, Justice BD, Haff EE, Pistilli EE, O’Bryant HS, et al. Peak force and rate of force development during isometric and dynamic mid-thigh clean pulls performed at Various intensities. J Strength Cond Res. (2006) 20(3):483–91. doi: 10.1519/18025.1
62. Marcora S, Miller MK. The effect of knee angle on the external validity of isometric measures of lower body neuromuscular function. J Sports Sci. (2000) 18(5):313–9. doi: 10.1080/026404100402377
63. Wilson GJ, Murphy AJ. The use of isometric tests of muscular function in athletic assessment. Sports Med. (1996) 22(1):19–37. doi: 10.2165/00007256-199622010-00003
64. Murphy AJ, Wilson GJ. Poor correlations between isometric tests and dynamic performance: relationship to muscle activation. Eur J Appl Physiol. (1996) 73(3–4):353–7. doi: 10.1007/BF02425498
65. Murphy AJ, Wilson G, Pryor JF, Newton RU. Isometric assessment of muscular function: the effect of joint angle. J Appl Biomech. (1995) 11(2):205–15. doi: 10.1123/jab.11.2.205
66. Murphy AJ, Wilson GJ, Pryor JF. Use of the iso-inertial force mass relationship in the prediction of dynamic human performance. Eur J Appl Physiol Occup Physiol. (1994) 69(3):250–7. doi: 10.1007/BF01094797
67. Behm DG, Sale DG. Velocity specificity of resistance training. Sports Med. (1993) 15(6):374–88. doi: 10.2165/00007256-199315060-00003
68. Rosecrance JC, Cook TM, Golden NS. A comparison of isometric strength and dynamic lifting capacity in men with work-related low back injuries. J Occup Rehabil. (1991) 1(3):197–205. doi: 10.1007/BF01073456
69. McGuigan MR, Winchester JB. The relationship between isometric and dynamic strength in college football players. J Sports Sci Med. (2008) 7:101–5. PMID: 24150141; PMCID: PMC3763333
70. Boraczyński M, Boraczyński T, Podstawski R, Wójcik Z, Gronek P. Relationships between measures of functional and isometric lower body strength, aerobic capacity, anaerobic power, sprint and countermovement jump performance in professional soccer players. J Hum Kinet. (2020) 75(1):161–75. doi: 10.2478/hukin-2020-0045
71. Bartolomei S, Rovai C, Lanzoni IM, Michele R. Relationships between muscle architecture, deadlift performance, and maximal isometric force produced at the midthigh and midshin pull in resistance-trained individuals. J Strength Cond Res. (2022) 36(2):299–303. doi: 10.1519/JSC.0000000000003455
72. Bazyler CD, Beckham GK, Sato K. The use of the isometric squat as a measure of strength and explosiveness. J Strength Cond Res. (2015) 29(5):1386–92. doi: 10.1519/JSC.0000000000000751
73. Blazevich AJ, Gill N, Newton RU. Reliability and validity of two isometric squat tests. J Strength Cond Res. (2002) 16(2):298–304. PMID: 11991785
74. de Witt JK, English KL, Crowell JB, Kalogera KL, Guilliams ME, Nieschwitz BE, et al. Isometric midthigh pull reliability and relationship to deadlift one repetition Maximum. J Strength Cond Res. (2018) 32(2):528–33. doi: 10.1519/JSC.0000000000001605
75. Dos’Santos T, Thomas C, Comfort P, McMahon J, Jones P. Relationships between isometric force-time characteristics and dynamic performance. Sports. (2017) 5(3):68. doi: 10.3390/sports5030068
76. Drake D, Kennedy R, Familiarization E. Validitiy and smallest detectable difference of the isometric squat test in evaluating maximal strength. J Sports Sci. (2018) 36(18):2087–95. doi: 10.1080/02640414.2018.1436857
77. Haff GG, Stone M, O’Bryant HS, Harman E, Dinan C, Johnson R, et al. Force-time dependent characteristics of dynamic and isometric muscle actions. J Strength Cond Res. (1997) 11(4):269–72. doi: 10.3390/app11115272
78. Haff GG, Carlock JM, Hartman MJ, Kilgore JL, Kawamori N, Jackson JR, et al. Force-time curve characteristics of dynamic and isometric muscle actions of elite women Olympic weightlifters. J Strength Cond Res. (2005) 19(4):741–8. doi: 10.1519/R-15134.1
79. Markovic G, Jaric S. Is vertical jump height a body size-independent measure of muscle power? J Sports Sci. (2007) 25(12):1355–63. doi: 10.1080/02640410601021713
80. McGuigan MR, Winchester JB, Erickson T. The importance of isometric maximum strength in college wrestlers. J Sports Sci Med. (2006) 5(CSSI):108–13. PMID: 24357982; PMCID: PMC3863928
81. Miller BA, Arroyo E, Tagesen EC, Jajtner AR. Relationships between hex bar deadlift one-repetition maximum and maximal isometric pulls. Int J Exerc Sci. (2022) 15(4):45–57. https://digitalcommons.wku.edu/ijes/vol15/iss4/1
82. Townsend JR, Bender D, Vantrease WC, Hudy J, Huet K, Williamson C, et al. Isometric midthigh pull performance is associated with athletic performance and sprinting kinetics in division I men and women’s basketball players. J Strength Cond Res. (2019) 33(10):2665–73. doi: 10.1519/JSC.0000000000002165
83. Young W, Bilby G. The effect of voluntary effort to influence speed of contraction on strength, muscular power and hypertrophy development. J Strength Cond Res. (1993) 7(3):172–8.
84. Lum D, Aziz L. Validity and reliability of the isometric prone bench pull test. Int J Sports Med. (2020) 41(08):520–7. doi: 10.1055/a-1103-2173
85. Doğan NÖ. Bland-Altman Analysis: A Paradigm to Understand Correlation and Agreement. (2018). Available from: doi: 10.1016/j.tjem.2018.09.001
86. Giavarina D. Understanding bland altman analysis. Biochem Med (Zagreb). (2015) 25(2):141–51. doi: 10.11613/BM.2015.015
87. Bland JM, Altmann DG. Statistical methods of assessing agreement between two methods of clinical measurement. Lancet. (1986) i:307–10. doi: 10.1016/S0140-6736(86)90837-8
88. Lin LIK. A concordance correlation coefficient to evaluate reproducibility. (1989) 45. p. 255–68 Available from: https://www.jstor.org/stable/2532051.2720055
89. Vetter TR, Schober P. Agreement analysis. Anesth Analg. (2018) 126(6):2123–8. doi: 10.1213/ANE.0000000000002924
90. Kim J, Lee JH. A novel graphical evaluation of agreement. BMC Med Res Methodol. (2022) 22(1):51. doi: 10.1186/s12874-022-01532-w
91. Pasadyn SR, Soudan M, Gillinov M, Houghtaling P, Phelan D, Gillinov N, et al. Accuracy of commercially available heart rate monitors in athletes: a prospective study. Cardiovasc Diagn Ther. (2019) 9(4):379–85. doi: 10.21037/cdt.2019.06.05
92. Singh S, Kumar D, Kashyap V, Singh S. A comparative study of automated blood pressure device and mercury-free LED blood pressure device using lin’s concordance correlation coefficient and other validity measures in Indian population. J Family Med Prim Care. (2020) 9(3):1464. doi: 10.4103/jfmpc.jfmpc_796_19
93. Kopp-Schneider A, Hielscher T. How to evaluate agreement between quantitative measurements. Radiother Oncol. (2019) 141:321–6. doi: 10.1016/j.radonc.2019.09.004
94. Willmott CJ, Matsuura K. On the use of dimensioned measures of error to evaluate the performance of spatial interpolators. Int J Geogr Inf Sci. (2006) 20(1):89–102. doi: 10.1080/13658810500286976
95. Willmott C, Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res. (2005) 30:79–82. doi: 10.3354/cr030079
96. Makridakis S. Accuracy measures: theoretical and practical concerns. Int J Forecast. (1993) 9(4):527–9. doi: 10.1016/0169-2070(93)90079-3
97. Kim S, Kim H. A new metric of absolute percentage error for intermittent demand forecasts. Int J Forecast. (2016) 32(3):669–79. doi: 10.1016/j.ijforecast.2015.12.003
98. Hyndman RJ, Koehler AB. Another look at measures of forecast accuracy. Int J Forecast. (2006) 22(4):679–88. doi: 10.1016/j.ijforecast.2006.03.001
99. Gao WD, Nuuttila OP, Fang HB, Chen Q, Chen X. A new fitness test of estimating VO2max in well-trained rowing athletes. Front Physiol. (2021) 12:701541. doi: 10.3389/fphys.2021.701541
100. Karinharju KS, Gomersall SR, Clanchy KM, Trost SG, Yeo LT, Tweedy SM. Validity of two wheelchair-mounted devices for estimating wheelchair speed and distance traveled. Adapt Phys Activ Q. (2020) 38(3):435–51. doi: 10.1123/apaq.2020-0122
101. Gillnov S, Etiwy M, Wang R, Blackburn G, Phelan D, Gillinov M, et al. Variable accuracy of wearable heart rate monitors during aerobic exercise. Med Sci Sports Exerc. (2017) 49(8):1697–703. doi: 10.1249/MSS.0000000000001284
102. Cohen J. Statistical power analysis for behavioral sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers (1988).
103. Colquhoun RJ, Gai CM, Aguilar D, Bove D, Dolan J, Vargas A, et al. Training volume, not frequency, indicative of maximal strength adaptations to resistance training. J Strength Cond Res. (2018) 32(5):1207–13. doi: 10.1519/JSC.0000000000002414
104. Losnegard T, Mikkelsen K, Rønnestad BR, Hallén J, Rud B, Raastad T. The effect of heavy strength training on muscle mass and physical performance in elite cross country skiers. Scand J Med Sci Sports. (2011) 21(3):389–401. doi: 10.1111/j.1600-0838.2009.01074.x
105. Domínguez Jiménez JL, Fernández Suárez A. Correlation between capillary and venous blood glucose in the lactose tolerance test. Dig Dis Sci. (2016) 61(1):208–14. doi: 10.1007/s10620-015-3851-1
106. Cataldi D, Bennett JP, Quon BK, Liu YE, Heymsfield SB, Kelly T, et al. Agreement and precision of deuterium dilution for total body water and multicompartment body composition assessment in collegiate athletes. J Nutr. (2022) 152(9):2048–59. doi: 10.1093/jn/nxac116
107. Bayzler CD, Beckham GK, Sato K. The use of the isometric squat as a measure of strength and explosiveness. J Strength Cond Res. (2015) 29(5):1386–92. doi: 10.1519/JSC.0000000000000751
108. Warneke K, Hillebrecht M, Wirth K, Schiemann S, Keiner M. Correlation between isometric maximum strength and one repetition maximum in the calf muscle in extended and bended knee joint. Int J Appl Sports Sci. (2022) 34(1):61–71. doi: 10.24985/ijass.2022.34.1.61
109. Wagner CM, Warneke K, Bächer C, Liefke C, Paitner P, Kuhn L, et al. Despite good correlations, there is no exact coincidence between isometric and dynamic strength measurements in elite youth soccer players. Sports. (2022) 10(11):175. doi: 10.3390/sports10110175
110. van den Tillaar R, Andersen V, Saeterbakken AH. The existence of a sticking region in free weight squats. J Hum Kinet. (2014) 42(1):63–71. doi: 10.2478/hukin-2014-0061
111. Beckham GK, Sato K, Santana HA, Mizuguchim S, Haff GG, Stone MH. Effect of body position on force production during the isometric midthigh pull. J Strength Cond Res. (2018) 32(1):48–56. doi: 10.1519/JSC.0000000000001968
112. Lanza MB, Balshaw TG, Folland JP. Is the joint-angle specificity of isometric resistance training real? And if so, does it have a neural basis? Eur J Appl Physiol. (2019) 119(11–12):2465–76. doi: 10.1007/s00421-019-04229-z
113. Paulus DC, Reiser RF, Troxell WO. Pneumatic strength assessment device: design and isometric measurement. Biomed Sci Instrum. (2004) 40:277–82. PMID: 15133971
114. Rahmani A, Viale F, Dalleau G, Lacour JR. Force/velocity and power/velocity relationships in squat exercise. Eur J Appl Physiol. (2001) 84(3):227–32. doi: 10.1007/PL00007956
115. Yahata K, Konrad A, Sato S, Kiyono R, Yoshida R, Fukaya T, et al. Effects of a high-volume static stretching programme on plantar-flexor muscle strength and architecture. Eur J Appl Physiol. (2021) 121(4):1159–66. doi: 10.1007/s00421-021-04608-5
116. Comfort P. Within- and between-session reliability of power, force, and rate of force development during the power clean. J Strength Cond Res. (2013) 27(5):1210–4. doi: 10.1519/JSC.0b013e3182679364
117. Hori N, Newton RU, Andrews WA, Kawamori N, McGuigan MR, Nosaka K. Comparison of four different methods to measure power output during the hang power clean and the weighted jump squat. J Strength Cond Res. (2007) 21(2):314. doi: 10.1519/R-22896.1
118. Argus CK, Gill ND, Keogh JW, Hopkins WG, Beaven CM. Changes in strength, power, and steroid hormones during a professional rugby union competition. J Strength Cond Res. (2009) 23(5):1583–92. doi: 10.1519/JSC.0b013e3181a392d9
119. Cronin JB, Hansen KT. Strength and power predictors of sports speed. J Strength Cond Res. (2005) 19(2):349. doi: 10.1519/14323.1
120. Harris NK, Cronin JB, Hopkins WG, Hansen KT. Relationship between sprint times and the strength/power outputs of a machine squat jump. J Strength Cond Res. (2008) 22(3):691–8. doi: 10.1519/JSC.0b013e31816d8d80
121. Swinton PA, Lloyd R, Keogh JWL, Agouris I, Stewart AD. A biomechanical comparison of the traditional squat, powerlifting squat, and box squat. J Strength Cond Res. (2012) 26(7):1805–16. doi: 10.1519/JSC.0b013e3182577067
122. Cotter JA, Chaudhari AM, Jamison ST, Devor ST. Knee joint kinetics in relation to commonly prescribed squat loads and depths. J Strength Cond Res. (2013) 27(7):1765–74. doi: 10.1519/JSC.0b013e3182773319
123. Kubo K, Ikebukuro T, Yata H. Effects of squat training with different depths on lower limb muscle volumes. Eur J Appl Physiol. (2019) 119(9):1933–42. doi: 10.1007/s00421-019-04181-y
124. Hartmann H, Wirth K, Klusemann M, Dalic J, Matuschek C, Schmidtbleicher D, et al. Influence of squatting depth on jumping performance. J Strength Cond Res. (2012) 26(12):3243–61. doi: 10.1519/JSC.0b013e31824ede62
125. Lum D, Joseph R. Relationship between isometric force-time characteristics and dynamic performance pre- and post-training. J Sports Med Phys Fitness. (2020) 60(4):520–6. doi: 10.23736/S0022-4707.19.10293-9
126. Feeler L, St. James JD, Schapmire DW. Isometric strength assessment, part I: static testing does not accurately predict dynamic lifting capacity. Work. (2010) 37(3):301–8. doi: 10.3233/WOR-2010-1082
127. Worrell TW, Karst G, Adamczyk D, Moore R, Stanley C, Steimel B, et al. Influence of joint position on electromyographic and torque generation during maximal voluntary isometric contractions of the hamstrings and gluteus Maximus muscles. J Orthop Sports Phys Ther. (2001) 31(12):730–40. doi: 10.2519/jospt.2001.31.12.730
128. Wilson GJ, Murphy AJ, Walshe A. The specificity of strength training: the effect of posture. Eur J Appl Physiol Occup Physiol. (1996) 73(3–4):346–52. doi: 10.1007/BF02425497
129. Pekünlü E, Özsu İ. Avoiding systematic errors in isometric squat-related studies without pre-familiarization by using sufficient numbers of trials. J Hum Kinet. (2014) 42(1):201–13. doi: 10.2478/hukin-2014-0074
130. Palmer TB, Pineda JG, Durham RM. Effects of knee position on the reliability and production of maximal and rapid strength characteristics during an isometric squat test. J Appl Biomech. (2018) 34(2):111–7. doi: 10.1123/jab.2017-0213
131. Drake D, Kennedy RA, Wallace ES. Multi-joint rate of force development testing protocol affects reliability and the smallest detectible difference. J Sports Sci. (2019) 37(14):1570–81. doi: 10.1080/02640414.2019.1576258
132. Warneke K, Keiner M, Schiemann S, Lohmann LH, Wirth K. The influence of maximal strength performance in the front squat and deadlift on linear sprint and jump performance in male youth elite basketball players. Ger J Sport Res. (2022). doi: 10.1007/s12662-022-00863-6
133. Storey A, Smith HK. Unique aspects of competitive weightlifting. Sports Med. (2012) 42(9):769–90. doi: 10.1007/BF03262294
134. Haff GG, Carlock JM, Hartman MJ, Kilgore JL, Kawamori N, Jackson JR, et al. Force–time curve characteristics of dynamic and isometric muscle actions of elite women Olympic weightlifters. J Strength Cond Res. (2005) 19(4):741. doi: 10.1519/R-15134.1
Keywords: maximal strength testing, isometric, dynamic, 1RM, agreement, isometric mid thigh pull, squat, performance testing
Citation: Warneke K, Wagner C-M, Keiner M, Hillebrecht M, Schiemann S, Behm DG, Wallot S and Wirth K (2023) Maximal strength measurement: A critical evaluation of common methods—a narrative review. Front. Sports Act. Living 5:1105201. doi: 10.3389/fspor.2023.1105201
Received: 25 November 2022; Accepted: 30 January 2023;
Published: 17 February 2023.
Edited by:
Jaime Fernandez Fernandez, Universidad de León, SpainReviewed by:
Dustin J. Oranchuk, Auckland University of Technology, New ZealandHagen Hartmann, Hochschule für Gesundheit & Sport, Technik & Kunst, Germany
© 2023 Warneke, Wagner, Keiner, Hillebrecht, Schiemann, Behm, Wallot and Wirth. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Konstantin Warneke konstantin.warneke@stud.leuphana.de
Specialty Section: This article was submitted to Elite Sports and Performance Enhancement, a section of the journal Frontiers in Sports and Active Living