Despite Good Correlations, There Is No Exact Coincidence between Isometric and Dynamic Strength Measurements in Elite Youth Soccer Players

Can isometric testing substitute for the one repetition maximum squat test?

When measuring maximum strength, a high accuracy and precision is required to monitor the training adaptations. Based on available reliability parameters, the literature suggests the replacement of the one repetition maximum (1RM) by isometric testing to save testing time. However, from a statistical point of view, correlation coefficients do not provide the required information when aiming to replace one test by another. Therefore, the literature suggests the inclusion of the mean absolute error (MAE), the mean absolute percentage error (MAPE) for agreement analysis. Consequently, to check the replaceability of 1RM testing methods, the current study examined the agreement of isometric and dynamic testing methods in the squat and the isometric mid-thigh pull. While in accordance with the literature, correlations were classified high r = 0.638-0.828 and ICC = 0.630-0.828, the agreement analysis provided MAEs of 175.75-444.17 N and MAPEs of 16.16-57.71% indicating an intolerable high measurement error between isometric and dynamic testing conditions in the squat and isometric mid-thigh pull. In contrast to previous studies, using MAE, MAPE supplemented by CCC and BA analysis highlights the poor agreement between the included strength tests. The recommendation to replace 1RM testing with isometric testing routines in the squat does not provide suitable concordance and is not recommended.

The magnitude of correlation between deadlift 1RM and jumping performance is sports dependent

Introduction

Based on the assumption of maximal strength as a basic ability, several studies show a high influence of maximum strength on jumping performance in several sport athletes. However, there is a wide range of correlations from r = 0.17-0.9 between squat 1RM and jumping performance in different sports. Additionally, there are only a few studies investigating the influence of deadlift one repetition maximum (1RM) on jumping performance. Thus, this study aimed to investigate the correlations between 1RM in the deadlift on jumping performance using the countermovement jump height (CMJ) and squat jump height (SJ) considering different sports.

Methods

103 athletes with experience in the deadlift from soccer, basketball, American football, powerlifting as well as participants from different sports without any deadlift experience (control group) were included to this study.

Results

Overall statistics showed a significant moderate influence of deadlift 1RM (r = 0.301-0.472) on jumping performance. However, subgroup analysis showed no significant correlation between deadlift 1RM and jumping performance in control participants, while moderate correlations could be detected in powerlifters (r = 0.34-0.39), soccer players (r = 0.437-0.46), American football players (0.584-0.62) and high correlations in basketball players (r = 0.809-0.848) showing significant influence of type of sport on correlations between deadlift maximum strength and jumping performance.

Discussion

Presented results underline movement velocity- and task specificity of strength training routines which is discussed in the light of the respective sports.

Maximum strength and power as determinants of on-ice sprint performance in elite U16 to adult ice hockey players

In ice hockey, speed strength is one of the major physical key performance indicators, which is significantly influenced by maximum strength. The objective of this study was to evaluate the age-dependent relationship of off-ice maximum strength and vertical jump performance with on-ice linear sprint performance, considering age and performance level. Ninety-one male youth and adult professional ice hockey players (age: 19.3 ± 5.49 years) were recruited and divided into four age groups: under 16, 18, 21 years old and professional elite players (Pro) (i.e., > 21 years). They were tested in maximal isometric strength, squat jump (loaded and unloaded), countermovement jump and on-ice sprint performance (15 m and 30 m linear sprint; 15 m flying linear sprint). Statistical analysis revealed that on-ice sprint performance correlated with isometric strength performance (r = |0.34|-|0.63|) and with off-ice jump performance (r = |0.61|-|0.77|) without an influence of age group or performance level. However, performance differed between age groups and performance level, the largest differences being found between the youngest age group (U16) and the Pro group (g = 0.966-3.281). The present study shows that maximum strength influences on-ice sprint performances in ice hockey players, as well as performance differences between age groups and professional players. Strength and jumping performance should therefore be included in regular performance testing in ice hockey. Since performance differences are observed for almost all strength and speed-strength performances of the youth teams to the Pros, training of these variables is strongly recommended to improve in the transition phase from junior to elite level.

Maximal strength measurement: A critical evaluation of common methods-a narrative review

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 (ρ c) 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 ρ c = 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 ρ c = 0.68 with a MAE = 304.51N/MAPE = 17.4% with a range of -750 N-600 N within a 95% CI and ρ c = 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 ρ c, 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.