Agility is a significant determinant of success in soccer; however, studies have rarely presented and evaluated soccer-specific tests of reactive agility (S_RAG) and non-reactive agility (change of direction speed – S_CODS) or their applicability in this sport. The aim of this study was to define the reliability and validity of newly developed tests of the S_RAG and S_CODS to discriminate between the performance levels of junior soccer players. The study consisted of 20 players who were involved at the highest national competitive rank (all males; age: 17.0 ± 0.9 years), divided into three playing positions (defenders, midfielders, and forwards) and two performance levels (U17 and U19). Variables included body mass (BM), body height, body fat percentage, 20-m sprint, squat jump, countermovement jump, reactive-strength-index, unilateral jump, 1RM-back-squat, S_CODS, and three protocols of S_RAG. The reliabilities of the S_RAG and S_CODS were appropriate to high (ICC: 0.70 to 0.92), with the strongest reliability evidenced for the S_CODS. The S_CODS and S_RAG shared 25–40% of the common variance. Playing positions significantly differed in BM (large effect-size differences [ES]; midfielders were lightest) and 1RM-back-squat (large ES; lowest results in midfielders). The performance levels significantly differed in age and experience in soccer; U19 achieved better results in the S_CODS (t-test: 3.61, p < 0.05, large ES) and two S_RAG protocols (t-test: 2.14 and 2.41, p < 0.05, moderate ES). Newly developed tests of soccer-specific agility are applicable to differentiate U17 and U19 players. Coaches who work with young soccer athletes should be informed that the development of soccer-specific CODS and RAG in this age is mostly dependent on training of the specific motor proficiency.

Purpose: To compare the effects of velocity-based training (VBT) and 1-repetition-maximum (1RM) percentage-based training (PBT) on changes in strength, loaded countermovement jump (CMJ), and sprint performance. Methods: A total of 24 resistance-trained males performed 6 weeks of full-depth free-weight back squats 3 times per week in a daily undulating format, with groups matched for sets and repetitions. The PBT group lifted with fixed relative loads varying from 59% to 85% of preintervention 1RM. The VBT group aimed for a sessional target velocity that was prescribed from pretraining individualized load–velocity profiles. Thus, real-time velocity feedback dictated the VBT set-by-set training load adjustments. Pretraining and posttraining assessments included the 1RM, peak velocity for CMJ at 30%1RM (PV-CMJ), 20-m sprint (including 5 and 10 m), and 505 change-of-direction test (COD). Results: The VBT group maintained faster (effect size [ES] = 1.25) training repetitions with less perceived difficulty (ES = 0.72) compared with the PBT group. The VBT group had likely to very likely improvements in the COD (ES = −1.20 to −1.27), 5-m sprint (ES = −1.17), 10-m sprint (ES = −0.93), 1RM (ES = 0.89), and PV-CMJ (ES = 0.79). The PBT group had almost certain improvements in the 1RM (ES = 1.41) and possibly beneficial improvements in the COD (ES = −0.86). Very likely favorable between-groups effects were observed for VBT compared to PBT in the PV-CMJ (ES = 1.81), 5-m sprint (ES = 1.35), and 20-m sprint (ES = 1.27); likely favorable between-groups effects were observed in the 10-m sprint (ES = 1.24) and nondominant-leg COD (ES = 0.96), whereas the dominant-leg COD (ES = 0.67) was possibly favorable. PBT had small (ES = 0.57), but unclear differences for 1RM improvement compared to VBT. Conclusions: Both training methods improved 1RM and COD times, but PBT may be slightly favorable for stronger individuals focusing on maximal strength, whereas VBT was more beneficial for PV-CMJ, sprint, and COD improvements.

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Jukic, I, García-Ramos, A, Malecek, J, Omcirk, D, and Tufano, JJ. Validity of load–velocity relationship to predict 1 repetition maximum during deadlifts performed with and without lifting straps: The accuracy of six prediction models. J Strength Cond Res 36(4): 902–910, 2022—This study aimed to compare the accuracy of six 1 repetition maximum (1RM) prediction models during deadlifts performed with (DLw) and without (DLn) lifting straps. In a counterbalanced order, 18 resistance-trained men performed 2 sessions that consisted of an incremental loading test (20-40-60-80-90% of 1RM) followed by 1RM attempts during the DLn (1RM = 162.0 ± 26.9 kg) and DLw (1RM = 179.0 ± 29.9 kg). Predicted 1RMs were calculated by entering both group and individualized mean concentric velocity of the 1RM (V1RM) into an individualized linear and polynomial regression equations, which were derived from the load–velocity relationship of 5 ([20-40-60-80-90% of 1RM], i.e., multiple-point method) or 2 ([40 and 90% of 1RM] i.e., 2-point method) incremental warm-up sets. The predicted 1RMs were deemed highly valid if the following criteria were met: trivial to small effect size, practically perfect r, and low absolute errors (<5 kg). The main findings revealed that although prediction models were more accurate during the DLn than DLw, none of the models provided an accurate estimation of the 1RM during both DLn (r = 0.92–0.98; absolute errors: 6.6–8.1 kg) and DLw (r = 0.80–0.93; absolute errors: 12.4–16.3 kg) according to our criteria. Therefore, these results suggest that the 1RM for both DLn and DLw should not be estimated through the recording of movement velocity if sport professionals are not willing to accept more than 5 kg of absolute errors.

Purpose: To explore the effect of several methodological factors on the number of repetitions performed before and after reaching certain velocity loss thresholds (VLTs). Method: Fifteen resistance-trained men (bench press 1-repetition maximum = 1.25 [0.16] kg·kg−1) performed with maximum intent a total of 182 sets (77 short sets [≤12 repetitions] and 105 long sets [>12 repetitions]) leading to failure during the Smith machine bench press exercise. Fifteen percent, 30%, and 45% VLTs were calculated, considering 2 reference repetitions (first and fastest repetitions) and 2 velocity variables (mean velocity [MV] and peak velocity [PV]). Results: The number of repetitions performed before reaching all VLTs were affected by the reference repetition and velocity variable (P ≤ .001). The fastest MV and PV during the short sets (75.3%) and PV during the long sets (72.4%) were predominantly observed during the first repetition, while the fastest MV during long sets was almost equally distributed between the first (37.1%) and second repetition (40.0%). Failure occurred before reaching the VLTs more frequently using PV (4, 8, and 33 occasions for 15%, 30%, and 45% VLTs, respectively) than MV (only 1 occasion for the 45% VLT). The participants rarely produced a velocity output above a VLT once this threshold was exceeded for the first time (≈10% and 30% of occasions during the short and long sets, respectively). Conclusions: The reference repetition and velocity variable are important factors to consider when implementing VLTs during resistance training. The fastest repetition (instead of the first repetition) and MV (instead of PV) are recommended.

Purpose: To compare the accuracy of nine 1-repetition maximum (1RM) prediction methods during the paused and touch-and-go bench press exercises performed in a Smith machine. Method: A total of 86 men performed 2 identical sessions (incremental loading test until reaching the 1RM followed by a set to failure) in a randomized order during the paused and touch-and-go bench press exercises. Individualized load–velocity relationships were modeled by linear and polynomial regression models considering 4 loads (45%–60%–75%–90% of 1RM) (multiple-point methods) and considering only 2 loads (45%–90% of 1RM) by a linear regression (2-point method). Three minimal velocity thresholds were used: the general velocity of 0.17 m·s−1 (general velocity of the 1RM [V1RM]), the velocity obtained when lifting the 1RM load (individual V1RM), and the velocity obtained during the last repetition of a set to failure. Results: The 1RM prediction methods were generally valid (range: r = .96–.99, standard error of the estimate = 2.8–4.9 kg or 4.6%–8.0% of 1RM). The multiple-point linear method (2.79 [2.29] kg) was more precise than the multiple-point polynomial method (3.54 [3.31] kg; P = .013), but no significant differences were observed when compared with the 2-point method (3.09 [2.66] kg, P = .136). The velocity of the last repetition of a set to failure (3.47 [2.97] kg) was significantly less precise than the individual V1RM (2.91 [2.75] kg, P = .009) and general V1RM (3.00 [2.65] kg, P = .010). Conclusions: Linear regression models and a general minimal velocity threshold of 0.17 m·s−1 should be recommended to obtain a quick and precise estimation of the 1RM during the bench press exercise performed in a Smith machine.

This study determined whether redistributing total rest time into shorter, but more frequent rest periods could maintain velocity and power output during 3 traditional sets of 6 clean pulls using 80% (TS80), 100% (TS100) and 120% (TS120) of power clean 1RM with 180 seconds of inter-set rest and during 3 “rest redistribution” protocols of 9 sets of 2 clean pulls using 80% (RR80), 100% (RR100) and 120% (RR120) of power clean 1RM with 45 seconds of inter-set rest. The total number of repetitions performed above 10 and 20% velocity loss thresholds, mean and peak velocity maintenance (the average of all 18 repetitions relative to the best repetition; MVM, PVM), and decline (the worst repetition relative to the best repetition; MVD, PVD) were calculated. For MVM, PVM, MVD, and PVD, there were small-to-moderate effect sizes in favour of RR80 and RR100, but large effects favouring RR120, compared to their respective TS protocols. The number of repetitions within a 20% velocity loss threshold was 17.7 ± 0.6 during RR and 16.5 ± 2.4 during TS (effect size 0.69); and the number of repetitions within a 10% velocity loss threshold was about 13.1 ± 3.7 during RR and 10.7 ± 3.6 during TS (effect size 0.66). Therefore, RR generally allowed for a better overall maintenance of velocity and power, especially at heavy loads. Coaches who wish to implement velocity-based training, but who do not wish to purchase or use the associated equipment, may consider rest-redistribution to encourage similar training stimuli.

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