Comparison of the Capacity of Different Jump and Sprint Field Tests to Detect Neuromuscular Fatigue.

Different jump and sprint tests have been used to assess neuromuscular fatigue, but the test with optimal validity remains to be established. The current investigation examined the suitability of vertical jump (countermovement jump [CMJ], squat jump [SJ], drop jump [DJ]) and 20-m sprint (SPRINT) testing for neuromuscular fatigue detection. On 6 separate occasions, 11 male team-sport athletes performed 6 CMJ, SJ, DJ, and 3 SPRINT trials. Repeatability was determined on the first 3 visits, with subsequent 3 visits (0-, 24-, and 72-hour postexercise) following a fatiguing Yo-Yo running protocol. SPRINT performance was most repeatable (mean coefficient of variation ≤2%), whereas DJ testing (4.8%) was significantly less repeatable than CMJ (3.0%) and SJ (3.5%). Each test displayed large decreases at 0-hour (33 of 49 total variables; mean effect size = 1.82), with fewer and smaller decreases at 24-hour postexercise (13 variables; 0.75), and 72-hour postexercise (19 variables; 0.78). SPRINT displayed the largest decreases at 0-hour (3.65) but was subsequently unchanged, whereas SJ performance recovered by 72-hour postexercise. In contrast, CMJ and DJ performance displayed moderate (12 variables; 1.18) and small (6 variables; 0.53) reductions at 72-hour postexercise, respectively. Consequently, the high repeatability and immediate and prolonged fatigue-induced changes indicated CMJ testing as most suitable for neuromuscular fatigue monitoring.

Alternative countermovement-jump analysis to quantify acute neuromuscular fatigue.

PURPOSE: To examine the reliability and magnitude of change after fatiguing exercise in the countermovement-jump (CMJ) test and determine its suitability for the assessment of fatigue-induced changes in neuromuscular (NM) function. A secondary aim was to examine the usefulness of a set of alternative CMJ variables (CMJ-ALT) related to CMJ mechanics. METHODS: Eleven male college-level team-sport athletes performed 6 CMJ trials on 6 occasions. A total of 22 variables, 16 typical (CMJ-TYP) and 6 CMJ-ALT, were examined. CMJ reproducibility (coefficient of variation; CV) was examined on participants' first 3 visits. The next 3 visits (at 0, 24, and 72 h postexercise) followed a fatiguing high-intensity intermittent-exercise running protocol. Meaningful differences in CMJ performance were examined through effect sizes (ES) and comparisons to interday CV. RESULTS: Most CMJ variables exhibited intraday (n = 20) and interday (n = 21) CVs of <10%. ESs ranging from trivial to moderate were observed in 18 variables at 0 h (immediately postfatigue). Mean power, peak velocity, flight time, force at zero velocity, and area under the force-velocity trace showed changes greater than the CV in most individuals. At 24 h, most variables displayed trends toward a return to baseline. At 72 h, small increases were observed in time-related CMJ variables, with mean changes also greater than the CV. CONCLUSIONS: The CMJ test appears a suitable athlete-monitoring method for NM-fatigue detection. However, the current approach (ie, CMJ-TYP) may overlook a number of key fatigue-related changes, and so practitioners are advised to also adopt variables that reflect the NM strategy used.

Analysis of jump performance of world-class mogul skiers over an Olympic quadrennial cycle: a case study.

This case study examines the longitudinal jump data of 1 male and 1 female world-class mogul skier over the course of a quadrennial leading to the 2010 Winter Olympics. Between-subjects standard deviation, smallest worthwhile enhancement, % coefficient of variance, and effect size (ES) were calculated from team jump testing taking place immediately preceding the 2010 Winter Olympics, as this was deemed the point in the quadrennial that the athlete group would be most likely near their best performance. These data were then used to characterize the progression of explosive power of elite mogul skiers over an Olympic quadrennial. Jump data for both the male and the female athlete showed trivial to large improvements in jump performance from Q1 (quadrennial year 1) to Q2, variable changes in performance from Q2 to Q4, and an overall improvement (small to large ES) from Q1 to Q4. Explosive power is a critical component of performance for moguls, and an analysis of the group data (Canadian athletes 2006-2010) shows that of all performance markers, jump testing is the variable that clearly delineates between World Cup and developmental athletes.

Challenges in understanding the influence of maximal power training on improving athletic performance.

The ability to optimise muscular power output is considered fundamental to successful performance of many athletic and sporting activities. Consequently, a great deal of research has investigated methods to improve power output and its transference to athletic performance. One issue that makes comparisons between studies difficult is the different modes of dynamometry (isometric, isokinetic and isoinertial) used to measure strength and power. However, it is recognised that isokinetic and isometric assessment bear little resemblance to the accelerative/decelerative motion implicit in limb movement during resistance training and sporting performance. Furthermore, most people who train to increase power would have limited or no access to isometric and/or isokinetic dynamometry. It is for these reasons and for the sake of brevity that the findings of isoinertial (constant gravitational load) research will provide the focus of much of the discussion in this review. One variable that is considered important in increasing power and performance in explosive tasks such as running and jumping is the training load that maximises the mechanical power output (Pmax) of muscle. However, there are discrepancies in the research as to which load maximises power output during various resistance exercises and whether training at Pmax improves functional performance is debatable. There is also some evidence suggesting that Pmax is affected by the training status of the individuals; however, other strength variables could quite possibly be of greater importance for improving functional performance. If Pmax is found to be important in improving athletic performance, then each individual's Pmax needs to be determined and they then train at this load. The predilection of research to train all subjects at one load (e.g. 30% one repetition maximum [1RM]) is fundamentally flawed due to inter-individual Pmax differences, which may be ascribed to factors such as training status (strength level) and the exercise (muscle groups) used. Pmax needs to be constantly monitored and adjusted as research suggests that it is transient. In terms of training studies, experienced subjects should be used, volume equated and the outcome measures clearly defined and measured (i.e. mean power and/or peak power). Sport scientists are urged to formulate research designs that result in meaningful and practical information that assists coaches and strength and conditioning practitioners in the development of their athletes.