Purpose: Anaerobic speed reserve (ASR), defined as the speed range from velocity associated with maximal oxygen uptake (vVO2max) to maximal sprint speed, has recently been shown to be an important tool for middle-distance coaches to meet event surge demands and inform on the complexity of athlete profiles. To enable field application of ASR, the relationship between gun-to-tape 1500-m average speed (1500v) and the vVO2max for the determination of lower landmark of the ASR was assessed in elite middle-distance runners. Methods: A total of 8 national and 4 international middle-distance runners completed a laboratory-measured vVO2max assessment within 6 wk of a nonchampionship 1500-m gun-to-tape race. ASR was calculated using both laboratory-derived vVO2max (ASR-LAB) and 1500v (ASR-1500v), with maximal sprint speed measured using radar technology. Results: 1500v was on average +2.06 ± 1.03 km/h faster than vVO2max (moderate effect, very likely). ASR-LAB and ASR-1500v mean differences were −2.1 ± 1.5 km/h (large effect, very likely). 1500v showed an extremely large relationship with vVO2max, r = .90 ± .12 (most likely). Using this relationship, a linear-regression vVO2max-estimation equation was derived as vVO2max (km/h) = (1500v [km/h] − 14.921)/0.4266. Conclusions: A moderate difference was evident between 1500v and vVO2max in elite middle-distance runners. The present regression equation should be applied for an accurate field prediction of vVO2max from 1500-m gun-to-tape races. These findings have strong practical implications for coaches lacking access to a sports physiology laboratory who seek to monitor and profile middle-distance runners.

Purpose: A novel 4-task Athlete Introductory Movement Screen was developed and tested to provide an appropriate and reliable movement screening tool for youth sport practitioners. Methods: The overhead squat, lunge, push-up, and a prone brace with shoulder touches were selected based on previous assessments. A total of 28 mixed-sport junior athletes (18 boys and 10 girls; mean age = 15.7 [1.8] y) completed screening after viewing standardized demonstration videos. Athletes were filmed performing 8 repetitions of each task and assessed retrospectively by 2 independent raters using a 3-point scale. The primary rater reassessed the footage 3 weeks later. A subgroup (n = 11) repeated the screening 7 days later, and a further 8 athletes were reassessed 6 months later. Intraclass correlation coefficients (ICC), typical error (TE), coefficient of variation (CV%), and weighted kappa (k) were used in reliability analysis. Results: For the Athlete Introductory Movement Screen 4-task sum score, intrarater reliability was high (ICC = .97; CV = 2.8%), whereas interrater reliability was good (intraclass correlation coefficient = .88; CV = 5.6%). There was a range of agreement from fair to almost perfect (k = .31–.89) between raters across individual movements. A 7-day and 6-month test–retest held good reliability and acceptable CVs (≤ 10%) for sum scores. Conclusion: The 4-task Athlete Introductory Movement Screen appears to be a reliable tool for profiling emerging athletes. Reliability was strongest within the same rater; it was lower, yet acceptable, between 2 raters. Scores can provide an overview of appropriate movement competencies, helping practitioners assess training interventions in the athlete development pathway.

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In well-trained MD athletes, greater stiffness appears linked to faster and more economical running. Although k had the strongest relationship with RE, k while sprinting and k in maximal unilateral jumps may be more practical measures of stiffness. Agreement between global stiffness assessments and k highlights the energy contribution of the Achilles tendon to running efficiency and velocity. Further research incorporating these assessment tools could help establish more comprehensive mechanical and metabolic athlete profiles and further our understanding of training adaptations, especially stiffness modification, longitudinally.