Anaerobic Speed Reserve, Sprint Force–Velocity Profile, Kinematic Characteristics, and Jump Ability among Elite Male Speed- and Endurance-Adapted Milers

imed to compare sprint, jump performance, and sprint mechanical variables between endurance-adapted milers (EAM, specialized in 1500–3000-m) and speed-adapted milers (SAM, specialized in 800–1500 m) and to examine the relationships between maximal sprint speed (MSS), anaerobic speed reserve (ASR), sprint, jump performance, and sprint mechanical characteristics of elite middle-distance runners. Fifteen participants (8 EAM; 7 SAM) were evaluated to obtain their maximal aerobic speed, sprint mechanical characteristics (force–velocity pro le and kinematic variables), jump, and sprint performance. SAM displayed greater MSS, ASR, horizontal jump, sprint performance, and mechanical ability than EAM (p< 0.05). SAM also showed higher stiffness in the 40-msprint (p= 0.026) and a higher ratio of horizontal-to-resultant force (RF) at 10 m(p= 0.003) and RFpeak (p=

to obtain their maximal aerobic speed, sprint mechanical characteristics (force–velocity pro le and kinematic variables), jump, and sprint performance. SAM displayed greater MSS, ASR, horizontal jump, sprint performance, and mechanical ability than EAM (p< 0.05). SAM also showed higher stiffness in the 40-msprint (p= 0.026) and a higher ratio of horizontal-to-resultant force (RF) at 10 m(p= 0.003) and RFpeak (p= 0.024). MSS and ASR correlated with horizontal (r= 0.76) and vertical (r= 0.64) jumps, all sprint split times (r 0.85), stiffness (r= 0.86), and mechanical characteristics (r 0.56) during the 100-m sprint, and physical qualities during acceleration (r 0.66) and sprint mechanical effectiveness from the force–velocity pro le (r 0.69). Season-best times in the 800 m were signi cantly correlated with MSS (r= 0.86). Sprint ability has a crucial relevance in middle-distance runners' performance, especially for SAM. Keywords:maximal force; performance; maximal power; middle-distance running 1. Introduction Performance in middle-distance runners is determined by tactical decision-making and physiological and mechanical factors [1]. Success in athletic races from 800 m to 3000 m is characterized by rapid, economical, and cyclical movement patterns [2]. Athletes need to sustain running velocities at and above maximal aerobic speed (MAS), deemed as the minimum speed at which maximum oxygen uptake is attained, and develop their sprinting ability to a great extent in order to achieve successful performances at major championships [3,4]. Although running economy and MAS are considered main middle- distance running performance determinants [5], recent studies also highlight the important role of anaerobic qualities [6,7] such as anaerobic speed reserve (ASR), which is the speed zone ranging from MAS to maximal sprint speed (MSS) [8,9]. Given that elite middle- distance runners display high levels of MAS [5] and anaerobic capacity, it seems that ASR should be considered to understand the underpinning mechanisms explaining their performance. In addition, MSS, which represents the upper part of the ASR spectrum, Int. J. Environ. Res. Public Health2022,19, 1447.

Int. J. Environ. Res. Public Health2022,19, 1447 2 of 11 could also be an appropriate key performance parameter in middle-distance runners, not only because it allows athletes to achieve faster paces over longer distances [6] but also because it is the way to increase their ASR. Furthermore, ASR has been proposed to be useful in categorizing different middle- distance runners' pro les (i.e., 400–800 m, 800 m, and 800–1500 m types) and identifying training models (i.e., speci c prescription of high-intensity training sessions) according to these pro les [10]. In this sense, different running categories exist in each distance event, and 1500 m runners can be considered either speed-adapted (800–1500 m specialists) or endurance-adapted (1500–3000 m specialists) milers (SAM and EAM, respectively) [11]. In addition, current evidence fails to describe the in uence of anaerobic capacity (i.e., the ability to display higher speeds than MAS and lower than MSS) on running performance and ASR in middle-distance runners. In this term, the force–velocity (F-V) pro le [12,13] during a maximum speed sprint would allow to describe the mechanical effectiveness in force application (i.e., the percentage of the resultant force that is produced in the horizontal direction) at the upper limit of ASR in middle-distance runners [14], apart from helping coaches to implement individualized training programs [12,13]. Apart from anaerobic factors, several studies have shown a rising interest in me- chanical parameters such as the association of stiffness with running economy (RE) and maximal velocity [2,15], or the existing differences in running kinematics (i.e., step length, frequency, and ight and contact time) among athletes of different performance levels [16] and categories [11]. However, the in uence of all these mechanical parameters on running performance in middle-distance running events has not been explored suf ciently yet. Since increasing evidence suggests that performance in these events could be strongly con- nected to anaerobic characteristics and sprint ability [7,17], it would be useful for athletes and coaches to describe the aforementioned mechanical parameters in middle-distance runners and elucidate the relationship to performance determinants. Therefore, the aims of the present study were: (1) to describe and

suf ciently yet. Since increasing evidence suggests that performance in these events could be strongly con- nected to anaerobic characteristics and sprint ability [7,17], it would be useful for athletes and coaches to describe the aforementioned mechanical parameters in middle-distance runners and elucidate the relationship to performance determinants. Therefore, the aims of the present study were: (1) to describe and compare sprint and jump performance and sprint mechanical variables between elite male SAM and EAM, and (2) to examine the relationships between MSS and ASR with sprint and jump performance and sprint mechanical variables in elite male middle-distance runners. We hypothesize that SAM will display greater sprint and jump performance and more ef cient sprint mechanical responses than EAM and that MSS and ASR will signi cantly correlate with sprint and jump performance and ef ciency of sprint mechanical responses. 2. Materials and Methods 2.1. Participants A convenient sample of 15 elite male middle-distance running athletes (age = 24.5 4.6 years, body mass = 63.1 4.3 kg, height = 1.77 0.05 m) voluntarily participated in this study. All athletes trained in the same training group and shared the same coach at the Sport High Per- formance Centre of the Spanish Government (Madrid). To conduct an exhaustive analysis, participants were classi ed based on their coach's perspective regarding the athletic event they were specialized in. Accordingly, eight and seven runners were considered SAM and EAM, respectively. This coach's decision was based on the target event for the season and the training characteristics being used (i.e., milers who were also targeting the 800 m event displayed higher intensity and lower volume in training; milers who were also targeting the 3000 m, 3000 m steeplechase, or 5000 m events displayed lower intensity and higher volume in training). Additionally, this decision was con rmed by means of analyzing the difference in recent competitive performances between shorter (i.e., 800 m) and longer (i.e., 3000 m) events than 1500 m. The World Athletic open access website was used to collect the best performances achieved by participants during competition 12 months prior to testing (www.worldathletics.org into World

higher volume in training). Additionally, this decision was con rmed by means of analyzing the difference in recent competitive performances between shorter (i.e., 800 m) and longer (i.e., 3000 m) events than 1500 m. The World Athletic open access website was used to collect the best performances achieved by participants during competition 12 months prior to testing (www.worldathletics.org into World Athletics (WA) scores [18]. If the “better” recent performance of participants was achieved in shorter events than 1500 m, they were allocated to the SAM group, and

Int. J. Environ. Res. Public Health2022,19, 1447 3 of 11 if the “better” recent performance was shown in longer events than 1500 m, they were allocated to the EAM group. Eligibility criteria required that participants: (a) were current elite athletes, considered those who competed internationally or at senior category national championships, to accord with widely used criteria used to de ne elite athletes [19]; (b) had at least 5 years of system- atic training experience (Table); (c) were free from health problems or musculoskeletal injuries that could compromise testing performance during at least 6 months prior to the beginning of the study. All the participants were informed of the study procedures and signed a written informed consent form prior to initiating the study. The study protocol adhered to the tenets of the Declaration of Helsinki and was approved by the Institutional Review Board of Pablo de Olavide University (935/CEIH/2019). Table 1.Performance characteristics of participants. Competitive Level Greatest Competition in Which Athletes Participated Other Relevant Information World Athletics Scores SB (min:s.cs) Mean SD Mean SD World (n = 2) European (n = 11) National (n = 2) Olympic Games European Championships National Championships 2 x national record holders 3 European medalists 2 x World Championship nalists 7 national champions 800 m (n = 7): 987.4 120.1 1500 m (n = 15): 1011.6 86.0 3000 m (n = 5): 974.0 168.2 800 m (n = 7): 1:51.24 4.29 1500 m (n = 15): 3:47.44 6.8 3000 m (n = 5): 8:32.45 27.5 SB, season-best time; SD, standard deviation. 2.2. Study Design A cross-sectional study was designed in two different testing sessions, with 1 week apart: (1) participants performed an incremental treadmill test through which physiological performance outcomes were obtained; and (2) participants performed a testing battery in this order: maximal vertical and horizontal jumps and maximal 40 m and 100 m sprints. Prior to the beginning of the second testing session, all athletes performed a 15-min warm- up and a familiarization process to ensure the correct execution of all testing procedures. In addition, athletes were asked to avoid intense exercise in the

performed a testing battery in this order: maximal vertical and horizontal jumps and maximal 40 m and 100 m sprints. Prior to the beginning of the second testing session, all athletes performed a 15-min warm- up and a familiarization process to ensure the correct execution of all testing procedures. In addition, athletes were asked to avoid intense exercise in the 24 h before testing, apart from ensuring that the training load was similar for all athletes in the last 3 days prior to testing to avoid fatigue-affected results. These sessions were carried out in the High Performance Centre of the city in June 2019, which refers to the competitive period of all the athletes participating in the study. 2.3. Testing Session 1 Maximal aerobic speed (MAS): The maximal aerobic speed was determined through an incremental treadmill test (Technogym, Exite Run 600, Cesena, Italy) that was performed 1 week before the aforementioned testing session. All participants carried out a standard- ized warm-up consisting of low-intensity running and, thus, started the test at 8.0 km h 1 , with 2% as the treadmill slope and progressive increments of 0.5 km h 1 every 30 s until exhaustion. Exhaustion was considered when the runners volitionally declared their inca- pacity to continue at the predetermined pace. During the test, gas analyses were conducted since the participants breathed through a low dead space (90 mL), low resistance (5.5 cm H2O at 510 L min 1 ) facemask, and turbine assembly. Gases were drawn continuously from the facemask to a breath-by-breath gas analyzer (Fitmate Pro, Cosmed, Rome, Italy) through a 2 m sampling line (0.5 mm internal diameter) and were analyzed for O2and CO2(with a 200 ms delay). A turbine volume transducer (Interface Associates, Alifovieja, CA, USA) determined the expired volumes. Prior to each test, the breath-by-breath gas analyzer was calibrated by using gas mixtures (Linde Gas, London, UK) of concentrations previously known. The turbine was also calibrated prior to each test with a 3 L calibration syringe (Hans Rudolf, Shawnee, KS, USA). Oxygen uptake was calculated and displayed on a breath-by-breath basis. A computer was

USA) determined the expired volumes. Prior to each test, the breath-by-breath gas analyzer was calibrated by using gas mixtures (Linde Gas, London, UK) of concentrations previously known. The turbine was also calibrated prior to each test with a 3 L calibration syringe (Hans Rudolf, Shawnee, KS, USA). Oxygen uptake was calculated and displayed on a breath-by-breath basis. A computer was used to integrate the volume and concen- tration signals by converting values from analog to digital format. In this conversion, the

Int. J. Environ. Res. Public Health2022,19, 1447 4 of 11 delay of the gas transit through the capillary and the room temperature was taken into account. MAS was considered as the slowest speed at which maximum oxygen uptake was attained [5]. Anaerobic speed reserve (ASR): ASR was calculated as the difference between MAS and MSS. ASR is a good re ection of the speed range that an athlete possesses, considering these two milestones. With this information, it is possible to calculate the speed reserve ratio (SRR) as the coef cient of “maximal sprint speed (km h 1 )/maximal aerobic speed (km h 1 )”. 2.4. Testing Session 2 All participants performed a 15-min warm-up consisting of 5 min of jogging and 5 min of lower limb dynamic stretching. During the last 5 min, as part of the speci c warm-up, participants also performed three progressive sprints of 40 m at 50%, 70%, and 90% effort. As a familiarization process, all athletes performed progressive trials in the case of jumps and progressive accelerations from the starting line in the case of races. Vertical jump—countermovement (CMJ): Just after warming up and familiarization, the runners carried out a maximum vertical jump. They started from an upright position, with their hands on their waists. Thus, they performed a countermovement by exing their knees up to 90 and jumping as high as possible. During the ight phase of the jump, they should maintain their knees extended up to 180 , without hyperextending their hips [20]. Horizontal jump—standing long jump (SLJ): Athletes were instructed to perform a maximal horizontal jump from a starting line, with both feet simultaneously and arms swinging, and without a run-up. The maximal metered performance was measured by taking into account the rear part of the most indented heel [21]. For both vertical and horizontal jumps, participants performed three trials, with 2 min as the inter-trial passive recovery, and the best one was recorded (in meters). A sports professional external to the investigation supervised the correct execution of jumps, and an OptoGait Photoelectric Cell System (OptoGait, Microgate, Bolzano, Italy) was used. 40

rear part of the most indented heel [21]. For both vertical and horizontal jumps, participants performed three trials, with 2 min as the inter-trial passive recovery, and the best one was recorded (in meters). A sports professional external to the investigation supervised the correct execution of jumps, and an OptoGait Photoelectric Cell System (OptoGait, Microgate, Bolzano, Italy) was used. 40 m sprint: After 4 min of rest, participants performed three maximal sprints of 40 m, with 4 min as the inter-trial period of rest. The fastest one was considered for the analysis. Athletes were instructed to start from a crouching position (staggered stance). A previously validated simple eld method was used to compute sprint performance and mechanical outputs [13]. A Stalker Acceleration Testing System (ATS) II radar device (Stalker ATS II, Applied Concepts, Dallas, TX, USA) at 46.9 Hz was employed to collect velocity–time data of each sprint. The radar device was attached to a tripod 10 m from the starting line at a height of 1 m, which corresponded to the height of participants' center of mass. Based on Samozino's method, sprint mechanical variables were obtained from the velocity–time data [13,14]. This validated method is a macroscopic biomechanical model to estimate external horizontal force production during sprinting from the velocity of the center of mass using the inverse dynamic approach [14]. The outcomes regarding the F-V pro le were: maximal theoretical force (F0), maximal theoretical velocity (V0), F-V slope, maximal power (Pmax), decrease in the ratio of horizontal-to-resultant force (DRF), maximal ratio of horizontal-to-resultant force (RFpeak), and this same variable at 10 m (RF_10m). DRF and RFpeak are commonly employed to assess mechanical effectiveness and have been correlated with sprint performance. From the data of this test, we also calculated MSS. We also obtained sprint split times at 10 m, 20 m, 30 m, and 40 m. 100 m sprint: After 4 min of rest, athletes performed two maximal sprints of 100 m from a crouching position (staggered stance), with 10 min of rest between sprints. For stride pattern/mechanical variables and partial times, an optoelectronic system (Optojump Next Microgate,

calculated MSS. We also obtained sprint split times at 10 m, 20 m, 30 m, and 40 m. 100 m sprint: After 4 min of rest, athletes performed two maximal sprints of 100 m from a crouching position (staggered stance), with 10 min of rest between sprints. For stride pattern/mechanical variables and partial times, an optoelectronic system (Optojump Next Microgate, Bolzano, Italy) was installed on the lane of an indoor track to obtain running kinematics from 30 to 40 m during the maximum velocity phase and from 80 to 90 m during the decrement of velocity phase. This material permits measurement of contact time on the oor (CT), ight time (FT), step time (ST), stride length (SL), stride ight (SF), and step velocity (SV). SL asymmetry (SLasy) was calculated as the absolute

Int. J. Environ. Res. Public Health2022,19, 1447 5 of 11 difference of distance covered on three left-foot strides minus the distance covered on three right-foot strides. SR, SL, FT, and CT were measured and averaged from the third up to the eighth last stride of the approach. Furthermore, partial times were collected for 21-to-30 m, 30 m, 60 m, 80 m, and 100 m. For vertical and leg stiffness, step characteristics of CT and FT sampled at 1000 Hz were captured via a series of ground-based photoelectric cells (Microgate: OptoJump, Bolzano, Italy) positioned between 40 and 49 m of the sprint track. This part of the sprint is often the segment where runners achieved Vmax (as shown in pilot testing). The spring–mass model [22,23] was used to compute the mechanical leg behavior during the ground contact. The calculation of peak vertical ground reaction force (Fmax), vertical stiffness (Kvert), and leg stiffness (Kleg) was based on the method validated by Morin et al. (2005) [24]. 2.5. Statistical Analyses Descriptive data are presented as means and standard deviations. The degree of the linear relationship between variables was examined using Pearson's product moment correlation. Independent samplet-tests and Cohen'sdeffect size (ES) with 95% con dence intervals were used to compare the sprint mechanical F-V pro le (F0, V0, Pmax, DRF, and RFpeak), ASR, mechanical variables of stride patterns, and MSS between types of middle-distance runners. The scale used for interpreting the magnitude of the effect size was speci c to training research: negligible (<0.2), small (0.2–0.49), moderate (0.5–0.79), and large ( 0.8) [25]. Statistical signi cance was set atp 0.05. Data were analyzed using SPSS 20.0 software (SPSS Inc. Chicago, IL, USA) and Of ce Excel 2010 (Microsoft Corporation, Redmond, WA, USA). 3. Results Table chanical pro le, and performance of SAM and EAM. Signi cant differences were found between groups in variables describing aerobic–anaerobic performance, SLJ distance, 100 m sprint performance, and sprint mechanical pro le and effectiveness. In all variables, SAM displayed a greater performance than EAM. Table chanical characteristics and physiological performance determinants derived from the incremental treadmill test that participants

The study compares performance metrics between elite male middle-distance runners specialized in different events.