Exploratory Analysis of Sprint Force-Velocity Characteristics, Kinematics and Performance across a Periodized Training Year: A Case Study of Two National Level Sprint Athletes

bjective: This case study aimed to explore changes to sprint force-velocity characteristics across a periodized training year (45 weeks) and the in uence on sprint kinematics and performance in national level 100-meter athletes. Force-velocity characteristics have been shown to differentiate between performance levels in sprint athletes, yet limited information exists describing how charac- teristics change across a season and impact sprint performance, therefore warranting further research. Methods:Two male national level 100-meter athletes (Athlete 1:22 years, 1.83 m, 81.1 kg, 100 m time: 10.47 s; Athlete 2: 19 years, 1.82 cm, 75.3 kg, 100 m time: 10.81 s) completed 12 and 11 force-velocity as- sessments, respectively, using electronic timing gates. Sprint mechanical characteristics were derived from 30-meter maximal sprint efforts using split times (i.e., 0–10 m,0–20 m, 0–30 m) whereas step kinematics were established from 100-meter competition performance using video analysis.Results: Between the preparation (PREP) and competition (COMP) phase, Athlete 1 showed signi cantly large within-athlete effects for relative maximal power (P

force-velocity as- sessments, respectively, using electronic timing gates. Sprint mechanical characteristics were derived from 30-meter maximal sprint efforts using split times (i.e., 0–10 m,0–20 m, 0–30 m) whereas step kinematics were established from 100-meter competition performance using video analysis.Results: Between the preparation (PREP) and competition (COMP) phase, Athlete 1 showed signi cantly large within-athlete effects for relative maximal power (P MAX), theoretical maximal velocity (v 0), maximum ratio of force (RF MAX), maximal velocity (V MAX), and split time from 0 to 20 m and 0 to 30 m ( 1.70 ES 1.92,p 0.05). Athlete 2 reported signi cant differences with large effects for relative maximal force (F 0) and RF MAXonly (ES: 1.46,p 0.04). In the PREP phase, both athletes reported almost perfect correlations between F 0, P MAXand0–20 m(r = 0.99,p 0.01), however in the COMP phase, the relationships between mechanical characteristics and split times were more individual. Competition performance in the 100-meter sprint (10.64 0.24 s) showed a greater reliance on step length (r 0.72,p 0.001) than step frequency to achieve faster performances. The minimal detectable change (%) across mechanical variables ranged from 1.3 to 10.0% while spatio-temporal variables were much lower, from 0.94 to 1.48%, with Athlete 1 showing a higher `true change' in performance across the season compared to Athlete 2.Conclusions:The estimated sprint force-velocity data collected across a training year may provide insight to practitioners about the underpinning mechanical characteristics which affect sprint performance during speci c phases of training, plus how a periodized training design may enhance sprint force-velocity characteristics and performance outcomes. Keywords:force; velocity; power; sprint; training; biomechanics; pro le 1. Introduction Across a training year, sprint athletes typically progress through a periodized training program aimed at peaking towards major competitions including national championships. Training components within a sprint program generally include acceleration and maximal velocity sprinting, resistance training and plyometrics [1] which aim to enhance neuromus- cular, biomechanical and technical sprint characteristics. However, the overall aim of all sprint programs should be to improve an athlete's ability to run fast. Sprint running re- quires athletes to overcome inertia and accelerate from a

championships. Training components within a sprint program generally include acceleration and maximal velocity sprinting, resistance training and plyometrics [1] which aim to enhance neuromus- cular, biomechanical and technical sprint characteristics. However, the overall aim of all sprint programs should be to improve an athlete's ability to run fast. Sprint running re- quires athletes to overcome inertia and accelerate from a stationary start to a high maximal Int. J. Environ. Res. Public Health2022,19, 15404.

Int. J. Environ. Res. Public Health2022,19, 15404 2 of 16 velocity [2]. From a mechanical perspective, the ability to complete this movement task requires the athlete to apply a large amount of force and power in the horizontal direction at an increasing running velocity [3]. Although sprint mechanical characteristics have been assessed in various athletic populations in cross-sectional studies [4,5], there is a paucity of longitudinal research investigating individual mechanical changes in sprint athletes in response to speci c periods of training. An analysis of sprint mechanical characteristics and performance is therefore of interest to practitioners as it may provide greater insight into training program design and periodization structure of sprint training and competition. To quantify the mechanical determinants which underpin sprint performance, a eld method known as force-velocity (F-v) pro ling has been proposed by Samozino et al. [3]. Using an inverse dynamics approach to the body center of mass, the eld method describes the mechanical output of over-ground maximal sprint running by modelling position- time data to indirectly estimate the underlying mechanical properties (i.e., forces) which produced the sprint performance [6]. The key mechanical variables obtained from sprint F-v pro les include theoretical maximal force (F0), theoretical maximal velocity (v0) and theoretical maximal power (PMAX) [3], which determine the intercepts of the inverse linear F-v relationship, and the parabolic relationship between power and velocity (P-v) [3]. The mechanical characteristics obtained by sprint force-velocity and power-velocity data can be used as a quantitative approach to improve the planning of sprint training to in uence sprint outcomes during competition. The aim of sprint athletes who compete in traditional track events is to cover the competition distance (i.e., 100-meter) in the shortest time possible, however the aim of the coach is to periodize the training load and content to ensure the athlete produces their best performance at key times in the year, for example national championships. Furthermore, at different stages of the year, the training focus will likely change from attempting to improve various bio-motor abilities including strength and power, to more sprint-speci c foci including acceleration, maximal velocity and speed

to periodize the training load and content to ensure the athlete produces their best performance at key times in the year, for example national championships. Furthermore, at different stages of the year, the training focus will likely change from attempting to improve various bio-motor abilities including strength and power, to more sprint-speci c foci including acceleration, maximal velocity and speed endurance [7], a planning process known as periodization. Periodization of physical training has been identi ed as key to developing physiological and neuromuscular adaptations to maximize performance at speci c periods during the training year [7]. Despite its recent widespread use in team sport to differentiate between ability level, eld position and to individualize training strategies [5,8–10], an investigation into changes to mechanical characteristics in sprint athletes across a training year is yet to be explored. Recent evidence has highlighted the importance of maximal power (PMAX) during the sprint action and the in uence of individual F-v characteristics (i.e., SFV) to sprint accelera- tion performance [11]. Therefore, it would be useful information for sprint practitioners to understand mechanical changes across the training year and the relationships with sprint outcomes. Previous longitudinal case studies of junior (7 weeks, 100-meter personal best: 10.89 0.21 s) and senior level (5 months, 100-meter personal best: 10.16 0.16) sprinters focused on strength training and its effect on sprint performance [12], plus changes to step kinematics in response to periodized training [13]. Sprint performance changes in junior athletes were deemed inconclusive; however, it was hypothesized changes to performance in senior elite athletes was explained by the periodization of speci c training components which was associated with an increase in force production, along with the ability to pro- duce force rapidly leading to increases in step velocity and frequency during phases of low volume resistance training and high-intensity sprint training [13]. However, to the authors' knowledge, no research exists examining changes to mechanical characteristics and the sprint F-v pro le in national level sprint athletes across a training year. Therefore, the aim of this case study was to investigate how sprint mechanical char- acteristics change across a

and frequency during phases of low volume resistance training and high-intensity sprint training [13]. However, to the authors' knowledge, no research exists examining changes to mechanical characteristics and the sprint F-v pro le in national level sprint athletes across a training year. Therefore, the aim of this case study was to investigate how sprint mechanical char- acteristics change across a track and eld season (~45 weeks) in two male sprint athletes who quali ed for their national championships. A secondary aim was to explore how periodized sprint training in uences mechanical and spatio-temporal characteristics, step kinematics and sprint performance outcomes. We hypothesized that, as the periodization model changed between training phases and the mechanical load was reduced [7], it would likely result in improved sprint outcomes due to an enhanced F-v pro le, plus optimized

Int. J. Environ. Res. Public Health2022,19, 15404 3 of 16 step kinematics for each athlete during 100-meter performance, however inter-athlete differences would be evident based on initial F-v characteristics and level of performance. 2. Materials and Methods 2.1. Participants Two male sprint athletes who qualified for their national track and field championships (2021–22) in the 100-meter sprint event volunteered to participate in this study. Both athletes (Athlete 1: 22 years, 1.83 m, 81.1 kg, 100-meter time: 10.47 s; Athlete 2:19 years, 1.82 m, 75.3 kg, 100-meter time: 10.81 s) met the inclusion criteria of completing a minimum of 10 sprint force-velocityassessments across the training and competition period. Further inclusion criteria included participants aged over 18 years of age. Exclusion criteria maintained that participants needed to be six-months free of musculoskeletal injuries which may prevent them from performing maximal effort sprints. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Social and Behavioral Research Ethics Committee at Flinders University (Ethics App Number: 8146). Personal best data and World Athletics points during the past12 monthsof competition were collected from World Athletics [14] to establish a baseline for the performance levels of both athletes (100 m: 10.81 0.42/895 56.5 points, 200 m: 21.98 1.01/898 91.9 points). 2.2. Study Design A case study design was used to monitor the sprint athletes from when they began their general preparation phase training at the end May 2021 and were followed through to the national championships at the start of April 2022 (~45-weeks). During this period, the athletes completed 12 (Athlete 1) and 11 (Athlete 2) force-velocity assessments, respectively, while also competing in 100-meter and 200-meter events (Table). Table 1. Timeline and number of force-velocity assessments and competitions across the training year. Date Phase Type Athlete 1 Athlete 2 June-21 PREP FV 1 1 July-21 PREP FV 2 2 August-21 PREP FV 2 2 October-21 PREP 100 m/200 m - 3 November-21 PREP FV 1 1 November-21 PREP 100 m/200 m - 1 December-21 PREP 100 m/200 m - 1 December-21 PREP FV 1 1 January-22 COMP FV

across the training year. Date Phase Type Athlete 1 Athlete 2 June-21 PREP FV 1 1 July-21 PREP FV 2 2 August-21 PREP FV 2 2 October-21 PREP 100 m/200 m - 3 November-21 PREP FV 1 1 November-21 PREP 100 m/200 m - 1 December-21 PREP 100 m/200 m - 1 December-21 PREP FV 1 1 January-22 COMP FV 1 1 January-22 COMP 100 m/200 m 4 3 February-22 COMP FV 1 1 February-22 COMP 100 m/200 m 2 4 March-22 COMP FV 2 2 March-22 COMP 100 m/200 m 2 3 April-22 COMP FV 1 - April-22 COMP 100 m/200 m 2 2 PREP = preparation phase, COMP = competition phase, FV = force-velocity pro le, 100 m/200 m = competition performance. Training components including acceleration, speed, speed endurance and strength endurance, were periodized across the year to ensure the development and retention of speci c physiological and neuromuscular adaptations [15,16]. The structure of training was de ned by the two track and eld coaching staff working with Athlete 1 and Athlete 2 and included running based sessions on grass elds, hills and synthetic tracks, plyometrics, along with gym-based resistance training sessions focused on developing aspects of the force-velocity continuum [17]. Typical training cycles and periodization of training com- ponents for the season are outlined in Table. During the preparation (PREP) phase, a 3:1 summated step loading model of periodization, FigureA, was implemented which

Int. J. Environ. Res. Public Health2022,19, 15404 4 of 16 allows for progressive overload of training modalities across three microcycles (~21 days), which is then followed by one microcycle (~7 days) of unloading, i.e., reduced training load [7,18,19]. The unloading period provides time for athlete regeneration and physiologi- cal adaptations to occur, while limiting the potential for overtraining [18]. Furthermore, the step-loading model of periodization also adds an aspect of inter-mesocycle contrast which may increase and stimulate adaptation(s) across the season [18]. The competition (COMP) phase was characterized with an undulating periodization model (also referred to as non-linear periodization), FigureB, across the mesocycle (~4 weeks) [ 20]. Undulating periodization provides more frequent changes to stimuli (i.e., volume, intensity) which have been reported to be more conducive to optimize gains in strength [20]. During the COMP phase, this approach to periodization has been implemented to provide a micro-dosing effect to training prior to reducing the training load ahead of a competition [21]. Table 2.Typical training microcycles across preparation phases during the training year. Preparation Phase (General: June–September) DAY SUNDAY MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY INTENSITY MODERATE MODERATE MODERATE MODERATE- HARD MODERATE EASY MODERATE- HARD LOCATION GRASS INCLINE GRASS FIELD WEIGHTROOM TRACK WEIGHTROOM POOL/BEACH TRACK MAIN SESSION AM Hill runs PM Speed Endurance PM Accumulation- Strength- Speed (UB) PM Special Endurance PM Accumulation- Speed- Strength (LB) Regeneration AM Acceleration/ Speed Weightroom (TB) Maximal effort Preparation Phase (Speci c: October–December) DAY SUNDAY MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY INTENSITY MODERATE EASY- MODERATE MODERATE- HARD MODERATE HARD EASY MODERATE- HARD LOCATION WEIGHTROOM GRASS FIELD TRACK WEIGHTROOM TRACK POOL/BEACH TRACK MAIN SESSION AM Intensi cation -Strength- Speed (LB) PM Varied-paced runs PM Acceleration/ Special Endurance PM Intensi cation- Speed- Strength (UB) PM Maximal Velocity + Tempo Regeneration AM Acceleration/ Speed Endurance Competitive Phase (January–March) DAY SUNDAY MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY INTENSITY EASY EASY- MODERATE MODERATE- HARD MODERATE MODERATE EASY MODERATE LOCATION WEIGHTROOM GRASS FIELD TRACK WEIGHTROOM TRACK POOL/BEACH TRACK MAIN SESSION PM Strength Circuits (TB) PM Varied-paced runs PM Acceleration/ Speed PM Power (TB) PM Maximal velocity + Tempo Regeneration PM Competition

+ Tempo Regeneration AM Acceleration/ Speed Endurance Competitive Phase (January–March) DAY SUNDAY MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY INTENSITY EASY EASY- MODERATE MODERATE- HARD MODERATE MODERATE EASY MODERATE LOCATION WEIGHTROOM GRASS FIELD TRACK WEIGHTROOM TRACK POOL/BEACH TRACK MAIN SESSION PM Strength Circuits (TB) PM Varied-paced runs PM Acceleration/ Speed PM Power (TB) PM Maximal velocity + Tempo Regeneration PM Competition (UB = Upper body, LB = Lower body, TB = Total body). Figure 1. Periodization models used across the training year. (A): represents the summated step- loading periodization model for the preparation phase; (B): represents the undulating periodization model during the competition phase.

Int. J. Environ. Res. Public Health2022,19, 15404 5 of 16 2.3. Methodology Sprint F-v assessments occurred outdoors on synthetic running tracks during training sessions with Athlete 1 and Athlete 2 completing 12 and 11 assessments, respectively. No wind measurements were obtained. Body mass and environmental conditions (i.e., ambient temperature, barometric pressure) were collected on the day of each sprint F-v assessment due to its effect on F-v pro le calculation. The biomechanical model to establish the F-v pro le has previously been reported [3] and validated [22] when compared with direct measurement of ground reaction forces (GRF) from in-ground force plates and has been used in previous interventional studies [23]. Position-time data from the electronic timing games were used in a custom-made Microsoft Excel spreadsheet [24] to derive and model all force-velocity variables using the equations developed by Samozino et al. [3]. Recent explanations on the procedures used to determine sprint F-v characteristics are provided by Morin et al. [22]. Prior to the sprint F-v assessment, a standardized 45 min warm-up consisting of light jogging, dynamic running-based drills and movements, and 4–8 linear accelerations, over 10–40 m, progressing from sub-maximal to maximal was undertaken by each participant. Individually, participants then performed 30-meter maximal sprint efforts from either a four-point start or from starting blocks, wearing track spiked shoes. For each force-velocity assessment, the average splits times (i.e., 0–10 m, 0–20 m, 0–30 m) acrossthree trials was used for reliability purposes and to determine the minimal detectable change in performance, in line with previous research [25,26]. Timing of sprint efforts were collected with electronic timing gates (Freelap Timing System, Fleurier–Switzerland). The Freelap Timing System is an electronic timing system which records the position-time data via a radio frequency connection between an antenna located in the FxChip on the athlete, and the transmitter on the track (Tx Junior Pro). The radio frequency transmission eld is suggested to be 0.80 m by the manufacturer. Timing began when the athlete moved their hand off the touch pad resting on the ground (Tx Touch Pro), with split times recorded at each 10-meter interval once the

antenna located in the FxChip on the athlete, and the transmitter on the track (Tx Junior Pro). The radio frequency transmission eld is suggested to be 0.80 m by the manufacturer. Timing began when the athlete moved their hand off the touch pad resting on the ground (Tx Touch Pro), with split times recorded at each 10-meter interval once the athlete passed the timing gate (Tx Junior Pro Transmitter). The FxChip was positioned on the athletes at the midline of the waistbelt, adjacent to the anterior superior iliac crest (ASIS). Speci cations for setting up the touch pad and timing gates are detailed in Figure. The reported bene ts of using a `touch-pad' approach to start the timing system is a possible reduction in the body swing and momentum gathered prior to the sprint start which may occur in a standing start [27]. Previous research using a `touch pad' reported strong between-test reliability, Intraclass Correlation Coef cient (ICC) = 0.92, and a typical error of 0.03 s over a 10-meter sprint distance, yet the authors noted the lack of familiarization of the starting technique with junior rugby players [27]. At the conclusion of each sprint effort, electronic timing gate data was sent via Bluetooth to an application (MyFreelap) on a smartphone device. Reaction time is not included in the total sprint time, which at world class level is typically 0.17 0.18 0.03 s [28]. Timing gate data was also provided as feedback to athletes at the conclusion of each sprint effort. Between each sprint effort there was 5 min passive recovery period to ensure readiness before the next sprint and to limit fatigue. Figure 2. Electronic timing gate (Freelap) setup to record split times (10-meter intervals) from 0–30 m. The training year was periodized into two categories for statistical analysis: PREP (i.e., general and speci c preparation phases—a focus on preparing the athletes for competition) and COMP (i.e., competitive phase—the focus is on achieving performance outcomes

The study investigates sprint performance changes in two national level athletes over a training year.