The (Rocky) Road to the Olympic Games: A Longitudinal Case Study on the Preparation, Monitoring, and Training of an Elite Weightlifter

Abstract

This case study provides a comprehensive, longitudinal analysis of an elite weightlifter’s performance, neuromuscular ability, and barbell kinematics over a 2.9-year period in preparation for the Tokyo 2020 Olympic Games. Monitoring of training load, weightlifting performance, and measures of force production were conducted periodically throughout the lead up to the Olympic Games. Data were analyzed utilizing upper and lower tail standard deviations between time points. Key findings show performance improvements in 2019, with notable gains in the capacity to express higher forces, as measured by the isometric mid-thigh pull and countermovement jump. COVID-19 led to a decrease in training intensity (81 ± 6% to 75 ± 6% 1RM), which subsequently resulted in reduced performance (360 kg to 340 kg total). Following the pandemic, training intensity increased (75 ± 6% to 84 ± 4%), particularly during the taper phase, which positively impacted peak barbell vertical velocity (1.87 ± 0.01 vs. 1.94 ± 0.01 m.s⁻¹). COVID-19 necessitated a shift towards General Physical Preparedness, reflecting the challenge of limited training resources. The tapering strategies, involving volume reduction and increased intensity, were in line with established weightlifting practices. This study highlights the importance of adaptability in supporting elite athletes, emphasizing the need for flexible monitoring strategies during periods of disruption, whilst maintaining some ability to objectively identify meaningful changes in physical preparedness. Findings from this case study suggest that tailored adjustments to training load were critical in enhancing performance. Therefore, adopting pragmatic approaches, such as modifying training relative to external constraints and stressors with a holistic approach to monitoring, can help optimize performance.

1. Introduction

Weightlifting is an Olympic sport where athletes compete for their respective countries following a qualification period. The qualification process for the 2020 Tokyo Olympic Games required athletes to compete in gold, silver, and bronze-ranked events hosted by the International Weightlifting Federation (IWF) between the dates of November 2018 and May 2021, with an additional year of qualification added due to COVID-19. To achieve Olympic qualification, athletes are required to compete in at least six ranked events, with at least one being of a gold standard and another being either gold or silver. The top 8 ranked athletes by the end of the qualification period would be provided with a place at the Olympics, with an additional 5 provided to the highest ranked continental athlete, 1 tripartite athlete, and an additional place for re-allocation of an unused quota place, totaling a number of 14 athletes per weight category. As the pinnacle of international competition, the Olympics represents the ultimate goal for weightlifters, making optimal preparation critical for success. A comprehensive approach to training and performance monitoring is thus necessary to peak at the right time and secure qualification [1].

Weightlifting can be classified as a strength–speed sport [2], where athletes perform the snatch and the clean and jerk, each with up to three attempts. The combined total of the highest successful lifts in both movements determines an athlete’s final total (kg). The previous literature has determined that higher performing weightlifters are able to generate greater vertical ground-reaction forces than their lesser-performing counterparts [3]. Furthermore, successful lifts are characterized by the ability to appropriately apply this force to the barbell, generating a greater vertical acceleration vector [4]. It can therefore be deduced that the ability to express high levels of force within the technical constraints underpins successful performance in weightlifting. Based on this premise, training must be structured to develop both the neuromuscular strength and technical proficiency of the athlete. These qualities can be systematically enhanced through sequential training blocks that target specific adaptations [5]. As athletes progress toward competition, these adaptations should increasingly transfer to the demands of the competitive lifts, ensuring both improved force production and technical execution under maximal loads.

Longitudinal monitoring of changes in neuromuscular ability, biochemical adaptations, muscle cross-sectional area, and overall weightlifting performance have previously been reported in national and international level weightlifters [6,7,8,9]. Surrogate tests that are often used consist of maximal and ballistic force expression by way of isometric mid-thigh pull (IMTP) or a jump (i.e., countermovement or squat). Variables extrapolated from such tests, such as peak force, rate of force development, jump height, and net propulsive impulse, have all been shown to have strong to very-strong relationships with weightlifting performance (r = 0.68–0.85) [10,11]. The consensus of utilizing such variables for monitoring purposes is that they carry high sensitivity to change, with the response of each variable dependent on the training block focus and thus training volume and intensity experienced [6,7,8]. While insightful, the aforementioned studies only consider the physical preparation of weightlifting; investigations into technical changes are far less common, with research often characterizing technique through barbell trajectories [12]. For a coach to make well-informed decisions on exercise selection and loading, a holistic approach of monitoring both neuromuscular and technical conditions throughout training should be considered. However, the practicality of this within a high-performance environment using group-based research designs with optimal sample sizes can be difficult. This becomes inherently more impractical in individual sports, such as weightlifting, where controlled interventions may not be viable given the individual requirements of each athlete. Therefore, single-subject case studies, particularly at an elite level, can provide necessary information on the effect of training on the physical preparedness of the athlete and its concurrent effect on performance [13].

Given the limited research on the long-term preparation of elite male weightlifters, especially studies exploring both neuromuscular adaptations and barbell kinematics, this case study addresses a critical gap in the existing literature. Although Sandau and Granacher [14] have explored similar themes, research on the temporal evolution of performance at the highest levels of competition remains limited. The Tokyo 2020 Olympics marked a historic moment with the inclusion of the first Refugee Olympic Team (EOR) weightlifter in the men’s 96 kg category. Due to his refugee status, the athlete could not follow the typical qualification process. This case study offers a unique, longitudinal analysis of his performance, focusing on the neuromuscular changes, barbell kinematics, and the impact of COVID-19 disruptions on his preparation. The findings contribute novel insights into the long-term development and competitive preparation of an elite-level weightlifter, a critical addition to the sparse body of longitudinal data in the field. Moreover, this study not only provides insight into longitudinal changes, but also highlights the adaptability and resilience required to navigate unprecedented challenges. By exploring the combination of physical preparation and technical proficiency, this case study offers valuable perspectives on how athletes can overcome external barriers to achieve elite-level performance while also providing practitioners with insight into adapting monitoring and training processes.

2. Materials and Methods

2.1. Experimental Approach to the Problem

A quasi-experimental case study was conducted over 2.9 years to evaluate neuromuscular, technical, and performance changes over a series of competitions leading into the 2020 Olympic Games. Given the constraints dictated by COVID-19, the training and monitoring process was adapted throughout the lead up to the Olympics. Neuromuscular performance was monitored using IMTP and countermovement jump (CMJ). Barbell analysis was conducted on the snatch only using an inertial measurement unit (IMU) interfaced with a native application on an iPad, where peak vertical velocity was assessed. Due to changes in body weight category, competition performance of absolute load was monitored as well as relative to weight category. Leading into the Olympics, historic competition performances achieved by the opposition were calculated as mean ± 1 standard deviation (SD) along with success rate and average increment between attempts as a percentage to help identify opportunities to achieve the highest possible rank. This was used synonymously with the predicted performance zone to help identify the minimum loads required to achieve a top 10 finish. Over the 2.9-year period a total of 22 blocks of training were employed, consisting of 4–6 sessions per week with each session lasting approximately two hours. Adaptations to the program were made when necessary to account for injuries, illness, and work schedule demands of the athlete.

2.2. Participant

The athlete was a 25-year-old male weightlifter competing in the 96 kg and 102 kg weight categories within the United Kingdom (UK), with his primary weight category being 96 kg. He had previously competed in weightlifting and had training experience of 10 years at the time. His accolades prior to the initiation of this case study include competing at a continental championship (2013) and the Commonwealth Games (2014), at 94 and 85 kg, respectively, achieving 5th in both cases. Alongside his training, he was also a full-time mental health nurse for the National Health Service (NHS), making him a dual-career athlete and a key worker during the COVID-19 pandemic. The athlete was part of the International Olympic Committees (IOC’s) solidarity support program and was a hopeful for the Tokyo Olympic Games as part of the Refugee Olympic Team (EOR). The athlete provided written consent for his data to be used, which was collected as part of his regular performance monitoring. Ethical approval was granted by an institutional organization (#30117).

2.3. Procedures

2.3.1. Neuromuscular Performance Data

Following each domestic competition, the athlete was asked to partake in the CMJ and IMTP. Every effort was made to ensure that the athlete had a sufficient recovery period prior to the testing day, and it was mutually decided that this would be conducted within the first 5 days following a competition. This decision was to ensure that the testing results did not have any psychological influence on the athlete’s preparedness going into competition, as well as not being affected by fatigue induced by normal training. Prior to testing, he was given a self-selected time to perform a general warm-up, which typically consisted of dynamic stretches of the lower body followed by 2–3 submaximal efforts on the CMJ and IMTP, respectively. All neuromuscular performance tests were conducted in the morning to reduce any diurnal effects.

2.3.2. Countermovement Jump

The CMJ was performed on a portable force plate (Kistler 9286, Winterhur, Switzerland) sampling at 1000 Hz. The athlete was asked to stand as still as possible on the force plate, with arms akimbo, for a minimum of 1 s, before he was instructed to jump as high as possible whilst keeping his hands on his hips [15]. Once the athlete was ready, he was asked to perform 2 maximal CMJ’s interspersed with ~1 min rest between trials. All raw force–time data were extracted for analysis in a custom spreadsheet [15]. The variables extracted were net propulsive impulse (propIMP), propulsion time, and countermovement depth, where net propulsive impulse was defined as the change in force by time from minimum velocity to 0 velocity, less the system weight. The time this took and the depth at which it started were defined as the propulsion time and countermovement depth, respectively [16]. This ensures that any changes in jump strategies that concurrently influence propulsive impulse are accounted for [16,17].

2.3.3. Isometric-Mid Thigh Pull

The IMTP was conducted on a portable force plate (Kistler 9286, Winterhur, Switzerland) sampling at 1000 Hz, placed within a custom-made rig (Absolute Performance, Cardiff, UK). The bar was adjusted to a height that allowed the athlete to assume a position that approximated the beginning of a second pull of the clean. Hip and knee angles were assessed at each testing session using a hand-held goniometer to verify that an angle of 140–150° and 125–145° was achieved, respectively [18,19]. To eliminate the effect of grip loss, lifting straps and chalk were used. Weightlifting shoes and a belt were also used during the test. Once familiar with the setup up the athlete was asked to perform 2–3 submaximal pulls to familiarize himself with the task and as part of his warm-up, familiarizing himself with taking slack out of the bar whilst remaining relaxed [19]. The athlete was encouraged to drive the floor away as “fast and as hard as possible”. Each trial lasted approximately 3–5 s. All raw force–time data were extracted for analysis in a custom spreadsheet [14], where net peak force (NPF), relative net peak force (relNPF), and force at 150 and 200 ms (F150, F200) were extracted, where NPF was the maximum force achieved less system weight (i.e., athlete weight + pretension), relNPF was the aforementioned divided by the athlete body mass, and with F100 and F200 being the net force achieved at 100 and 200 ms, respectively.

2.3.4. Competition Performance

Domestic competition performance was recorded as the heaviest successful snatch and clean and jerk (CJ), and therefore Total (TOT). Official results were taken from the British Weightlifting website (accessed between 26 January 2019 and 20 April 2019). Competition performance was taken as absolute (absWLP), relative to weight category (catWLP), due to weight class changes in the period assessed. In preparation for the Olympics, prediction of performance zones was conducted using methods outlined by Chavda et al. [20]. Additional competition performance data for each opposition competitor within the 96 kg weight class was also extracted from the IWF website following the final entries publication, accessible 22 July 2021. This was overlaid onto the predicted performance zones, to help identify minimum loads required to achieve a top 10 finish and where each competitor may place.

2.3.5. Barbell Kinematics Data Capture

Peak barbell vertical velocity was collected using Enode (Blaumann & Meyer, Sports Technology UG, Magdeburg, Germany) interfaced with an iPad pro (2nd generation, Apple Inc., Cupertino, CA, USA). Previous research has demonstrated the Enode’s validity as well as it’s within and between session reliability [21]. Data capture occurred during the last training week of block 19, the first training week of block 20 and 21, the last week of block 21, and finally the start and end of block 22 during the taper. This was due to international travel coupled with the necessity of helping monitor adaptation without access to force plates, whilst additionally being less intrusive to the athlete’s preparations. A standard load of 140 kg was used as this was the heaviest, most commonly lifted load throughout the 4 training blocks. Given that displacement of the barbell remains relatively consistent within individuals during the snatch (~70% of height) [22], an increase in peak barbell vertical velocity (PBVv) at the given load (i.e., 140 kg) would suggest that the force applied has increased, inferring a positive training adaptation has taken place.

2.3.6. Training Program

The training program consisted of 22 blocks. Each block lasted between 2 and 9 weeks and had a specific focus centered around the general preparatory phase (GPP), sport-specific phase (SSP), and competitive phase (CP), which was designed, implemented, and adjusted by an international weightlifting coach with input from the athlete. Confirmation of team selection was not made until June 2021, approximately 1.5 months before the start of the Olympics; therefore, the 2.9-year training period was periodized for specific major competitions within this time frame. Loading across the 2.9-year period is depicted in Figure 1. Volume load was calculated as the total repetitions (volume) multiplied by the load lifted, expressed as tonnage. Intensity was expressed as a percentage of the athlete one-repetition maximum (1RM).

Table 1. Exercise classifications to define volume–load distributions.

Classification	Base Exercises	Specific Examples
Technical	Snatch *	Snatch from block at knee Power Snatch
	C&J *	Clean from block at knee Power Clean
Strength	Snatch/Clean Pull ¥	Snatch High Pull Deficit Snatch Pull Mid-Thigh Clean Pull
	Squat	Back Squat Front Squat
Accessory	Supplementary exercises outside of the above	Snatch grip Romanian deadlift Glute Hamstring Raise Back extensions Push Press Dips Chin ups

* Includes all derivatives of the classical competition lifts (i.e., hang, block, power variants). ^¥ Includes all positional derivatives of the classical competition lifts (i.e., hang, block, to/from position, deficit). All exercise complexes (i.e., Snatch Pull + Snatch) were classified as technical lifts.

identifies the exercise types in which the volume load has been distributed. Due to the constraints elicited by COVID-19 and abrupt changes in accessibility, the 2.9-year period has been segmented into 3-time frames, representing pre, during, and post-COVID-19. Supplement S2 outlines each block in detail.

2.4. Statistical Analysis

Often, sports science studies utilize conventional statistics based on the means of a sample population [23]. Whilst useful in providing the scientific community with generalizable findings in specific groups, it can often mask important information on individuals. Single-subject case studies therefore may be preferable, particularly in the case of analyzing elite individuals [24]. An inherent issue with case study designs within the elite population often means there is a lack of a controlled experimental design, given the dynamic nature of training, which may often interrupt phases of training and availability of monitoring [24]. Furthermore, the quasi-experimental nature of this study highlights the barriers that may be experienced, which are out of the control of the scientist or coach.

Given the issues highlighted above, the application of traditional methods of statistical analyses means assumptions of the data will be violated, if at all available in the first instance. Therefore, the methods of analysis employed to determine meaningful changes in all performance measures (neuromuscular and technical) were made by adopting methods outlined by Sands et al. [24] and more recently Turner [25]. While traditional statistical assumptions may not hold in this context, the analytical approach utilized in the present study is intentionally designed for high-performance sport, where n = 1 scenario is necessary. The objective here is not to generalize to a population, but to detect small yet meaningful changes within this individual’s performance. We employ 1SD intervals as a pragmatic balance, sufficiently wide enough to account for measurement error (~68%), yet narrow enough to retain sensitivity to true performance changes. This approach reflects a deliberate emphasis on minimizing Type II errors, which is critical in applied sport science where overlooking a genuine improvement may have significant performance implications.

All neuromuscular performance data and training technical data are presented as means ± 1SD. Inference as to whether meaningful change had occurred outside of the variability of the test required the lower limit SD to be greater than that of the previous time points’ upper limit SD. This is depicted visually, accompanied by percentage change, a value commonly used to help contextualize changes when reporting back to athletes. Peak vertical velocity derived from the snatch was also assessed using the mean ± 1SD. Performance predictions for the Olympics were calculated utilizing methods outlined by Chavda et al. [20], specifically

−0.023x² + 6.293x + −15.190

This was used in conjunction with the sum of the best snatch and CJ achieved from historic performance ± 1SD from each competitor within the 96 kg weight category, plotted with predicted zones (Figure 2). In addition to this, a competitor “cheat sheet” was also developed, allowing identification of opportunities to best position the athlete to obtain the highest rank possible with a realistic idea of whether the target of a top 10 rank could be achieved (Supplement S1).

3. Results

3.1. Changes in Training Load

Mean training volume load pre-COVID-19 was 1.98 ± 0.38 tons, which increased by 13% to 2.25 ± 0.43 tons during COVID-19. This was elicited from an increase in average volume, which went from 12 ± 4 repetitions to 14 ± 7 repetitions, accompanied by a concurrent decrease in average intensity reducing from 81 ± 6% to 75 ± 6%. Between COVID-19 and post-COVID-19, volume load saw a significant decrease dropping from 2.25 ± 0.43 to 1.19 0.24 tons. A primary reason for this was the increase in average intensity, which rose from 75 ± 6% to 84 ± 4%, and the reduction in average volume (14 ± 7 vs. 8 ± 1 repetitions). The greatest variability in training load is evident during COVID-19 where training accessibility was limited due to both facility and lockdown restrictions, and key worker commitments.

3.2. Neuromuscular Performance Changes

Due to national lockdowns, neuromuscular performance testing was only conducted during the first three competitions in 2019, pre-COVID-19. Figure 3 depicts changes in CMJ JH, propIMP, countermovement depth, and propulsion time. Figure 4 depicts the changes in IMTP performance for NPF, relNPF, and F150 and F200. The most significant change occurred between English Championship 2019 (EC19) and British Universities Championship 2019 (BU19), where net propulsive impulse had increased by 12.1%, consequently increasing JH. Mechanistically, the time taken during the propulsion phase did not change; however, the depth of the countermovement increased by 17.1%, suggesting an improvement in the athlete’s ballistic force expression. This increase in propulsive force expression was supported by a significant increase of 5.6% in NPF during the IMTP. Both F150 and F200 decreased between EC19 and BU19, but significantly improved between BU19 and British International Open (BIO19) by 14% (F150) and 12.4% (F200). This was accompanied by an increase in NPF (4.1%) and relNPF (4.7%).

3.3. Competition Performance Changes

Competition performances are depicted in Figure 5. Changes in the absolute performance total leading into the Olympics was 0.43 ± 3.20%, with the biggest decrement occurring during the English Championships 2021 (EC21) (−4.71%) which took place virtually during national lockdown. The biggest increase in performance was between EC19 and BU19 for an increase of 5.56%, with a concurrent increase in body weight category from 96 to 102 kg. In his Olympic category of 96 kg, the athlete’s biggest increase in performance was between EC21 and British Championships 2021 (BC21) for an increase of 2.86%. When total performance was made relative to weight category (kg/kg), his best performances were at the BC21 and Olympic Games (OG), achieving 3.65, where he achieved his highest snatch (160 kg) and CJ (195 kg) as a 96 kg, respectively. During this 2.9-year period, the athlete had broken multiple national records over two weight categories. Internationally, the athletes’ personal target of a top 10 finish at the Olympics was also achieved, due to the disqualification of two athletes and the 5.89% lower than predicted performances.

3.4. Barbell Kinematic Changes

Changes in PBVv are depicted in Figure 6. The start of block 21 had a meaningful increase in PBVv relative to block 20, with PBVv also showing a meaningful increase toward the end of the taper in block 22, 7 days out from competition.

4. Discussion

This case study aimed to examine time–course changes in weightlifting performance in relation to neuromuscular ability and barbell kinematics in an elite Olympic refugee athlete. To the authors’ knowledge, this is the first longitudinal, holistic investigation of its kind. During 2019, performance improvement coincided with increases in force capacity and expression, as measured by CMJ and IMTP assessments (Figure 3, Figure 4 and Figure 5). However, the onset of the COVID-19 introduced unavoidable disruptions to training frequency, monitoring, and equipment availability, fundamentally limiting monitoring consistency. These factors necessitated a quasi-experimental approach, in which data were collected under evolving, real-world constraints rather than tightly controlled conditions. As a result, training intensity decreased and volume became more varied (Figure 1), contributing to a reduction in performance.

Post-COVID-19, training access improved, allowing for an increase in intensity across blocks 17–22. This shift, combined with strategic tapering and reduced training volume, resulted in improved PBVv, especially during block 22, a week prior to the Olympic competition. Despite lifting below the predicted benchmark total of 376 kg required for a top 10 Olympic finish, the athlete achieved the desired target of 10th, aided in part by reduced international performances due to pandemic-related disruptions and two disqualifications (Figure 2). While findings reflect authentic training responses in elite sport, they must be interpreted with an understanding of the environmental constraints that shaped them. The following discussion explores these findings in relation to training manipulation and adaptation based on three distinct periods of time; pre-, intra-, and post-COVID-19.

4.1. Pre-COVID-19

Prior to the pandemic, the athlete competed in three events. Following the BU19 competition in block 3, marked improvements in neuromuscular force capacity and expression were observed, reflected in increased NPF and propIMP as illustrated in Figure 3 and Figure 4, respectively. These adaptations aligned with personal bests of 160 kg in the snatch and 200 kg in the jerk. A likely contributor was the training structure in blocks 2 and 3, emphasizing pulls, squats, and accessories, accounting for 29%, 13%, and 32% of block 2, and 39%, 12%, and 27% of block 3 (Supplement S2). Interestingly, the athlete’s increase in propIMP was accompanied by a greater countermovement depth, but without a corresponding change in time during the propulsive phase. This suggests that force expression improved due to increased force output rather than temporal factors. Notably, despite gaining body mass while transitioning from the 96 kg to 102 kg weight class, relNPF remained stable, indicating a proportional increase in both weight and force capacity. Unfortunately, due to the lack of accessibility, the absence of body composition measurements, such as fat mass, lean mass, and visceral fat. Without these data, it is difficult to determine whether changes in weight or other physical outcomes were due to changes in fat or muscle mass. It is important to note that the present data reports net values, excluding contributions from body weight and pretension, whereas values in the literature typically reflect absolute force values. When accounting for estimated body weight and pretension (~950–1100 N), the athlete’s adjusted absolute PF values (~5050–5600 N) fall within or slightly above the ranges reported by Joffe et al. [26] (3324 ± 664 N) and Ben-Zeev et al. [27] (4318 ± 767 N), but remain below the highest values observed in elite athletes by Beckham et al. [28] (7115 N). However, in all cases, the athlete of the present study had considerably higher performance totals than that presented in the literature, suggesting factors beyond maximal force contributing to greater weightlifting performance, such as technique and force expression.

At the BIO19 competition, the athlete achieved a 1 kg snatch increase (161 kg) and cleaned 205 kg but failed the jerk, resulting in a no lift. Improvements in clean performance may be linked to observed increases in NPF, relNPF, and F150 and F200. However, CMJ performance remained unchanged, despite higher relNPF, suggesting possible independence between some isometric and dynamic performance metrics. Collectively, the data suggests the following: (1) increases in NPF were associated with improved snatch and clean performance, and (2) F150 and F200 may not be consistently predictive of performance outcomes.

During BIO19, the athlete reported acute wrist and elbow pain, prompting a three-week pause before beginning block 5. This injury incident highlights the “high-risk, high-reward” nature of elite-level weightlifting. Epidemiological data from Doerr [29] indicate that 45–54 athletes were injured in major competitions between 2007 and 2012, with the elbow being among the most commonly affected sites. While the exact injury types are often unspecified, acute dislocations and tendon ruptures, typically resulting from technical breakdowns or loss of control under maximal loads, are common [30,31]. To facilitate recovery, block 5 emphasized low-intensity, high-volume training, primarily through accessories (81%) and pulls (19%), to maintain adaptation while minimizing upper-limb loading. This approach aligns with recommendations from Suchomel, Comfort, and Stone [32], who advocate for pull-only derivatives to support technical retention and reduce joint impact [33].

Block 6 concluded with a low-priority national competition (English Grand Prix 2021, EGP). A shift toward heavier lifting resumed, marked by decreased training volume and increased intensity. In spite of this, performance declined from 356 kg to 340 kg, primarily due to a drop in the clean and jerk (from 195 kg to 185 kg), coinciding with the athlete’s body weight reduction below 96 kg. Shortly after the EGP21, a 10-week hiatus followed due to increased professional workload within the NHS and a subsequent COVID-19 infection. During this time, structured training and monitoring ceased entirely. These events underscore the real-world complexity of performance sport. Additionally, injury, illness, and dual-career responsibilities often disrupt training consistency, limit data collection, and restrict experimental control, conditions symbolic of a quasi-experimental design.

4.2. COVID-19

On 24 March 2020, the Tokyo Olympic Games were officially postponed, shifting the athlete’s focus toward general physical preparation (GPP). However, the COVID-19 pandemic imposed constraints on training access and coaching contact. With closures of training facilities, the athletes were restricted to training outdoors based on weather conditions. Due to public health restrictions, no face-to-face coaching was possible, limiting immediate technical feedback and adjustments critical for weightlifting performance. Consequently, training volume was deliberately increased, governed by the weights available, but also to preserve some level of strength and robustness, while intensity was reduced, as shown in Figure 1.

Musa et al. [34] emphasize that many elite athletes during the pandemic faced drastic reductions in training volume, limited access to facilities and equipment, and overall declines in physical fitness, further challenging their ability to maintain sport-specific adaptations. The lack of structured load progression, combined with the absence of controlled, high-intensity neuromuscular stimuli, likely contributed to performance stagnation during this period. Critically, the inability to conduct regular neuromuscular monitoring assessments during confinement meant that force production and neuromuscular readiness could not be objectively quantified, compounding the difficulty in managing training load and progression remotely.

Upon receiving elite athlete exemption in block 15, the athlete resumed full-time training and participated in an online benchmark competition. Training intensity was markedly increased with concurrent reductions in volume; however, total performance remained unchanged at 340 kg. The persistent lack of exposure to higher intensity training during the preceding confinement period likely limited neuromuscular adaptations necessary for strength gains, consistent with the detraining effects elicited by COVID-19, as outlined by Sarto et al. [35]. Additionally, the absence of objective force monitoring tools during this phase prevented accurate assessment of capacity. This gap in data hindered evidence-based decision-making regarding program focus. These limitations highlight the inherent challenges of quasi-experimental research, where external factors such as restricted training environments and health emergencies significantly confound controlled intervention. Furthermore, given the elevated injury risk associated with rapid reintroduction of intense loading after periods of detraining [35], cautious programming was essential to optimize athlete safety and performance during transitions back to full training.

4.3. Post-COVID-19

Once COVID-19 restrictions were lifted in March 2021, the athlete resumed a more typical training regime with a clear focus on peaking for the Olympic Games. Despite this, accessibility to lab-based neuromuscular testing remained restricted. The Olympic team was announced on 8th June 2021, during block 20, approximately two months prior to competition. In preparation, blocks 17 to 19 emphasized progressive increases in training intensity for the competition lifts, with an online national championship held approximately three weeks before the Olympics (BC21). This event served as a critical performance benchmark, with target lifts of 160 kg in the snatch and 190 kg in the clean and jerk. From blocks 19 to 22, barbell kinematics were monitored using an Enode sensor during key sessions, providing valuable insights despite the absence of more sophisticated laboratory assessments. Recent longitudinal case study research by Sandau and Granacher [14] documented force–velocity relationships and theoretical snatch one-repetition maximum (1RM) changes over 40 weeks in elite weightlifters preparing for major international competitions. They observed a decline in theoretical velocity (${\stackrel{-}{\mathrm{v}}}_0$) concurrent with increases in theoretical maximal force (${\stackrel{-}{\mathrm{F}}}_0$) and power (${\stackrel{-}{\mathrm{P}}}_0$) following peak performance periods. Although this study did not conduct force–velocity profile analysis, it employed established velocity-based monitoring concepts to assess neuromuscular adaptation and preparedness. Specifically, PBVv at a fixed load (e.g., 140 kg) was tracked during the lead up to the Olympics. Given the consistency of barbell displacement during the snatch (~70% of body height) within individuals [22], variations in PBVv can serve as indirect indicators of changes in neuromuscular force production, aligning with velocity-based strength training literature that associates increased movement velocity at constant loads with enhanced neuromuscular function [36].

The mesocycles during this preparatory phase predominantly featured medium to high training loads with relatively low volume, reflecting a focus on optimizing maximal strength and power in the competition lifts, consistent with loading paradigms described by Sandau and Granacher [14]. To maximize performance gains while mitigating overtraining risk, an effective taper strategy is essential to dissipate accumulated fatigue and induce supercompensation. Winwood et al. [37], through a survey of 144 competitive weightlifters (including 34 internationals), identified typical tapering durations averaging 8 ± 4.4 days, with a preference for linear tapers and average volume reductions of 41.3 ± 14.6%. These values align closely with findings from a meta-analysis by Bosquet et al. [38], which reported volume reductions of 41–60%. The taper’s fundamental purpose is to enhance performance by facilitating recovery from accumulated training stress. In this case study, both the British International Open (BIO19) and Olympic Games (OG) saw training volume reductions of 57% and 53%, respectively. Peak loads (~95% intensity) were generally attempted six days before competition, consistent with Winwood et al.’s findings where the last heavy session occurred approximately 5.3 ± 2.3 days pre-competition. The taper’s efficacy is supported by a 4% increase in PBVv from the start to the end of the taper (1.87 ± 0.01 m·s⁻¹ to 1.94 ± 0.01 m·s⁻¹; Figure 6), suggesting successful supercompensation.

This case study highlights the critical need for adaptability in supporting elite athletes, particularly when objective monitoring tools are restricted. Case studies inherently involve repeated observations under uncontrolled and retrospective conditions [39]. Here, pandemic-related constraints necessitated the adoption of alternative monitoring approaches to inform training decisions. Recognizing these limitations enables a constructive critique of current practices and guides improvements for future athlete monitoring. The present investigation primarily used isolated monitoring methods but nonetheless provides insight into training dose–response relationships over a macrocycle. Integrating neuromuscular assessments with barbell kinematics and gym-based maximal strength testing could yield a more comprehensive understanding of adaptation processes. As pre-COVID-19 practice indicated, implementing neuromuscular testing at specific mesocycle intervals may better verify intended physiological adaptations. Moreover, traditional prescription methods can be enhanced by velocity-based training (VBT) approaches, particularly for strength exercises such as squats, to regulate neuromuscular fatigue and optimize the distribution of volume and intensity across the training program. Finally, in preparation for competition, recent recommendations by Sandau, Chaabene, and Granacher [40] advocate using force–velocity profiling of the snatch high pull to estimate current 1RM snatch with good accuracy [40,41]. Coupled with predictive performance zones, this can refine opening lift selections in competition, increasing the likelihood of successful attempts.

While this case study provides valuable insights into the longitudinal preparation of an elite-level weightlifter, it is not without its limitations, which must be considered when interpreting the findings. Firstly, the study design is quasi-experimental, and as such, it does not allow for the same level of control and randomization as a true experimental design. This limits the ability to draw causal inferences regarding the effectiveness of specific training interventions or the precise mechanisms driving the observed performance changes. Instead, the findings should be interpreted as primarily descriptive, providing important insights but without the statistical rigor required to infer direct cause-and-effect relationships. Secondly, the global pandemic introduced significant disruptions to training and monitoring schedules, affecting the frequency and regularity of data collection. As a result, the athlete’s training was inconsistent during certain periods, and the limitations in monitoring frequency may have impacted the completeness of the data. In particular, disruptions to training, competitions, and access to performance monitoring tools may have hindered the ability to capture all relevant data points that may have provided a richer set of results. While the methods employed in this study were adapted to these circumstances, the irregularity of data collection poses a limitation to the study’s overall statistical rigor.

Finally, the athlete in question was also a dual-career athlete and key worker during the pandemic. This introduces an additional layer of complexity in terms of time availability and training consistency. Balancing both high-level sports performance and professional commitments likely impacted the intensity and frequency of training, which may have confounded some of the observed neuromuscular and performance outcomes. The transparency of these limitations provides the readership with an insight into how a practitioner must adapt to circumstantial changes in environment and accessibility. While in this instance it was the pandemic that governed these circumstances, loss of funding and changes in accessibility to training and equipment could also be factors that practitioners must overcome.

Despite these limitations, this case study provides valuable preliminary insights into the preparation of an elite-level athlete under unique circumstances, and it underscores the need for further research with more controlled designs and more frequent, consistent monitoring. Future studies should aim to implement longitudinal, randomized controlled designs and to employ inferential statistics to enhance the rigor of data analysis. Additionally, much like the present study, surrogate measures of performance such as ballistic and isometric tasks offer little specificity for weightlifting-specific programming and provide, at the very best, general information on force producing capabilities. To supplement this and to provide potentially more specific methods of training specificity based on the limiting phase of the lift, protocols from Sandau and Granacher [42] may be of use. The authors suggest that identifying the phase of lift in which the lifter loses the most velocity as the load increases may help to better direct training specificity. This, in conjunction with positional isometric tests from the knee or set position, may also help better identify potential relationships between velocity changes at the end of each phase, relative to the force expressed at that specific position. These alternative positional isometrics have been utilized in previous weightlifting research, which identified strong relationships with weightlifting performance [26,27,43]. Collectively, this may allow the coach to distribute greater training volume to enhance the specific limiting phase to see its influence on vertical velocity loss, phase-specific force expression, and lift performance increases.

5. Conclusions

This case study provides insight into the preparation of an elite weightlifter for the Olympic Games and the potential neuromuscular adaptations that occur due to training distribution and its effects on performance. Primary findings from this case study highlight the utility of individual athlete analysis and how to pragmatically interpret information to understand how training and enhancing specific biomotors may influence weightlifting performance. Another practical application drawn from this study is the necessity for adaptability within the training process while aiming to maintain and/or optimize physical and technical capabilities. While prior research suggests that weightlifting derivatives omitting the catch can be used for injured athletes, the present study showed that certain technical and physical attributes can be maintained through their use. Lastly, evidence supporting tapering methods and their positive influence on PBVv may be useful to weightlifting coaches preparing athletes for competition, where training volume reductions of 53–57%, while maintaining competition lift intensity at ~95% up to 6 days out, may help elicit performance improvements on the platform.