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BACKGROUND: The determination of critical power (CP) during training is a useful tool monitoring performance progression and to demarcate training intensity zones. The aims of this study were: 1) to compare CP with varied effort short, medium and long intervals (SML-INT) with a field CP test; 2) to assess if SML-INT is an effective way to improve CP.METHODS: Seven male cyclists completed a 4-week training period. Before and after the training period, an assessment of CP was conducted using a 2 and 3-parameter model. Furthermore, during the training period, mean maximal power (MMP) achieved during 30-s, 1-, 3- and 7-min intervals, were used to calculate CP.RESULTS: CP was increased by 5% after four weeks. A significant difference in CP and W' (the finite amount of work which can be performed above CP) in pre-test values and all power outputs analyzed (P

Purpose: This study evaluated the power profile of a top 5 result achieved in World Tour cycling races of varying types, namely: flat sprint finish, semi-mountain race with a sprint finish, semi-mountain race with uphill finish, and mountain races (MT). Methods: Power output data from 33 professional cyclists were collected between 2012 and 2019. This large data set was filtered so that it only included top 5 finishes in World Tour races (18 participants and 177 races). Each of these top 5 finishes were subsequently classified as flat sprint finish, semi-mountain race with uphill finish, semi-mountain race with a sprint finish, and MT based on set criteria. Maximal mean power output (MMP) for a wide range of durations (5 s to 60 min), expressed in both absolute (in Watts) and relative terms (in Watts per kilogram), were assessed for each race type. Result: Short-duration power outputs (10 minutes seem to be a key determining factor for success in MT. These race-type specific MMPs of importance (ie, short-duration MMPs for sprint finishes, longer-duration MMPs for races with more elevation gain) are performed at a wide range (80%–97%) of the cyclist’s personal best MMP. Conclusions: This study shows that the relative importance of certain points on the power–duration spectrum varies with different race types and provides insight into benchmarks for achieving a result in a World Tour cycling race.

A methodology to study bike handling of cyclists during individual time trials (ITT) is presented. Lateral and longitudinal accelerations were estimated from GPS data of professional cyclists (n = 53) racing in two ITT of different length and technical content. Acceleration points were plotted on a plot (g-g diagram) and they were enclosed in an ellipse. A correlation analysis was conducted between the area of the ellipse and the final ITT ranking. It was hypothesised that a larger area was associated with a better performance. An analytical model for the bike-cyclist system dynamics was used to conduct a parametric analysis on the influence of riding position on the shape of the g-g diagram. A moderate (n = 27, r = -0.40, p = 0.038) and a very large (n = 26, r = -0.83, p < 0.0001) association were found between the area of the enclosing ellipse and the final ranking in the two ITT. Interestingly, this association was larger in the shorter race with higher technical content. The analytical model suggested that maximal decelerations are highly influenced by the cycling position, road slope and speed. This investigation, for the first time, explores a novel methodology that can provide insights into bike handling, a large unexplored area of cycling performance.

Introduction This study aimed to investigate if performance measures are related to success in professional cycling and to highlight the influence of prior work done on these performance measures and success. Methods Power output data from 26 professional cyclists, in a total of 85 seasons, collected between 2012 and 2019, were analyzed. The cyclists were classified as "climber" or "sprinter" and into category 1 (CAT.1; >= 400 PCSpoints (successful)) and CAT.2 (

To optimize use of available resources, professional academies develop strategies to assess, monitor, and evaluate players as they progress through adolescence toward adulthood. However, few published reports exist using longitudinal study designs to examine performance throughout adolescence and the transition from youth to professional soccer. We examined differences in the age of player recruitment alongside longitudinal performance differences on field-based fitness tests of successful vs. unsuccessful graduates across the entire age spectrum recruited by a professional soccer academy. Altogether, 537 youth soccer players volunteered to participate. We recorded the age of recruitment, biannual fitness test performance, and subsequent success in attaining a senior professional contract at the club across a period of 12 years. Only 53 (10%) of players were successful in obtaining a professional contract, with 68% of players who became professional being recruited at 12 years of age or older. Individuals recruited at an earlier age did not display a higher probability of success in attaining a professional contract. Bayesian regression models reported a consistent interaction between age and group for data on all performance measures. Moreover, "successful" academy graduates only physically outperformed their "unsuccessful" counterparts from age similar to 13-14 years onward, with either no differences in performance, or performance on physical fitness tests favoring "unsuccessful" players prior to this age. Findings suggest that high achievers during childhood and early adolescence may not develop into successful senior professionals, raising concerns about the predictive utility of talent identification models.

Purpose: This case study aims to describe the multidisciplinary preparation of a multiple medal-winning Paralympic cyclist active in the C5 class. Specifically, it describes the 12-month preparation period toward the Tokyo 2020 Paralympic Games. Method: The participant (height 173 cm; weight approximately 63 kg) is active in the C5 para-cycling class (right arm impairment) and was preparing for the individual pursuit, road time trial, and mass-start race in the Tokyo Paralympic Games. The participant was supported by a multidisciplinary practitioner team focusing on multiple facets of athletic preparation. Morning resting heart rate (HR) and HR variability, as well as daily training data, were collected during the 12 months prior to Tokyo. Weekly and monthly trends in training, performance, and morning measures were analyzed. Training intensity zones were divided into zone 1 (lactate threshold, critical power). Results: The participant won a silver (individual pursuit) and a bronze (time trial) medal at the Paralympic Games. Annual sums of volume and total work (in kilojoules) were, respectively, 1039 hours and 620,715 kJ. Analyzing all road sessions, 85% was spent in zone 1, 9% in zone 2, and 6% in zone 3. Physiological (eg, high training loads, hypoxic stimuli) and psychological stressors (ie, significant life events) were clearly reflected in morning HR and HR-variability responses. Conclusions: This case study demonstrates how a multidisciplinary team of specialist practitioners successfully prepared an elite Paralympic cyclist utilizing a holistic approach to training and health using data to manage allostatic load.

The aim of this study was to evaluate a field-based approach to determine torque-cadence and power-cadence profiles in professional cyclists and establish if this field-based protocol can differentiate between varying rider specialisations. Twenty-four male professional athletes from a World Tour cycling team participated in this investigation (Height = 1.84 +/- 0.05 m, Weight = 72.3 +/- 5.6 kg, Age = 25 +/- 4 y). All riders were subsequently categorised into the following groups: 1) General Classification (GC) group; 2) sprinter group; and 3) classics group. All participants completed a specific sprint protocol in the field which included 6 times 6s sprints with varying gearing, starting cadences, starting speeds and position (i.e. seated vs standing). Power-cadence and torque-cadence profiles were determined based on the sprint outputs. There was a significant main effect of rider specialisation on the measured (sprint) variables (P

Background: A variety of intensity, load, and performance measures (eg, “power profile”) have been used to characterize the demands of professional cycling races with differing stage types. An increased understanding of the characteristics of these races could provide valuable insight for practitioners toward the design of training strategies to optimally prepare for these demands. However, current reviews within this area are outdated and do not include a recent influx of new articles describing the demands of professional cycling races. Purpose: To provide an updated overview of the intensity and load demands and power profile of professional cycling races. Typically adopted measures are introduced and their results summarized. Conclusion: There is a clear trend in the research that stage type significantly influences the intensity, load, and power profile of races with more elevation gain typically resulting in a higher intensity and load and longer-duration power outputs (ie, >10 min). Flat and semimountainous stages are characterized by higher maximal mean power outputs over shorter durations (ie

Sanders, D, Taylor, RJ, Myers, T, and Akubat, I. A field-based cycling test to assess predictors of endurance performance and establishing training zones. J Strength Cond Res 34(12): 3482-3488, 2020-This study evaluates the relationship between a field-based 8-minute time trial (8MTT) and physiological endurance variables assessed with an incremental laboratory test. Second, lactate thresholds assessed in the laboratory were compared with estimated functional threshold power (FTP) from the 8MTT. Nineteen well-trained road cyclists (aged 22 ± 2 years, height 185.9 ± 4.5 cm, body mass 72.8 ± 4.6 kg, V[Combining Dot Above]O2max 64 ± 4 ml·min·kg) participated. Linear regression revealed that mean 8MTT power output (PO) was strongly to very strongly related to PO at 4 mmol·L, PO at initial rise of 1.00 mmol·L, PO at Dmax and modified (mDmax) (r = 0.61-0.82). Mean 8MTT PO was largely to very largely different compared with PO at fixed blood lactate concentration of 2 mmol·L (ES = 3.20) and 4 mmol·L (ES = 1.90), PO at initial rise 1.00 mmol·L (ES = 2.33), PO at Dmax (ES = 3.47) and mDmax (ES = 1.79) but only trivially different from maximal PO (Wmax) (ES = 0.09). The 8MTT based estimated FTP was moderate to very largely different compared with PO at initial rise of 1 mmol·L (ES = 1.37), PO at Dmax (ES = 2.42), PO at mDmax (ES = 0.77) and PO at 4 mmol·L (ES = 0.83). Therefore, even though the 8MTT can be valuable as a performance test in cycling shown through its relationships with predictors of endurance performance, coaches should be cautious when using FTP and PO at laboratory-based thresholds interchangeably to inform training prescription.

This study analyses the influence of race category and result on the demands of professional cycling races. In total, 2920 race files were collected from 20 male professional cyclists, within a variety of race categories: Single-day (1.WT) and multi-day (2.WT) World Tour races, single-day (1.HC) and multi-day (2.HC) Hors Catégorie races and single-day (1.1) and multi-day (2.1) category 1 races. Additionally, the five cycling “monuments” were analysed separately. Maximal mean power outputs (MMP) were measured across a broad range of durations. Volume and load were large to very largely (d = 1.30–4.80) higher in monuments compared to other single-day race categories. Trivial to small differences were observed for most intensity measures between different single-day race categories, with only RPE and sRPE·km−1 being moderately (d = 0.70–1.50) higher in the monuments. Distance and duration were small to moderately (d = 0.20–0.80) higher in 2.WT races compared to 2.HC and 2.1 multi-day race categories with only small differences in terms of load and intensity. Generally, higher ranked races (i.e. Monuments, 2.WT and GT) tend to present with lower shorter-duration MMPs (e.g. 5–120 sec) compared to races of “lower rank” (with less differences and/or mixed results being present over longer durations), potentially caused by a “blunting” effect of the higher race duration and load of higher ranked races on short duration MMPs. MMP were small to largely higher over shorter durations (

Taylor, RJ, Sanders, D, Myers, T, and Akubat, I. Reliability and validity of integrated external and internal load ratios as measures of fitness in academy rugby union players. J Strength Cond Res 34(6): 1723-1730, 2020-This study aimed to assess the relationships between integrated ratios of external and internal load measures and aerobic fitness in 3 different training exercise protocols. Twelve academy rugby union players (aged; 17.6 ± 0.44 years, height; 179.4 ± 6.3 cm, body mass 83.3 ± 9.7 kg) performed a lactate threshold/V[Combining Dot Above]O2max test (LT/V[Combining Dot Above]O2max) followed by 3 exercise protocols; 760 m continuous shuttle running (20 m shuttle run at 9 km·h), sprint interval training (SIT: 6 × 6 seconds sprint with 54 seconds recovery), and a small-sided game (SSG: 6 vs. 6, 10 minutes on a 39 × 51 m pitch) on 2 occasions. A LT/V[Combining Dot Above]O2max test was used to determine velocity at lactate threshold (vLT) and at the onset of blood lactate accumulation (vOBLA), maximal oxygen uptake (V[Combining Dot Above]O2max) and the heart rate-blood lactate profile for the calculation of internal load (individualized training impulse or iTRIMP). The total distance (TD), PlayerLoad, metabolic power (MP), high-speed distance >15 km·h (HSD), very high-speed distance >18 km·h (VHSD) and individualized high-speed distance based on each player's vOBLA (iHSD) for the 3 exercise protocols were measured using Micro Electro Mechanical Systems/Global Positioning System technology. Bayesian analysis was used to assess the ratios validity and reliability. Ratios demonstrated large-to-very large associations with vOBLA (Rho = 0.64-0.76), vLT (Rho = 0.63-0.71). Reliability of the ratios ranged from 7.06 to 36.28% (coefficient of variation [CV]%). The results suggest that integrated load ratios from the SIT and SSG protocols provide a measure which is reliable with large-to-very large associations to submaximal aerobic fitness in rugby union.

Purpose: To describe the training intensity and load characteristics of professional cyclists using a 4-year retrospective analysis. Particularly, this study aimed to describe the differences in training characteristics between men and women professional cyclists. Method: For 4 consecutive years, training data were collected from 20 male and 10 female professional cyclists. From those training sessions, heart rate, rating of perceived exertion, and power output (PO) were analyzed. Training intensity distribution as time spent in different heart rate and PO zones was quantified. Training load was calculated using different metrics such as Training Stress Score, training impulse, and session rating of perceived exertion. Standardized effect size is reported as Cohen’s d. Results: Small to large higher values were observed for distance, duration, kilojoules spent, and (relative) mean PO in men’s training (d = 0.44–1.98). Furthermore, men spent more time in low-intensity zones (ie, zones 1 and 2) compared with women. Trivial differences in training load (ie, Training Stress Score and training impulse) were observed between men’s and women’s training (d = 0.07–0.12). However, load values expressed per kilometer were moderately (d = 0.67–0.76) higher in women compared with men’s training. Conclusions: Substantial differences in training characteristics exist between male and female professional cyclists. Particularly, it seems that female professional cyclists compensate their lower training volume, with a higher training intensity, in comparison with male professional cyclists.

Walsh, JA, Sanders, D, Hamilton, DL, and Walshe, I. Sleep profiles of elite swimmers during different training phases. J Strength Cond Res 33(3): 811-818, 2019-This study aims to describe the sleeping patterns during different training phases in competitive swimmers. Twelve national- and international-level swimmers (3 females and 9 males) were monitored during 4 different phases, consisting of a preparation training phase, a taper phase, a competition phase, and a rest phase. Sleep parameters were assessed using wrist activity monitors and self-reported sleep diaries. There was a moderately higher (d = 0.70-1.00) sleep onset latency during the competition phase compared with taper, train, and rest phases. Trivial to small differences were observed for total sleep time between phases (d = 0.05-0.40). Sleep efficiency was moderately higher (d = 0.60-0.75) in the training and taper phases compared with competition and rest. Restfulness and fragmentation index (FI) were lowest in the rest with differences between phases being small (d = 0.43-0.51) for restfulness and small to moderate (d = 0.43-0.62) for FI. Time in and out of bed was very largely later (d = 1.96-2.34) in rest compared with the other phases. Total nap time was moderately lower in rest (d = 1.13-1.18) compared with the training and competition phases, whereas there was a small difference (d = 0.46) compared with taper. To conclude, while there were trivial to small differences in sleep quantity between phases, there are small to moderate differences in other sleep parameters. Specifically, sleep onset latency was higher during the competition phase. In addition, this study highlights the substantial between-individual variations in sleep responses during different training phases.

The aim of this study was to determine the influence of body weight or lean body mass-based load on Wingate Anaerobic Test performance in male and female endurance trained individuals. Thirty-one participants (22 male cyclists and triathletes and 9 female triathletes) completed two randomized Wingate Anaerobic Test (body weight and lean body mass loads) in stationary start. There were no significant differences in power outputs variables between loads in any group. However, when comparing specific groups within the sample (e. g. cyclists vs cyclists) medium to large effect sizes were observed for Relative Mean Power Output (ES=0.53), Relative Lowest Power (ES=0.99) and Relative Power Muscle Mass (ES=0.54). Regarding gender differences, male cyclists and triathletes displayed higher relative and absolute power outputs (p

Considering the vast physical and neural developments experienced throughout adolescence, the reliability of physical performance may vary in youth populations. This study aimed to examine the reliability of change of direction (COD) and agility tests in youth soccer players. Altogether, 86 youth soccer players, aged 13.6 &plusmn, 2.0 years, volunteered to participate. Data were collected from a modified 505 COD test (m505COD) and the Y-sprint drill in both pre-planned (Y-SprintPRE) and reactive (Y-SprintREACT) conditions during 2 sessions, 7 days apart. Anthropometric data including body mass, standing stature, and sitting height were also collected. COD and agility tests demonstrated good reliability (ICC = 0.81&ndash, 0.91, CV = 1.2&ndash, 2.0, d = 0.00&ndash, 0.31, p &lt, 0.01) for our entire sample. However, we observed a small negative relationship between age and intersession differences for the Y-SprintPRE (r = &minus, 0.28, p = 0.04), and moderate negative relationships between both age (r = &minus, 0.41, 0.01), and maturity offset (r = &minus, 0.39, 0.01) for the Y-SprintREACT. Although the COD and agility tests adopted within this study possess good intersession reliability, we observed greater intersession differences for younger and less mature individuals. We suggest that while COD and agility tests may provide meaningful objective data for monitoring the development of youth soccer players, these tests should be used with caution when evaluating younger, more immature athletes.

This study aims to describe the intensity and load demands of different stage types within a cycling Grand Tour. Nine professional cyclists, whom are all part of the same World-Tour professional cycling team, participated in this investigation. Competition data were collected during the 2016 Giro d'Italia. Stages within the Grand Tour were classified into four categories: flat stages (FLAT), semi-mountainous stages (SMT), mountain stages (MT) and individual time trials (TT). Exercise intensity, measured with different heart rate and power output based variables, was highest in the TT compared to other stage types. During TT's the main proportion of time was spent at the high-intensity zone, whilst the main proportion of time was spent at low intensity for the mass start stage types (FLAT, SMT, MT). Exercise load, quantified using Training Stress Score and Training Impulse, was highest in the mass start stage types with exercise load being highest in MT (329, 359 AU) followed by SMT (280, 311 AU) and FLAT (217, 298 AU). Substantial between-stage type differences were observed in maximal mean power outputs over different durations. FLAT and SMT were characterised by higher short-duration maximal power outputs (5-30 s for FLAT, 30 s-2 min for SMT) whilst TT and MT are characterised by high longer duration maximal power outputs (10 min). The results of this study contribute to the growing body of evidence on the physical demands of stage types within a cycling Grand Tour.

This study examined if short-duration record power outputs can be predicted with the Anaerobic Power Reserve (APR) model in professional cyclists using a field-based approach. Additionally, we evaluated if modified model parameters could improve predictive ability of the model. Twelve professional cyclists (V̇O

Multistage cycling races are very demanding and may profoundly affect the body’s fluid homeostasis. This study aimed at monitoring body fluid volume and plasma volume (PV) changes during multi-stage cycling and to investigate whether changes are associated to work output and perceived exertion during the competition. During the Tour of the Alps cycling stage race 2017 daily hematocrit and hemoglobin evaluations, body weight, bioimpedance, RPE and power output measurements were performed on eight professional road cyclists. Results show modest to large changes in bioimpedance and blood hematocrit values during the race. Work accomplished during stage one was related to changes in vector length and body weight (n = 6, r = 0.821, p = 0.045 and r = ‒0.852, p = 0.031, respectively). Additionally, PV changes were associated with vector length changes (r = ‒0.759, p = 0.029). During the last stage, PV changes were related to reactance (Xc/H) changes (r = ‒0.716, p = 0.046). The physical work performed du...

Purpose:The aim of this study was to identify the dose-response relationship between measures of training load (TL) and changes in aerobic fitness in academy rugby union players.Methods:Training data from ten academy rugby union players was collected during a six-week in-season period. Participants completed a lactate threshold (LT) test which was used to assess VO2max and velocities at VO2max, 2 mmol·L-1 (vLT) and 4 mmol·L-1 (vOBLA) as measures of aerobic fitness. Internal training load measures calculated were Banister’s TRIMP (bTRIMP), Edward’s TRIMP (eTRIMP), Lucia’s TRIMP (luTRIMP), individualised TRIMP (iTRIMP) and session-RPE (sRPE). External TL measures calculated were; total distance (TD), PlayerLoad™ (PL), high-speed distance >15 km·h-1 (HSD), very high-speed distance >18 km·h-1 (VHSD) and individualized high-speed distance based on each player’s vOBLA (iHSD).Results:A second order regression (quadratic) analysis identified that bTRIMP (R2 = 0.78, P = 0.005) explained 78% of the variance and iTR...

This study evaluated the changes in ratios of different intensity (rating of perceived exertion; RPE, heart rate; HR, power output; PO) and load measures (session-RPE; sRPE, individualized TRIMP; iTRIMP, Training Stress Score; TSS) in professional cyclists. RPE, PO and HR data was collected from twelve professional cyclists (VO2max 75 +/- 6ml.min.kg(-1)) during a two-week baseline training period and during two cycling Grand Tours. Subjective:objective intensity (RPE:HR, RPE:PO) and load (sRPE:iTRIMP, sRPE:TSS) ratios and external:internal intensity (PO:HR) and load (TSS:iTRIMP) ratios were calculated for every session. Moderate to large increases in the RPE:HR, RPE:PO and sRPE:TSS ratios (d=0.79-1.79) and small increases in the PO:HR and sRPE:iTRIMP ratio (d=0.21-0.41) were observed during Grand Tours compared to baseline training data. Differences in the TSS:iTRIMP ratio were trivial to small (d=0.03-0.27). Small to moderate week-to-week changes (d=0.21-0.63) in the PO:HR, RPE:PO, RPE:HR, TSS:iTRIMP, sRPE:iTRIMP and sRPE:TSS were observed during the Grand Tour. Concluding, this study shows the value of using ratios of intensity and load measures in monitoring cyclists. Increases in ratios could reflect progressive fatigue that is not readily detected by changes in solitary intensity/load measures.

Purpose:To assess the dose-response relationships between different training-load methods and aerobic fitness and performance in competitive road cyclists.Methods:Training data from 15 well-trained competitive cyclists were collected during a 10-wk (December–March) preseason training period. Before and after the training period, participants underwent a laboratory incremental exercise test with gas-exchange and lactate measures and a performance assessment using an 8-min time trial (8MT). Internal training load was calculated using Banister TRIMP, Edwards TRIMP, individualized TRIMP (iTRIMP), Lucia TRIMP (luTRIMP), and session rating of perceived exertion (sRPE). External load was measured using Training Stress Score (TSS).Results:Large to very large relationships (r = .54–.81) between training load and changes in submaximal fitness variables (power at 2 and 4 mmol/L) were observed for all training-load calculation methods. The strongest relationships with changes in aerobic fitness variables were observed for iTRIMP (r = .81 [95% CI .51–.93, r = .77 [95% CI .43–.92]) and TSS (r = .75 [95% CI .31–.93], r = .79 [95% CI .40–.94]). The strongest dose-response relationships with changes in the 8MT test were observed for iTRIMP (r = .63 [95% CI .17–.86]) and luTRIMP (r = .70 [95% CI .29–.89).Conclusions:Training-load quantification methods that integrate individual physiological characteristics have the strongest dose-response relationships, suggesting this to be an essential factor in the quantification of training load in cycling.

Purpose:To assess if short-duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model in professional cyclists.Methods:Data from 4 professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output, and an exponential constant describing the decrement in power over time, a power-duration relationship was established for each participant. To test the predictive accuracy of the model, several all-out field trials of different durations were performed by each cyclist. The power output achieved during the all-out trials was compared with the predicted power output by the APR model.Results:The power output predicted by the model showed very large to nearly perfect correlations to the actual power output obtained during the all-out trials for each cyclist (r = .88 ± .21, .92 ± .17, .95 ± .13, and .97 ± .09). Power output during the all-out trials remained within an average of 6.6% (53 W) of the predicted power output by the model.Conclusions:This preliminary pilot study presents 4 case studies on the applicability of the APR model in professional cyclists using a field-based approach. The decrement in all-out performance during high-intensity exercise seems to conform to a general relationship with a single exponential-decay model describing the decrement in power vs increasing duration. These results are in line with previous studies using the APR model to predict performance during brief all-out trials. Future research should evaluate the APR model with a larger sample size of elite cyclists.

Subjective and objective assessments may be used congruently when making decisions regarding player recruitment in soccer, yet there have been few attempts to examine the level of agreement between these methods. Therefore, we compare levels of agreement between subjective and objective assessments of physical qualities associated with youth soccer performance. In total, 80 male youth soccer players (13.2 ± 1.9 years), and 12 professional coaches volunteered to participate. Players were objectively assessed using five fitness measures: Yo-Yo Intermittent Recovery Test Level 1; Countermovement vertical jump; Functional Movement Screen™; 5/20 m sprint; alongside anthropometric measures. Additionally, coaches subjectively rated each player on the same five physical qualities using 5-point Likert scales. Inter-rater agreement between ratings from lead and assistant coaches was established for each age group. Moreover, Bayesian regression models were fitted to determine how well coach ratings were able to predict fitness test performance. Although inter-rater agreement between lead and assistant coaches was moderate-to-substantial (ω = 0.48-0.68), relationships between coaches subjective rating's and corresponding fitness test performance were only highly related for the highest and lowest performing players. We suggest that while ratings derived from objective and subjective assessment methods may be related when attempting to differentiate between distinct populations, concerns exist when evaluating homogeneous samples using these methods. Our data highlight the benefits of using both types of measures in the talent identification process.

This study aimed to establish between-day reliability and validity of commonly used field-based fitness tests in youth soccer players of varied age and playing standards, and to discriminate between players without (“unidentified”) or with (“identified”) a direct route to professional football through their existing club pathway. Three-hundred-and-seventy-three Scottish youth soccer players (U11–U17) from three different playing standards (amateur, development, performance) completed a battery of commonly used generic field-based fitness tests (grip dynamometry, standing broad jump, countermovement vertical jump, 505 (505COD) and T-Drill (T-Test) change of direction and 10/20 m sprint tests) on two separate occasions within 7–14 days. The majority of field-based fitness tests selected within this study proved to be reliable measures of physical performance (ICC = 0.83–0.97; p less than .01). However, COD tests showed weaker reliability in younger participants (ICC = 0.57–0.79; p less than .01). The field-based fitness testing battery significantly discriminated between the unidentified and identified players; χ2 (7) = 101.646, p less than .001, with 70.2% of players being correctly classified. We have shown field-based fitness tests to be reliable measures of physical performance in youth soccer players. However, results from the 505COD and T-Test change of direction tests may be more variable in younger players, potentially due to complex demands of these tests and the limited training age established by these players. While the testing battery selected in this study was able to discriminate between unidentified and identified players, findings were inconsistent when attempting to differentiate between individual playing standards within the “identified” player group (development vs. performance).

Purpose: To provide a retrospective analysis of a large competition database describing the intensity and load demands of professional road-cycling races, highlighting the differences between men’s and women’s races. Methods: In total, 20 male and 10 female professional cyclists participated in this study. During 4 consecutive years, heart rate, rating of perceived exertion, and power-output data were collected during both men’s (n = 3024) and women’s (n = 667) professional races. Intensity distribution in 5 heart-rate zones was quantified. Competition load was calculated using different metrics, including Training Stress Score (TSS), training impulse (TRIMP), and session rating of perceived exertion. Standardized effect size is reported as Cohen d. Results: Large to very large higher values (d = 1.36–2.86) were observed for distance, duration, total work (in kilojoules), and mean power output in men’s races. Time spent in high-intensity heart-rate zones (ie, zones 4 and 5) was largely higher in women’s races (d = 1.38–1.55) than in men’s races. Small higher loads were observed in men’s races quantified using TSS (d = 0.53) and TRIMP (d = 0.23). However, load metrics expressed per kilometer were large to very largely higher in women’s races for TSS·km –1 (d = 1.50) and TRIMP·km –1 (d = 2.31). Conclusions: Volume and absolute load are higher in men’s races, whereas intensity and time spent in high-intensity zones is higher in women’s races. Coaches and practitioners should consider these differences in demands in the preparation of professional road cyclists.