Correlation Study between Oxygen Consumption and Body Composition in Professional Soccer Players and Non-Athlete Populations with and without Anterior Cruciate Ligament Rupture

For elite professional soccer players and alpine skiers, injuries associated with anterior cruciate ligament (ACL) rupture, such as meniscal, cartilage, or collateral ligament lesions, could result in a delayed return to sport compared with isolated ACL injury. The purpose of the study was to provide a detailed description of associated injuries at the time of primary ACL reconstruction in elite soccer players and alpine skiers. It was hypothesized that soccer players and skiers would present different typical injury patterns due to different injury mechanisms. Cohort study; Level of evidence, 3. Surgical reports and arthroscopic images of elite professional soccer players and alpine skiers who underwent primary ACL reconstruction at a single institution between January 2010 and June 2022 were analyzed retrospectively. The presence and location of multiligamentous injury, meniscal tears, and chondral lesions were compared between the athlete groups. A propensity score matching analysis with 1:1 ratio was performed between skiers and soccer players to limit the effect of selection bias. Included were ACL reconstruction data representative of 37 soccer players and 44 alpine skiers. Meniscal pathology was found in 32 (86%) soccer players and 30 (68%) skiers. Chondral injuries were reported in 11 (30%) soccer players and 15 (34%) skiers. Results of the propensity score matching analysis in 15 pairs of soccer players and skiers indicated that soccer players had a significantly higher rate of medial meniscal injuries (73% vs 27%; P = .03) and lateral posterior root tears (33% vs 0%; P = .04) compared with skiers. A higher prevalence of combined chondral and meniscal injuries versus isolated ACL injuries was observed in both groups of athletes. Professional soccer players were characterized by higher prevalence of medial meniscal tears and lateral posterior root lesions compared with professional alpine skiers.

Background:Anterior cruciate ligament (ACL) rupture is one of the most common injuries afflicting soccer players and requires a lengthy recovery processes after reconstructive surgery. The impact of ACL reconstruction (ACLR) on return to play (RTP) time and player performance in professional soccer players remains poorly studied.Purpose/Hypothesis:To determine player performance and RTP rate and time after ACLR in elite professional soccer players with a retrospective matched-cohort analysis. We expected that the RTP time and rate will be similar to those of other professional-level athletes.Study Design:Cohort study; Level of evidence, 3.Methods:Included were 51 players from 1 of the 5 elite Union of European Football Associations (UEFA) soccer leagues who suffered a complete ACL rupture between 1999 and 2019. These athletes were matched by position, age, season of injury, seasons played, and height and compared to uninjured control players. Change in performance metrics for the 4 years after the season of injury were compared with metrics 1 season before injury. Univariate 2-group comparisons were performed using independent 2-group t tests; Wilcoxon rank-sum tests were used when normality of distributions was violated.Results:Overall, 41 players (80%) returned to play after ACL rupture, with 6 (12%) experiencing a subsequent ipsilateral or contralateral ACL tear. The mean (±SD) RTP time for soccer players after ACLR was 216 ± 109 days (26 ± 18 games). Injured athletes played significantly fewer games and minutes per season and recorded inferior performances for 2 seasons after their injury (P < .001). However, the game performance of injured players equaled or exceeded that of their matched controls by season 3 after injury, with the exception of attackers, who demonstrated a continued decline in performance (P < .001).Conclusion:Results indicated that the mean RTP time for soccer players after ACLR is short in comparison with other major sports leagues (216 days). However, RTP rates were high, and rerupture rates were comparable with those of other sports. With the exception of attackers, player performance largely equaled or exceeded that of matched controls by the third postinjury season.

The purpose of this investigation was to determine the physical and physiological characteristics of professional male soccer players. The ht/wt, body composition, flexibility, muscular strength, resting and exercise HR and BP, respiratory function (VE, vital capacity, and FEV1), max VO2 consumption, anaerobic threshold, and anaerobic power of seven field players and two goalkeepers were determined via appropriate testing protocols outlined in the literature. The following mean of physical characteristics were observed: age 28.2 years, height 174 cm, body weight 77.3 kg, body fat percentage 13.5, and flexibility (sit and reach) minus 3.88 inches. The mean of physiological characteristics were: maximal heartrate 177.7 bpm, maximum oxygen consumption 53.3 ml.kg.min, and maximal minute ventilation 84.5 L.minute. The following mean values were measured at anaerobic threshold level: HR = 156.4 bpm, VE = 50.4 L.min, oxygen consumption = 39.3 ml.kg.min, and anaerobic threshold occurred at 75% of maximum oxygen consumption. The difference between the physiological and physical characteristics of subjects of this study with other groups of soccer, basketball, and field hockey players were examined. The subjects were taller than Japanese National players and Aberdeen FC players, but shorter than the Dallas Tornado, Australian, and Czechoslovakian players. They had lower percent body fat than the South Australian field hockey players. The subjects' mean maximum oxygen consumption of 53.3 ml.kg.min was lower than mean maximum oxygen consumption of other professional soccer players, college basketball players, and field hockey players.

Introduction: Ergospirometry is a noninvasive procedure used to assess physical performance or the capacity of an individual, through an analysis of expired gases and respiratory variables. This procedure is crucially important in sports, and makes a significant contribution to the measurement of cardiorespiratory fitness indices, such as maximal oxygen consumption (VO2 max) and the anaerobic threshold (AT). Objective: To assess aerobic capacity and potency in professional and junior soccer players, handball athletes, and women soccer players. Methods: Forty-eight athletes participated voluntarily and were divided into 4 groups. The first group consisted of 12 youth soccer players in the under-20 category, the second group was made up of 12 professional soccer players, the third group was made up of female soccer players, and the fourth group consisted of handball players. Results: We analyzed values such as peak VO2, average speed and heart rate at the anaerobic threshold as well as pulmonary ventilation. We found that the values were always greater for the group formed by professional soccer players, with the exception of mean maximum O2 consumption, in which the difference between this group and that of soccer players in the junior category was not significant. In other physical valences, there was a degree of similarity between the other groups, with special emphasis on pulmonary ventilation, which was significantly lower in the group of female soccer players. Conclusion: The particularities of each sport, such as pitch dimensions, duration, and tactical system, together with the morphology and sex of the athletes, directly influence peak VO2, AT and VE values in athletes who play different sports. Level of Evidence III; Development of diagnostic criteria in consecutive patients (with gold reference standard applied).

Pre-season training has been demonstrated to modify the physical fitness and hormone levels in professional soccer players. The present study aimed to analyze the relationships between testosterone and cortisol with anthropometric characteristics in a professional male soccer team after the pre-season period. Fourteen volunteer professional male soccer players participated in this study. Significant decreases in anthropometric characteristics were found. For biochemical measures, cortisol (13) =-5.25, p=.001, d=-.27), testosterone (t (13) =-8.10, p=.001, d=-.65) and C/T ratio (t (13) =-4.07, p=.001, d =-0.2) significantly increased after the pre-season period. Moreover, moderate negative relationships were observed between the percentage of change in body weight, r=0.61, p=.01, body fat percentage, r=.53, p=.04, and testosterone. The present study revealed that the improvements in body composition after intense training in the pre-season period could stimulate anabolic activities such as increases in muscle mass, which is an important result in terms of quality of performance and prevention of injury risk, especially throughout the competitive soccer season. Testosterone and cortisol should be considered for future research as stress and recovery state indicators. In fact, professional soccer staff can use these parameters in combination with other indicators to optimize workloads and avoid overreaching and overtraining. Keywords: Testosterone; cortisol; professional soccer players; performance; physical fitness

PURPOSE: To describe the anthropometric and body composition profile (determined by the five-way fractionation method) of young professional Mexican soccer players. METHODS: A retrospective cross-sectional study was carried out in soccer players of the Club Deportivo Guadalajara, A.C. (Chivas), belonging to the following categories: under-17, under-20, second, third and fourth division. Body weight, height, sitting height, skinfolds, girths and bone breadths were measured by five level II certified anthropometrists from September 2011 to March 2014, following the procedures described by the International Society for the Advancement of Kinanthropometry. Body composition was determined by the five-way fractionation method, which considers the following tissues (in kg): muscle mass, adipose mass, bone mass, skin mass and residual mass. Excel databases were built and descriptive analyses were performed in SPSS version 22 for Windows. RESULTS: Five hundred ninety seven subjects were included: 21.8% from second division, 15.1% from third division, 19.9% from fourth division, 20.8% from sub-17 category and 22.4% from sub-20 category. Mean age was 17.9(1.8) years old, (minimum 14.79, maximum 23.23). Anthropometric and body composition profiles were obtained and described in tables according to position play and category. Data is presented as mean, standard deviation, mean, minimum value and maximum value. CONCLUSION: These tables can be used as anthropometric standards for Mexican professional young soccer players, since no similar references are found in the literature in Mexico, especially using the five-way fractionation method. In addition, these tables are expected to keep on growing and they could allow to follow-up the anthropometric changes in professional soccer players, since youth to adulthood.

Full text Figures and data Side by side Abstract Editor's evaluation Introduction Materials and methods Results Discussion Data availability References Decision letter Author response Article and author information Metrics Abstract Background: Oxygen uptake (VO2) is one of the most important measures of fitness and critical vital sign. Cardiopulmonary exercise testing (CPET) is a valuable method of assessing fitness in sport and clinical settings. There is a lack of large studies on athletic populations to predict VO2max using somatic or submaximal CPET variables. Thus, this study aimed to: (1) derive prediction models for maximal VO2 (VO2max) based on submaximal exercise variables at anaerobic threshold (AT) or respiratory compensation point (RCP) or only somatic and (2) internally validate provided equations. Methods: Four thousand four hundred twenty-four male endurance athletes (EA) underwent maximal symptom-limited CPET on a treadmill (n=3330) or cycle ergometer (n=1094). The cohort was randomly divided between: variables selection (nrunners = 1998; ncyclist = 656), model building (nrunners = 666; ncyclist = 219), and validation (nrunners = 666; ncyclist = 219). Random forest was used to select the most significant variables. Models were derived and internally validated with multiple linear regression. Results: Runners were 36.24±8.45 years; BMI = 23.94 ± 2.43 kg·m−2; VO2max=53.81±6.67 mL·min−1·kg−1. Cyclists were 37.33±9.13 years; BMI = 24.34 ± 2.63 kg·m−2; VO2max=51.74±7.99 mL·min−1·kg−1. VO2 at AT and RCP were the most contributing variables to exercise equations. Body mass and body fat had the highest impact on the somatic equation. Model performance for VO2max based on variables at AT was R2=0.81, at RCP was R2=0.91, at AT and RCP was R2=0.91 and for somatic-only was R2=0.43. Conclusions: Derived prediction models were highly accurate and fairly replicable. Formulae allow for precise estimation of VO2max based on submaximal exercise performance or somatic variables. Presented models are applicable for sport and clinical settling. They are a valuable supplementary method for fitness practitioners to adjust individualised training recommendations. Funding: No external funding was received for this work. Editor's evaluation The authors have established new formulas to predict maximum oxygen uptake for cyclists and runners based on submaximal exercise testing and anthropometric characteristics. This is an important study with a large and comprehensive dataset, which may be helpful for many exercise labs. The work is convincing, using appropriate and validated methodology in line with the current state-of-the-art, as shown by references to common exercise books. https://doi.org/10.7554/eLife.86291.sa0 Decision letter Reviews on Sciety eLife's review process Introduction The oxygen uptake (VO2) is considered an important metric in assessing cardiorespiratory fitness, health status, or endurance performance potential (Guazzi et al., 2012). With the application of standardised procedures and interpretation protocols, during graded exercise tests (GXT), the (maximal oxygen uptake) VO2max can be established (Bentley et al., 2007). GXT is the most widely used assessment to examine the dynamic relationship between exercise and integrated physiological systems (Albouaini et al., 2007; Bentley et al., 2007). The information from GXT during cardiopulmonary exercise testing (CPET) can be applied across the spectrum of sport performance, occupational safety screening, research, and clinical diagnostics (Guazzi et al., 2017). VO2 max is often used as a boundary between severe and extreme intensity domains and by definition requires maximal effort from the tested subject (Gaesser and Poole, 1996). However, it is not always recommended or possible to undertake a test to exhaustion (Guazzi et al., 2012). For the athletes, the proximity of competition or injury history can allow submaximal testing, but not testing to exhaustion (Sassi et al., 2006). Testing that requires maximal effort may be disruptive to the training process or interfere with race performance (Coutts et al., 2007; Lamberts et al., 2011). Due to practical constraints, tests to exhaustion or peak-power-output tests are often performed only two or three times a year (Coutts et al., 2007). However, VO2 values are widely used in sport science and the decision-making process (Mann et al., 2013). VO2 is widely considered one of the major endurance performance determinants (Joyner and Coyle, 2008). Using VO2max to guide the selection process, prescribing training intensity, assessing training adaptations, or predicting race times is a common practice in high-performance sports (Bassett and Howley, 2000; Bentley et al., 2007; Hawley and Noakes, 1992; Noakes et al., 1990). VO2max is also one of the critical vital signs coordinating the function of the cardiovascular, respiratory, and muscular systems, it is an indicator of overall body health status (Kaminsky et al., 2017). Quantifying VO2max provides additional input regarding clinical decision-making, risk stratification, evaluation of therapy, and physical activity guidelines (Guazzi et al., 2012). For patients undertaking a test to exhaustion is rarely needed or possible due to health restraints or cardiac risk (Guazzi et al., 2016). For many years researchers have studied indirect methods of estimating VO2max(Sartor et al., 2013). Protocols such as the Astrand-Ryhming Test, Six-Minute Walk Test, or YMCA Step Test have been established and validated (Astrand and Ryhming, 1954; Beutner et al., 2015; Carey, 2022; Jalili et al., 2018). Moreover, estimation of the VO2 and heart rate (HR) values below the ventilatory threshold can be based on cardiorespiratory kinetics assessment using randomised changes in the work rate known as a pseudo-random binary sequences testing (Hoffmann et al., 2022). However, with the development of technology, the accessibility of laboratory testing and mobile testing improved (Montoye et al., 2020; Pritchard et al., 2021). Therefore, new opportunities to develop more precise yet simple and accessible methods and models to assess VO2max occur (Jurov et al., 2023). This appears to be especially important considering the low prediction accuracy of most of the VO2max formulae that were validated in our previous study (Wiecha et al., 2023). Recently, we have been observing the development of prediction methods with the usage of machine learning (ML) and artificial intelligence (AI) (Ashfaq et al., 2022). Both ML and AI are used in sport science as forecasting and decision-making support tools (Abut and Akay, 2015; Bobowik and Wiszomirska, 2022; Chmait and Westerbeek, 2021; Hammes et al., 2022; Rossi et al., 2021). There is growing evidence that VO2max prediction based on ML models, especially support vector ML and artificial neural network models, exhibits more robust and accurate results compared to MLR only (Abut and Akay, 2015; Ashfaq et al., 2022). Therefore, in this research, with the support of ML, we look for algorithms and prediction patterns that allow us to use values obtained during submaximal CPET and somatic measurements to estimate maximal VO2max values in male runners and cyclists. We stipulate that prediction models allow for accurate calculation of VO2max based on somatic or submaximal CPET variables. Materials and methods We have applied the development and validation of the prediction TRIPOD guidelines to conduct the study (see Supplementary Material 1TRIPOD Checklist for Prediction Model Development and Validation) (Collins et al., 2015). The study is based on retrospective data analysis from the CPET registry collected from 2013 to 2021 at the medical clinic (Sportslab, Warsaw, Poland). All CPET have been performed at the individual request of participants, as a part of regular training monitoring or performance assessment. Ethical approval Request a detailed protocol The Institutional Review Board of the Bioethical Committee at the Medical University of Warsaw (AKBE/32/2021) has approved the study protocol. The regulations of the Declaration of Helsinki were met during all parts of the study. Each study participant delivered written consent to undergo CPET and participate in the study. Derivation cohort Request a detailed protocol We selected the cohort with the use of rigorous exclusion/inclusion criteria. Due to the insufficient number of women in our database and the number of potential variables in the regression models for adequate power, we had to limit ourselves to conduct analysis in the male population only (Martens and Logan, 2021). Out of 6439 healthy, adult male cyclists and long-distance runners that undergone CPET, 4423 met the criteria as further: (1) age ≥18 years, (2) declared regular cycling or running training for ≥3 months, (3) had no extreme outliers ≤ or ≥±3 standard deviations (SD) from mean for all of the testing variables (beyond ≥±3 SD in VO2max), (4) lack of any injury, medical condition, or addiction in medical history that may affect exercise capacity, (5) not taking any medications with a modifying effect on exercise capacity, (6) maximum exertion achieved during CPET. We defined the maximum exertion in CPET as the fulfilment of the minimum six of the following criteria: (1) respiratory exchange ratio (RER) ≥1.10, (2) present VO2 plateau (growth <100 mL·min–1 in VO2 despite increased running speed or cycling power), (3) respiratory frequency (fR) ≥45 breaths·min–1, (4) declared subjective exertion intensity during CPET ≥18 in the Borg scale (Borg, 1970), (5) blood lactate concentration [La-]b ≥8 mmol·L–1, (6) growth in speed/power ≥10% of respiratory compensation point (RCP) values after exceeding the RCP, (7) peak heart rate (HRpeak) ≥15 beats·min–1 below predicted maximal heart rate (HRmax) (Lach et al., 2021). Participants’ selection procedure has been shown in Figure 1. Figure 1 Download asset Open asset Flowchart of the preliminary inclusion and exclusion process. Abbreviations: EA, endurance athlete; CPET, cardiopulmonary exercise testing; SD, standard deviation; TE, treadmill; RER, respiratory exchange ratio; VO2, oxygen uptake (mL·min−1·kg−1); [La−]b, lactate concentration (mmol·L−1); fR, breathing frequency (breaths·min−1); RCP, respiratory compensation point; HRpeak, peak heart rate (beats·min−1); HRmax, maximal heart rate (bpm). At both stages of the selection, some participants met several (>1) exclusion criteria. Somatic measurements and CPET protocols Request a detailed protocol Body mass was measured with a body composition (BC) analyser (Tanita, MC 718, Japan) with the multifrequency of 5 kHz/50 kHz/250 kHz via the bioimpedance analysis and normal testing mode. The participants’ skin was cleaned with alcohol before placing the electrodes on the skin. Prior to the test, the participants received instructions to refrain from exercising for 2 hr, consume a light meal rich in carbohydrates 2–3 hr beforehand, and maintain hydration by drinking isotonic beverages. Additionally, they were advised to abstain from medications, caffeine, and cigarettes on the day of the test. Running CPET (TE) was performed on a mechanical treadmill (h/p/Cosmos Quasar, Germany). Cycling CPET (CE) was performed on Cyclus-2 (RBM elektronik-automation GmbH, Leipzig, Germany). Hans Rudolph V2 mask (Hans Rudolph, Inc, Shawnee, KS, USA), breath-by-breath method with Cosmed Quark CPET gas exchange analysing device (Cosmed Srl, Rome, Italy), and Quark PFT Suite to Omnia 1.6 software were utilised. The gas analyser device was regularly calibrated with the reference gas (16% O2; 5% CO2) in accordance with the manufacturer’s instructions (Airgas USA, LLC, Plumsteadville, PA, USA). From 2013 to 2021, three Cosmed Quark CPET units were used. HR was measured with the Cosmed torso belt (Cosmed srl, Rome, Italy). [La-]b was measured via enzymatic-amperometric electrochemical technique with Super GL2 analyser (Müller Gerätebau GmbH, Freital, Germany). The [La-]b analyser was regularly calibrated before each measurement series. The 40 m2 indoor, air-conditioned laboratory with 20–22°C temperature and 40–60% humidity, and 100 m ASL provided the same conditions for all BC and CPET. Each CPET began with a 5 min personalised warm-up (walk or easy jog with ‘conversational’ intensity for running, easy pedalling with ‘conversational’ intensity for cycling). Then after the preparation (about 5 min), the continuous progressive step test was conducted. Due to the population diversity (training status), the running test speed started from 7 to 12 km·hr–1 with a 1% treadmill incline. The choice of initial starting speed was determined by the interview and sports results achieved. For example, those running less than 60 min at a distance of 10 km started the test at 7 km/hr, while those running 10 km for less than 35 min started the test at an initial speed of 12 km/hr. The pace increased by 1 km·hr–1 every 2 min with no change in incline. The cycling test began at 60–150 W, depending on the athletes training status. The power increased by 20–30 W every 2 min. It was recommended to maintain a constant cadence of 80–90 (repetition·min–1) during the test. The tests were terminated due to exhaustion: volitional inability to continue the activity or/and VO2 and HR plateau with increasing load or/and observed disturbance of coordination in running or/and inability to maintain the set cadence. Due to the graded protocol used, the cycling power and running speed values have been calculated as a function of time to better reflect the actual level for the test moment being determined (Kuipers et al., 1985). Before the test, after every step, and 3 min after the termination of the effort technician took a 20 µL blood sample from a fingertip. Samples were collected during the test without interrupting the effort. The samples were taken from the initial puncture. The first blood drop was collected into the swab and the second blood drop was drawn for further analysis into the capillary. VO2max was recorded as the highest value (15 s intervals) before the termination of the test. HRmax was recorded as the highest value obtained at the end of the test, without averaging. The anaerobic threshold (AT) was established with the following criteria: (1) common start of VE/VO2 and VE/VCO2 curves, (2) end-tidal partial pressure of oxygen raised constantly with the end-tidal partial pressure of carbon dioxide (Beaver et al., 1986). The was established with the following criteria: (1) PetCO2 must decrease after reaching maximal amount, (2) the presence of fast nonlinear growth in VE (second deflection), (3) the VE/VCO2 ratio achieved minimum and started to rise, and (4) a nonlinear increase in VCO2 versus VO2 (lack of linearity) (Beaver et al., 1986). The [La-]b was estimated for AT and RCP in relation to power or speed (Wiecha et al., 2022). Data analysis Request a detailed protocol Our comprehensive ML approach enables the evaluation of each formula by preliminary variables precision (at the stage of selection), then accuracy (during the model’s building) and recall (in internal validation). Individual CPET results were saved into the Excel file (Microsoft Corporation, Redmond, WA, USA) and a custom-made script was used to generate the database in Excel (Python programming). Further, mean, SD, and 95% confidence intervals (CI) were calculated. The normality of the distribution of the data was examined using the Shapiro-Wilk test and intergroup differences were calculated using the Student’s t-test for independent variables. Three-step variable selection procedures based on random forests were applied using the R package VSURF in RStudio software (R Core Team, Vienna, Austria; version 3.6.4) (Genuer et al., 2016). For each level of measurement (AT, RCP) and their combination (AT+RCP), significant variables were identified separately. The first step was dedicated to eliminate irrelevant variables from the dataset. Second step aimed to select all variables related to the response for interpretation purposes. The third step refined the selection by eliminating redundancy in the set of variables selected by the second step, for prediction purposes (Genuer et al., 2017). Each time for variables selection, the anthropometric variables as in Tables 1–2 and the CPET parameters given in Tables 3–4 from a specific level of measurement (AT; RCP) and their combinations were visible. Table 1 Basic anthropometric characteristics for runners. Variable (unit)Derivation group n=1998Testing group n=666Validation group n=666MeanCISDMeanCISDMeanCISDAge (years)36.235.6–36.98.4535.935.5–36.38.0535.534.9–36.28.14Height (cm)180.0179.6–180.56.04179.4179.1–179.76.13179.7179.2–180.26.61BM (kg)77.777.0–78.49.3577.777.3–78.19.2977.977.1–78.610.1BMI (kg·m–2)23.923.8–24.12.4324.124.0–24.22.4124.123.9–24.32.56BF (%)15.415.1–15.74.5515.515.3–15.74.5215.415.1–15.84.55FM (kg)12.211.9–12.64.6812.312.1–12.54.6512.311.9–12.74.92FFM (kg)65.565.0–66.06.4365.465.1–65.76.3165.665.1–66.16.86 BM, body mass; BMI, body mass index; BF, body fat; FM, fat mass; FFM, fat-free mass; CI, 95% confidence interval; SD, standard deviation. Table 2 Basic anthropometric characteristics for cyclists. Variable (unit)Derivation group n=656Testing group n=219Validation group n=219MeanCISDMeanCISDMeanCISDAge (years)37.336.6–38.09.1337.135.9–38.49.5037.636.5–38.88.46Height (cm)179.9179.4–180.46.27180.1179.2–181.06.96180.2179.4–181.06.13BM (kg)78.878.1–79.69.8079.177.7–80.510.479.878.4–81.310.9BMI (kg·m–2)24.324.1–24.62.6324.424.0–24.72.8024.624.2–25.02.96BF (%)16.415.7–17.14.9916.115.7–16.54.8116.215.5–16.84.87FM (kg)13.312.6–14.15.6613.012.6–13.45.2713.312.5–14.05.85FFM (kg)65.864.9–66.66.2565.865.4–66.36.0666.665.7–67.46.58 BM, body mass; BMI, body mass index; BF, body fat; FM, fat mass; FFM, fat-free mass; CI, 95% confidence interval; SD, standard deviation. Table 3 Cardiopulmonary exercise testing (CPET) characteristics for runners. Variable (unit)Derivation group n=1998Testing group n=666Validation group n=666MeanCISDMeanCISDMeanCISDrVO2AT (mL·min–1·kg–1)38.438.1–38.85.0138.538.3–38.74.8838.137.7–38.55.16RERAT0.870.86–0.870.040.870.86–0.870.040.870.86–0.870.04HRAT (beats·min–1)151.5150.8–152.310.3151.0150.6–151.510.8152.0151.2–152.810.8VEAT (L·min–1)79.178.1–80.012.278.377.8–78.912.077.276.3–78.212.0SPEEDAT (km·h–1)11.010.9–11.11.4511.011.0–11.11.3610.910.8–11.01.42LAAT (mmol·L–1)2.082.02–2.140.631.801.76–1.830.622.352.27–2.420.72rVO2RCP (mL·min–1·kg–1)47.547.0–48.05.8847.747.4–48.06.1547.346.8–47.86.16RERRCP1.001.00–1.000.041.001.00–1.000.041.001.00–1.000.03HRRCP (beats·min–1)173.4172.7–174.19.21173.2172.8–173.69.30174.3173.5–175.09.50VERCP (L·min–1)114.7113.5–116.015.9113.9113.1–114.616.7112.7111.4–114.016.2SPEEDRCP (km·h–1)14.013.9–14.11.7714.114.0–14.11.7013.913.8–14.11.75LARCP (mmol·L–1)4.724.63–4.821.044.404.34–4.451.044.814.69–4.931.14rVO2max (mL·min–1·kg–1)53.853.3–54.36.6754.354.0–54.66.9553.853.3–54.37.09 CI, 95% confidence interval; SD, standard deviation; rVO2AT, oxygen uptake at anaerobic threshold relative to body mass; RERAT, respiratory exchange ratio at anaerobic threshold; HRAT, heart rate at anaerobic threshold; VEAT, pulmonary ventilation at anaerobic threshold; SPEEDAT, velocity at anaerobic threshold; LAAT, blood lactate concentration at anaerobic threshold; rVO2RCP, oxygen uptake at respiratory compensation point relative to body mass; RERRCP, respiratory exchange ratio at respiratory compensation point; HRRCP, heart rate at respiratory compensation point; VERCP, pulmonary ventilation at respiratory compensation point; SPEEDRCP, velocity at respiratory compensation point; LARCP, blood lactate concentration at respiratory compensation point; rVO2max, maximal oxygen uptake relative to body mass. Table 4 Cardiopulmonary exercise testing (CPET) characteristics for cyclists. Variable (unit)Derivation group n=656Testing group n=219Validation group n=219MeanCISDMeanCISDMeanCISDrVO2AT (mL·min–1·kg–1)33.032.5–33.45.8433.232.4–33.95.6833.732.9–34.55.89RERAT0.870.87–0.870.040.870.87–0.880.040.870.87–0.880.04HRAT CI, 95% confidence interval; SD, standard deviation; rVO2AT, oxygen uptake at anaerobic threshold relative to body mass; RERAT, respiratory exchange ratio at anaerobic threshold; HRAT, heart rate at anaerobic threshold; VEAT, pulmonary ventilation at anaerobic threshold; power at anaerobic threshold relative to body mass; LAAT, blood lactate concentration at anaerobic threshold; rVO2RCP, oxygen uptake at respiratory compensation point relative to body mass; RERRCP, respiratory exchange ratio at respiratory compensation point; HRRCP, heart rate at respiratory compensation point; VERCP, pulmonary ventilation at respiratory compensation point; LARCP, blood lactate concentration at respiratory compensation point; power at respiratory compensation point relative to body mass; rVO2max, maximal oxygen uptake relative to body mass. selection variables were in the further only selected parameters were into multiple linear regression The data for MLR model building were randomly into that is testing, validation and of the a only significant were in the Derived are by the of mean and mean analysis was used to the model’s precision and accuracy during validation and tests to the fulfilment of MLR test the of in MLR test assessment between and test of Each model was examined the and any have not been 2 package in RStudio (R Core Team, Vienna, Austria; version version for and software version were used in was considered as the Results Somatic measurements and CPET results data of the runners models for testing, and validation are in Table while cyclists are in Table The runners of and for testing, and validation the cyclists and differences between of runners and cyclists were in BMI and between testing in all between validation only in CPET results for runners models are in Table 3 and for cyclists in Table Runners in the cohort achieved relative to body mass VO2max of in testing group and in validation group cyclists mean was and for testing, and validation to body mass oxygen uptake at anaerobic threshold in runners for ± ± and ± of in testing, and validation it was ± ± and ± of rVO2max, relative to body mass oxygen uptake at respiratory compensation point in runners for ± ± and ± of for testing, and validation while in cyclists for ± ± and ± of rVO2max, There were no significant differences in values between testing, and validation the runners and cyclists between runners and cyclists results were all significant Prediction models based on AT and RCP Full of MLR prediction models for cyclists are in Table for runners in Table The models prediction performance is as with and for cyclists from for somatic parameters to for RCP equations. For runners from for to for AT and equations. for cyclists models was the for RCP and the highest for For from for AT and to for equation. observed for cyclists was the for RCP in the validation group and the highest for while in runners the for AT and and the highest for The performance of prediction is in Figure Figure 2 Download asset Open asset of prediction for Abbreviations: maximal oxygen anaerobic threshold; RCP, respiratory compensation point; All values are in performance for running while the performance for cycling equations. performance of the prediction model for for for AT and for somatic-only equation. Table 5 VO2max prediction for cyclists. linear regression group group = = = = based on anaerobic threshold; RCP, based on respiratory compensation point; based on somatic variables mean mean maximal oxygen uptake relative to body mass rVO2AT, oxygen uptake at anaerobic threshold relative to body mass power at anaerobic threshold relative to body mass rVO2RCP, oxygen uptake at respiratory compensation point relative to body mass VERCP, pulmonary ventilation at respiratory compensation point BF, body fat BM, body mass Table VO2max prediction for runners. linear regression group group = = = = based on anaerobic threshold; RCP, based on respiratory compensation point; based on somatic variables mean mean maximal oxygen uptake relative to body mass rVO2AT, oxygen uptake at anaerobic threshold relative to body mass SPEEDAT, velocity at anaerobic threshold FFM, fat mass VEAT, pulmonary ventilation at anaerobic threshold HRAT, heart rate at anaerobic threshold BF, body fat rVO2RCP, oxygen uptake at respiratory compensation point relative to body mass SPEEDRCP, velocity at respiratory compensation point Models validation of each model for cyclists is in Table while for runners in Table the performance of our prediction was to that observed in the

The professional and amateur soccer players were tested to determine the running speed and agility performance by playing positions. The sample included 108 professional male soccer players at the national level and 79 amateur male soccer players at a regional level on teams from 10 clubs in Turkey. The study involved the players being assessed by the 10- x 5-m shuttle run test ( 10 x 5 SRT) on a soccer field in a soccer season.The difference between the mean scores of the professional and amateur players is significant. Differences between mean scores according to playing positions of soccer players are not significant.In conclusion, professional soccer players' running speed and agility performances are higher than amateur soccer players. In addition, these results indicate that all soccer players have the same running speed and agility performance in accordance with their different playing positions. Coaches should consider individual training programs based on the positional role of soccer players.

The aims of this study were (a) to assess and correlate interval shuttle run test (ISRT) performance, maximum oxygen uptake (V[Combining Dot Above]O(2)max), running economy (RE), running velocity at the first rise in blood lactate concentrations above baseline (vLT) and running velocity at 4 mmol·L(-1) blood lactate concentration (v4) in professional soccer players and (b) to investigate whether a correlation exists between the respective results of time to exhaustion (T(lim)) from continuous and intermittent endurance tests, respectively. Eleven male professional field soccer players (mean ± SD: age 23.8 ± 3.0 years, V[Combining Dot Above]O(2)max 58.2 ± 4.9 ml·kg(-1)·min(-1)) completed a continuous Incremental Test with lactate measurements to determine vLT and v4, a continuous Ramp Test with gas exchange analysis to determine V[Combining Dot Above]O(2)max and RE, and an intermittent ISRT to determine intermittent endurance capacity during the first week of preseason preparation. There were significant correlations between ISRT performance and V[Combining Dot Above]O(2)max (r = 0.70, p < 0.05), and between T(lim) in both continuous endurance tests (r = 0.89, p < 0.01). Between all other variables no significant correlations were found overall (best r = 0.60, p > 0.05). The assessment of all values of V[Combining Dot Above]O(2)max, RE, vLT, and v4 should be included when investigating aerobic endurance performance among groups or over time in professional soccer players. Although V[Combining Dot Above]O(2)max, RE, vLT, and v4 have been regarded as important factors of aerobic performance in endurance related sports, the present data revealed that V[Combining Dot Above]O(2)max was the only factor, which correlated with intermittent endurance capacity in professional soccer players. Hence, V[Combining Dot Above]O(2)max should be increased through soccer-specific training interventions including universal agility components. The T(lim) in continuous and intermittent endurance tests differs and is therefore an independent endurance performance factor in professional soccer players.

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This study compared the effects of two different half-squat training programs on the repeated-sprint ability of soccer players during the preseason. Twenty male professional soccer players were divided into 2 groups: One group (S-group) performed 4 sets of 5 repetitions with 90% of their 1-repetition maximum (1RM), and the other group (H-group) performed 4 sets of 12 repetitions with 70% of 1RM, 3 times per week for 6 weeks, in addition to their common preseason training program. Repeated-sprint ability was assessed before and after training by 10 × 6-second cycle ergometer sprints separated by 24 seconds of passive recovery. Maximal half-squat strength increased significantly in both groups (p < 0.01), but this increase was significantly greater in the S-group compared with the H-group (17.3 ± 1.9 vs. 11.0 ± 1.9%, p < 0.05). Lean leg volume (LLV) increased only in the H-group. Total work over the 10 sprints improved in both groups after training, but this increase was significantly greater in the second half (8.9 ± 2.6%) compared with the first half of the sprint test (3.2 ± 1.7%) only in the S-group. Mean power output (MPO) expressed per liter of LLV was better maintained during the last 6 sprints posttraining only in the S-group, whereas there was no change in MPO per LLV in the H-group over the 10 sprints. These results suggest that resistance training with high loads is superior to a moderate-load program, because it increases strength without a change in muscle mass and also results in a greater improvement in repeated sprint ability. Therefore, resistance training with high loads may be preferable when the aim is to improve maximal strength and fatigue during sprinting in professional soccer players.

Gene variants within the COL1A1 gene are associated with reduced anterior cruciate ligament injury in professional soccer players

Background/Objectives: Urinary incontinence (UI), defined as the involuntary loss of urine, is common among female athletes. As more women engage in competitive sports, numerous studies have explored UI in young, nulliparous, and physically active women. The objectives of this study were (i) to analyze the prevalence, severity, and characteristics of UI in professional nulliparous female soccer players and (ii) to compare the status of the pelvic floor muscles (PFMs) between professional soccer players and physically active young women. Methods: This descriptive cross-sectional study included professional soccer players (n = 18) and physically active women (n = 14). UI was assessed using the ICIQ-SF questionnaire, and PFM function was evaluated through intracavitary examination using the PERFECT method. Additional data were collected on body composition and on urinary, bowel, and sexual health. Results: UI affected 35.7% of physically active women and 50% of professional soccer players. Stress urinary incontinence (SUI) was the most common type, present in 100% of affected soccer players and 60% of affected active women. The severity of UI was mostly mild, with no significant differences between groups. PFM assessment revealed deficiencies in control, relaxation, endurance, and rapid contractions, as well as difficulties performing an effective perineal locking (PL) maneuver during increased intra-abdominal pressure. Conclusions: These findings highlight the need for targeted programs focused on strengthening and educating athletes about their PFMs, aiming to prevent UI and improve both performance and quality of life. The study reinforces the importance of preventive strategies for pelvic floor health in sports.

Anterior cruciate ligament (ACL) ruptures represent one of the most severe injuries in professional football, often resulting in long rehabilitation, impaired performance, and increased risk of re-injury. The aim of this study was to investigate whether performance parameters derived from match statistics can serve as early indicators of ACL rupture in professional male football players. A retrospective case-control design was applied. Forty-two male professional football players from the German Bundesliga and 2. Bundesliga with confirmed ACL ruptures between 2016 and 2024 were included, alongside 42 matched controls from the same teams and positions. Match performance data from ten games preceding the injury were analyzed. Parameters included minutes played, total distance covered, number of sprints, maximal speed, pass accuracy, number of duels, and duel success rate. Independent t-tests compared injured and control players across individual matchdays and aggregated intervals (the average values across the last four, three, and two matches before injury). Additionally, odds ratios (OR) with 95% confidence intervals were computed based on upper (≥ 75th percentile) and lower (≤ 25th percentile) quartile thresholds to quantify the relative risk associated with extreme performance values. Injured players showed higher maximum speed that consistently differentiated them from controls, with significant differences at matchday 2 (p = 0.005, OR = 3.42, 95% CI 1.45-8.06) and across all aggregated intervals (p = 0.015-0.031). Injured players also showed significantly fewer minutes played at matchday 2 before injury (p = 0.046, OR = 2.36, 95% CI 1.01-5.51) and across certain intervals (last four and three matches before injury; p = 0.027-0.044). Analysis of matchdays 5-10 revealed no significant group differences for any performance parameter, confirming that relevant performance changes manifest primarily in the immediate pre-injury period. No significant group differences emerged for distance covered, sprint count, pass accuracy, or duel frequency between ACL injured players and controls. Maximum speed showed the strongest association with ACL rupture risk, with significant differences at matchday 2 (p = 0.005) and across aggregated intervals (the average values across the last four, three, and two matches before injury). Reduced playing time emerged as an additional indicator. Although distance covered, sprint count, and pass accuracy did not reach statistical significance individually, their temporal patterns revealed a predisposing risk constellation: injured players demonstrated reduced cumulative exposure combined with acute high-intensity spikes at matchday 2, declining technical precision, and increased physical confrontation at matchday 1. This suggests ACL injury risk manifests through deterioration of integrated performance capacity under acute load fluctuations rather than isolated thresholds. Multifactorial approaches integrating biomechanical, physiological, and temporal performance patterns are essential for effective ACL injury prevention in professional football.

The research involved the preparation of isokinetic exercises for soccer players who had a partial rupture of the anterior cruciate ligament in the knee, and the determination of the crucial effectiveness of these exercises in the rehabilitation of the partial rupture of the anterior cruciate ligament of soccer players. The researchers use the experimental curriculum (pre-test and post-test) over one group. The research community is determined with soccer players who have partial rupture of anterior cruciate ligament the of knee in Babylon Centre for disabled Rehabilitation and Hospital of Imam Al-Sadiq in Babylon province. Their number was (6) players. The research sample was selected by the intentional method and the researchers performed rehabilitation sessions with isokinetic exercises that included (24) sessions and a rate of (3) sessions per week. The researchers used the statistical program (SPSS) to extract the results. The researchers come to several conclusions, including that isokinetic exercises play an active role in the progress of qualification of partial rupture of the anterior cruciate ligament in soccer players.