Next Article in Journal
Effect of Soft Interlayer Dip Angle on the Attenuation and Prediction of Blast-Induced Vibrations in Rock Slopes: An Experimental Study
Previous Article in Journal
A Survey on Deep Learning in 3D CAD Reconstruction
Previous Article in Special Issue
Handgrip Strength as an Indicator of Overall Strength and Functional Performance—Systematic Review
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 15
Issue 12
10.3390/app15126685
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Physiological Differences in Cardiorespiratory and Metabolic Parameters Between Football Players from Top- and Mid-Ranked Teams in the Serbian Super League

by
Radivoje Radakovic
1,2,
Dejan Martinovic
3,
Borko Katanic
4,*,
Karuppasamy Govindasamy
5,
Nikola Prvulovic
6,
Vlad Adrian Geantă
7,* and
Viorel Petru Ardelean
7
1
Institute of Information Technologies, University of Kragujevac, 34000 Kragujevac, Serbia
2
Bioengineering Research and Development Center, 34000 Kragujevac, Serbia
3
Faculty of Sport and Physical Education, University of Nis, 18000 Nis, Serbia
4
Montenegrin Sports Academy, 81000 Podgorica, Montenegro
5
Department of Sports, Recreation and Wellness, Symbiosis International (Deemed University), Hyderabad Campus, Modallaguda (V), Nandigama (M), Rangareddy, Telangana 509217, India
6
Institute for Medical Research, National Institute of Republic of Serbia, University of Belgrade, 11000 Beograd, Serbia
7
Faculty of Physical Education and Sport, Aurel Vlaicu University of Arad, 310010 Arad, Romania
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2025, 15(12), 6685; https://doi.org/10.3390/app15126685
Submission received: 24 April 2025 / Revised: 6 June 2025 / Accepted: 11 June 2025 / Published: 13 June 2025
(This article belongs to the Special Issue Advances in Assessment of Physical Performance)
Versions Notes

Abstract

This study investigated physiological differences in cardiorespiratory and metabolic performance parameters between professional football players from top- (TR) and mid-ranked teams (MR) in the Serbian Super League. A total of 55 male outfield players (TR: n = 29; MR: n = 26) were assessed in March 2022 using a maximal multistage treadmill protocol and lactate analysis. The key cardiorespiratory variables included maximum oxygen uptake (VO2max), heart rate at the anaerobic threshold (HR AT), and recovery heart rate metrics, while the metabolic variables focused on lactate concentrations and efficiency indices. The results indicate that the TR players achieved significantly lower HR AT values (162 ± 10.26 vs. 168.77 ± 7.28 bpm; p = 0.017) and demonstrated superior second-minute recovery (%Re 2′: 66.62 ± 14.08% vs. 34.53 ± 9.13%, p < 0.001). In contrast, the MR players exhibited higher VO2max (62.65 ± 4.48 vs. 60.06 ± 3.29 mL/kg/min; p = 0.017) and greater cardiorespiratory efficiency scores. The lactate parameters were comparable between the groups, except for the metabolic efficiency index (Index ME), which were favorable among the TR players (p = 0.011). These findings highlight that while MR players possess higher aerobic capacity, TR players demonstrate superior physiological recovery and metabolic control, reflecting adaptations to different tactical demands and match intensities. The results offer practical implications for individualized training design and performance monitoring in elite football settings.

1. Introduction

Football is one of the most popular team sports around the world, and it is characterized by a high-intensity game and participation by football players at national and international levels. In addition to high technical and tactical skills, professional football is characterized by high requirements for aerobic and anaerobic capacity. The values of aerobic capacities in national and international football among successful football players are quite high [1]. The football game contains various short- and long-term activities, such as sprinting and jumping on the playing field. Considering that the game lasts a long time, aerobic capacity is necessary throughout the entire game [2]. Performing short- and long-term activities requires a high level of physiological demand, which greatly burdens aerobic and anaerobic energy capacities throughout the whole game [3]. A higher level of aerobic capacity provides a better baseline for performance on the field in terms of playing activities [4]. A higher maximal oxygen consumption (VO2max) can give an advantage when playing against an opponent with a lower VO2max. However, achieving the VO2max advantage depends on many factors, such as technical–tactical skills [5]. In general, players from less successful teams often engage in more high-intensity running and cover greater distances compared to players from top-ranked teams, possibly reflecting compensatory strategies during play [6,7,8].

1.1. Cardiorespiratory Demand in Football Players

The high degree of physiological load during professional football competition demands from players a high degree of cardiovascular fitness. The intensity of playing football is reflected in the fact that the football game includes both aerobic and anaerobic capacities. The aerobic capacity enables a high level of play during an entire football game [9]. High-intensity activities appear more frequently in lower-ranked teams, likely due to tactical strategies aimed at regaining possession and compensating for technical or organizational disadvantages [10]. In such scenarios, players are required to coordinate efforts and exert sustained physical pressure against stronger opponents. Another study also showed that higher values of total high-intensity running were more present in lower-ranked teams compared to high-ranked teams (919 ± 128 m vs. 885 ± 113 m). They stated that this greater activity is a consequence of their effort to regain possession of the ball [7].
The average distance covered by male elite football players throughout a game is approximately 11 km during 90 min of play [8,11,12]. Moreover, it is essential for a player to consistently perform high-intensity efforts, including sprinting and generating significant power during specific in-game actions, such as shooting, jumping, and engaging in physical duels. To meet the demands of the sport, elite-level players must possess physical attributes that align with the physiological challenges of football. Match performance is shaped by the interplay of tactical understanding, physical fitness, technical skills, and psychological or social factors, all interconnected and mutually influential.
Endurance performance relies on two key elements: aerobic power and aerobic capacity. Aerobic power refers to the maximum rate at which the body can generate energy through aerobic metabolism, commonly measured as VO2max. Aerobic capacity denotes the ability to maintain physical activity over extended durations, effectively representing an individual’s overall stamina or endurance level [11].
Football scientists estimated that VO2max values above 60 mL/kg/min fulfill the corresponding requirements in men’s elite football [13,14,15,16]. Other authors found that VO2max corresponding values in professional football players were around 70 mL/kg/min [17,18]. In football, top-level players can achieve VO2max values ranging from 65 to 70 mL/kg/min, with variations influenced by factors such as age, individual fitness level, and playing position [19]. The most important corresponding factors that lead to high performance are the maximal produced physical working capacity, maximal heart rate (HRmax), maximal lactate concentration, VO2max, and other ergospirometry parameters [20].

1.2. Metabolic Demand in Football Players

Mader [21] introduced the term aerobic–anaerobic threshold in the literature, and it has undergone several modifications since then. He introduced the concept that an exercise intensity resulting in a lactate concentration of 4 mmol/L constituted the upper limit of exercise, above which lactate levels continued to rise. Diagnostic performance tests for the assessment of endurance performance in high-performance sports are hard to imagine today without the determination of lactic acid. Determination of lactate metabolism plays a major role in sports and performance medicine. It is used to record endurance performance and to evaluate training. Measuring lactate facilitates the assessment of metabolic processes during physical exertion, and the target parameter for diagnosis is the anaerobic threshold [20]. Stegmann, Kindermann, and Schnabel [22] defined the individual anaerobic threshold as the point in time at which the maximum rate of elimination and the rate of diffusion of lactate are in equilibrium. They reported that the lactate concentration at the individual anaerobic threshold varies widely among individuals, thus emphasizing the need for individual assessment.
The anaerobic lactate threshold largely determines the level of aerobic endurance capacity. Based on studies that have assessed endurance performance, it was proposed that the anaerobic threshold could be a more acceptable predictor of aerobic endurance than VO2max. It was reported that a change in training could lead to a change in the anaerobic threshold without a change in the VO2max [23]. It is indeed evident that the higher the level of football, the more frequent and longer the intervals of high-intensity exercise and the higher the lactate concentrations in the blood, which is often used as a criterion for anaerobic lactate production [1]. Earlier studies have indicated that the average intensity of a football game varies around the anaerobic lactate threshold, where the heart rate reaches 80 to 90% of the HRmax [4,24]. Most football activities are executed with low to moderate intensity, so the total energy expenditure is supplied by the aerobic energy capacity [25]. A higher aerobic energy capacity generally leads to improved football performance, providing increased potential for sustainably covering longer running lengths with higher intensity [26]. However, about 28% of football activities are executed at high intensity, which leads to a simultaneous increase in the level of lactate concentration to a submaximal level.

1.3. Metabolic Demand in Football Players of Different National Leagues

The corresponding values of blood lactate concentrations in Swedish football players were reported. After the first and second halves, First Division players showed blood lactate concentrations of 9.5 and 7.2 mmol/L, respectively. In comparison, Second Division players recorded values of 8.0 and 6.6 mmol/L, Third Division players had levels of 5.5 and 4.2 mmol/L, while Fourth Division players exhibited the lowest levels at 4.0 and 3.9 mmol/L [24]. The average values of blood lactate concentration in Danish football players of the First and Second Divisions during the first half of a competitive football match were 4.9 mmol/L, while the highest individual value was 10.3 mmol/L [27]. The average values of lactate concentration in the blood of the Italian First League players after a competitive football match were 6.3 ± 2.4 mmol/L, while the highest individual value was 11.3 mmol/L [28].
These reports show that the percentage of lactate production in muscles is high during a football match [29]. However, at a work intensity of 60–70% VO2max, the greatest reduction (16 to 11 mmol/L) of lactate in the blood was observed [24]. It is important to highlight that players with higher VO2max levels may exhibit lower blood lactate concentrations due to improved recovery from high-intensity intermittent activity. This is attributed to better aerobic responses, more efficient lactate clearance, and enhanced phosphocreatine regeneration [30]. However, they may experience similar blood lactate levels when exercising at a higher absolute intensity compared to their less fit counterparts [30,31].
Endurance performance is linked to the blood lactate response during sub-maximal continuous exercise, making lactate measurements valuable for assessing long-term exercise capabilities in players undergoing the same tests [32]. In a study of elite Danish football players, treadmill running tests revealed that full-backs and midfielders had higher oxygen uptake at a specific blood lactate concentration compared to central defenders and goalkeepers. Forwards, in line with their VO2max measurements, showed intermediate values between those of full-backs and midfielders. When oxygen consumption for a given lactate concentration was compared relative to VO2max, full-backs and midfielders also had slightly higher values. However, like the VO2max findings, no significant differences were found between regular and non-regular first-team players regarding the relationship between submaximal treadmill speeds and blood lactate concentrations. This suggests that these measurements should be interpreted carefully when distinguishing between top-level players [24].
Despite extensive research across major European leagues, comprehensive physiological profiling of male professional players in the Serbian Super League remains limited. Previous studies have not sufficiently examined intra-league variability in cardiorespiratory and metabolic performance, nor seasonal physiological changes. One recent study by Radaković et al. [33] evaluated VO2max and lactate thresholds in relation to match performance using regression models. However, it did not assess group-based physiological differences. It should also be noted that, to the authors’ knowledge, no studies have examined the differences between top-ranked and mid-ranked teams, as most existing research compares top-ranked with lower-ranked teams [34,35,36,37]. Additionally, there is a need for studies that investigate a wider range of cardiorespiratory and metabolic parameters in more detail than previous research [16,17,38,39].
The present study aims to address this gap by conducting a comparative analysis of cardiorespiratory and metabolic parameters between football players from top- and mid- ranked teams in the Serbian Super League. Our objective is to determine whether measurable physiological differences align with team status, thus providing relevant insights for individualized training and performance optimization at the elite level.

2. Materials and Methods

2.1. Participants

This comparative cross-sectional study included 55 male professional football players from the Serbian Super League, the highest national football competition, during the 2021/22 season. Players were selected randomly from four clubs, each providing 15 outfield players, resulting in an initial cohort of 60 participants. After excluding players who did not meet the eligibility criteria or had incomplete data, the final analytical sample comprised 55 athletes. The participants were divided into two groups based on their team’s league standing. The top-ranked team group (TR; n = 29) consisted of players from two teams ranked among the top five, while the mid-ranked team group (MR; n = 26) included players from two mid-ranked teams (from 6th to 10th place). Team selection was performed randomly within their respective ranking strata to minimize selection bias.
The eligibility criteria included male players aged between 18 and 35 years old, with a minimum of six years of structured football training, and no injuries in the previous 12 months or current illness at the time of testing. The exclusion criteria were goalkeepers, due to their distinct physical and tactical role [40,41], players under 18 years, those with recent injuries, and individuals for whom full physiological data were not obtained.
The previous literature on elite football players has shown that typical sample sizes have ranged between 15 and 25 participants [42,43,44]. In light of this, this study was designed to include a slightly larger cohort, targeting 30 players per group to enhance statistical power and data reliability.
All participants were informed of the study’s aim, procedures, and potential risks, and provided written informed consent. Ethical approval was granted by the Ethics Committee of the Faculty of Medical Science, University of Kragujevac (decision number: 01-15731; 29 December 2021), and all procedures complied with the principles outlined in the Declaration of Helsinki [45].
The characteristics of the two groups/samples are detailed in Table 1. Players in the TR group had a mean age of 23.38 ± 3.78 years, body height of 183.31 ± 5.64 cm, and body mass of 78.60 ± 7.33 kg. Players in the MR group were 22.96 ± 3.78 years old, with an average height of 181.92 ± 6.55 cm and weight of 76.12 ± 6.57 kg.

2.2. Procedures

All testing procedures were conducted during March 2022, within the competitive season of the Serbian Super League. Laboratory assessments were performed under standardized environmental conditions (temperature: 20–23 °C; relative humidity: 55–60%) to ensure consistency across participants. A progressive, multistage treadmill protocol was administered to assess maximal aerobic capacity. Following a standardized warm-up, participants began the test by running at 5 km/h for 3 min. Speed and incline were subsequently increased at predefined intervals. The test was finished when at least two of the following criteria were met: a VO2 plateau (≤2 mL/kg/min increase despite increased workload), achievement of maximal heart rate (HRmax), a respiratory exchange ratio (RER) greater than 1.2, or volitional exhaustion. All tests were conducted between 11:00 a.m. and 3:00 p.m. to control for diurnal variation. The participants were tested in two waves, on Wednesdays and Thursdays, with a minimum of 72 h of recovery after the previous official match and no interference with preparations for the upcoming match. The same procedures were repeated the following week for the remaining athletes, resulting in a total testing period of four days across two weeks. A trained team of three researchers administered all assessments, following standardized protocols to ensure measurement consistency and participant safety.

2.3. Anthropometric Characteristics

Anthropometric measurements were conducted following the standards set by the International Biological Program [46]. Body weight was measured using a Tefal 6010 scale (Tefal, Rumilly, Haute-Savoie, France), with an accuracy of 0.1 kg. Height was assessed using an anthropometer (GPM, Zurich, Switzerland), with the results taken to the nearest 0.1 cm.

2.4. Cardiorespiratory Parameters

For this study, a maximal multistage progressive treadmill test was conducted using the Technogym Run Exciting 9000 (Technogym, Fairfield, NJ, USA). After positioning the participants, a mask (Hans Rudolph, Kansas City, MO, USA) was securely fitted with elastic straps to prevent air leakage, allowing for direct VO2max measurement using Cosmed’s FitMate Med (Cosmed, Rome, Italy). Following the mask placement, a heart rate monitor (Polar Pro Team System, Kempele, Finland) was positioned around the chest, just below the nipples, and fastened. The monitor was placed on bare skin to ensure accurate and continuous heart rate measurements. Cardiovascular and respiratory data were recorded automatically every 15 s. During the test, the participants walked and ran at varying intensities and inclines, following a standardized stepwise continuous test protocol [47,48]. The variables were measured as in the previous study [33]. The directly measured variables during the test were maximum heart rate (HRmax), anaerobic threshold speed (V/AT), heart rate at the anaerobic threshold (HR AT), heart rate at the first minute of recovery (HR 1′), heart rate at the second minute of recovery (HR 2′), and maximum oxygen uptake (VO2max). Other cardiorespiratory parameters were calculated based on formulas: theoretical maximum heart rate (THRmax; THRmax = 220 − years) [49], achieved percentages of the load (%HRmax; %HRmax = HRmax/THRmax × 100), running efficiency (VO2max/v), cardiorespiratory efficiency (VO2max/HR), cardiovascular efficiency (HR AT/kg), percentage of cardiovascular efficiency (% HR AT/kg), percentage of recovery in the first minute (%Re 1′; %Re 1′ = 100 − HR 1′/HRmax × 100), and percentage of recovery in the second minute (%Re 2′; %Re 2′ = 100 − HR 2′/HRmax × 100). For clarity, all variables and their abbreviations are arranged in the order they will be used in the subsequent text (Table 2).

2.5. Lactate Parameters

To determine lactate thresholds, capillary blood lactate concentrations (measured in mmol/L) were recorded at the end of each stage of the stepwise test. Blood samples were collected from a hyperemic lobe using specialized test strips. Once a sample was taken, the lactate levels were immediately analyzed with a lactate analyzer (Lactate Scout, EKF SensLab, Leipzig, Germany). The sensitivity and accuracy of the lactate concentration measurement with the Lactate Scout analyzer were scientifically validated [50]. Using the data collected, the metabolic efficiency index was calculated, representing the ratio of blood lactate concentration at the 4th and 10th minute of recovery. Directly measured variables during the test included rest lactate (RL), lactate at 4 min (LA 4′), and lactate at 10 min (LA 10′). Calculated variables comprised the metabolic recovery index (Index LA; Index LA = LA 10′/LA 4′) and metabolic efficiency index (Index ME; Index ME = Index HR LT1/HR LT2, where LT1 and LT2 are lactate threshold 1 and lactate threshold 2). These parameters are presented in Table 2.

2.6. Statistics

Descriptive statistics, including means and standard deviations, were calculated for all variables. Between-group differences were assessed using independent samples t-tests. The effect size for each comparison was determined using Cohen’s d, with the following thresholds for interpretation: <0.20 = trivial, 0.20–0.49 = small, 0.50–0.79 = moderate, 0.80–1.29 = large, and ≥1.30 = very large [51]. Statistical significance was set at p < 0.05. All analyses were performed using IBM SPSS Statistics (v27.0, SPSS Inc., Chicago, IL, USA).

3. Results

A significant difference was identified in most parameters (Table 3). Although there was a difference in the THR max, which also influenced a significant difference in %HRmax (%), a more objective method demonstrated no difference in maximum heart rate, showing 192.79 ± 9.31 bpm compared to 191.15 ± 7.41 bpm between the groups.
%HRmax (%) indicates that the players from the top-ranked teams achieved lower values, 91.67 ± 3.75% compared to 96.48 ± 3.26% for the players from the mid-ranked teams.
The football players from better teams recorded lower heart rate values at the anaerobic threshold, HR AT (bpm) (162.79 ± 10.26 vs. 168.77 ± 7.28 bpm; p = 0.017), as well as in percentage terms, HR AT % (%) (84.90 ± 2.45% vs. 87.96 ± 3.14%; p = 0.000). Additionally, the TR players had a slightly higher speed at the anaerobic threshold, V AT (km/h), 17.38 ± 1.35 km/h compared to 16.73 ± 1.25 km/h, but no significant difference was found.
In VO2max parameters, the mid-ranked teams achieved significantly higher values, as follows: VO2max (ml/kg/min) (60.06 ± 3.29 mL/kg/min vs. 62.65 ± 4.48 mL/kg/min; p = 0.017), VO2max/v (score) (2.82 ± 0.15 vs. 3.03 ± 0.21; p = 0.001), and VO2max/HR (score) (0.31 ± 0.02 vs. 0.33 ± 0.02; p = 0.011).
Although there was no difference in the first-minute recovery between the groups, HR 1′ (bpm) (171.17 ± 13.50 bpm vs. 167.08 ± 11.45 bpm), and in percentages %Re 1′ (%) (12.98 ± 5.44% vs. 14.69 ± 4.87%), a significant difference was found in the second-minute recovery, HR 2′ (bpm) (116.45 ± 10.84 bpm vs. 142.96 ± 13.98 bpm; p = 0.001), which, in percentage terms, amounted to %Re 2′ (%) (66.62 ± 14.08% vs. 34.53 ± 9.13%; p = 0.001).
The resting lactate level of the football players was similar, RL (mmol/L) 2.40 ± 0.50 mmol/L vs. 2.21 ± 0.48 mmol/L. After 4 min, the lactate levels were comparable at 9.09 ± 1.82 mmol/L vs. 9.96 ± 1.57 mmol/L, as well as after 10 min (7.00 ± 1.67 mmol/L vs. 6.84 ± 0.87 mmol/L). There was no difference in the lactate index (Index La) between the groups. The only difference found was in the Index ME parameter, which was better in the TR players (p = 0.011).

4. Discussion

This study aimed to examine the differences between top-ranked and mid-ranked teams’ football players in cardiorespiratory and metabolic parameters. The main findings of the study are as follows: (i) The football players from better teams achieved significantly lower heart rate values at the anaerobic threshold (HR AT and HR AT%), as well as better performance in the second minute of recovery (HR 2′ and %Re 2′). (ii) In the VO2max parameters, the mid-ranked team players achieved significantly higher values, specifically in VO2max, VO2max/v, and VO2max/HR. (iii) There were no differences between the groups in Hrmax, V AT, HR 1′, or %Re 1′. (iv) In the lactate parameters, no differences were observed between the groups, except for the Index ME, which was more favorable in the better team.
Numerous studies have investigated the physiological profile of football players from various national leagues [4,11,37,52,53]. The average match intensity of elite-level football ranges between 76.6% and 90.1 ± 3.9% VO2max during a match [25]. In the Estonian Premium League, physiological comparisons revealed that players from higher-ranked teams had lower maximal heart rates (HRmax: 189.5 ± 5.6 bpm) than those from lower-ranked teams (192.2 ± 5.2 bpm). Similar trends were observed in the average heart rate values (146.6 ± 15.8 bpm vs. 155.0 ± 14.5 bpm) and the percentage of HRmax achieved during match play (77.4 ± 8.4% vs. 80.6 ± 6.5%), indicating enhanced cardiovascular efficiency among the top-performing teams [37]. This suggests that players from lower-ranked teams experience greater cardiovascular strain during matches, possibly due to inferior conditioning [8].
When comparing our cardiac parameter values, it was observed that the average HRmax values for both groups of our football players align with findings from other studies, with 191.3 bpm in Croatia (2019–2020 season) [54], 192.9 bpm in Belgium (2017–2019 seasons) [38], and 193 bpm in Greece (2019–2020 season) [55]. The average heart rate at the anaerobic threshold (HR AT) for both teams was 162.79 bpm for the stronger team and 168.77 bpm for the weaker team. The HR AT values of the weaker team correspond to the 169 bpm reported for Greek players (2019–2020 season) [55] but are lower than those observed in Belgian (178.2 bpm) (2017–2019 seasons) [38] and Croatian footballers (182.96 bpm) (2019–2020 season) [54]. These differences in HR AT values may be attributed to variations in methodology across studies.
Our resting heart rate (HR 1′) values were similar for both teams and slightly lower compared to Champions League football players (91% of HRmax) (2003–04 season) [56] and Scottish players (90% of HRmax) (2009–10 season) [57]. The other resting heart rate parameter (HR 2′) cannot be compared with recent studies, as no research has investigated this parameter to date.
The VO2max is considered the best single parameter for evaluating endurance performance and depends on age, height, weight, and gender, as well as the type of exercise (bicycle or treadmill). The main criterion for reaching VO2max is that the intake of oxygen is below the required performance, the formation of a plateau (“leveling off”) [20]. The determination of VO2max is reflected by reaching a plateau in VO2peak by maintaining oxygen consumption at the end stages of an incremental test under optimal exercise conditions [58,59], while stopping the test when reaching the plateau is considered the current limit of oxygen consumption, but not the maximal [60]. Numerous studies have emphasized the predictive value of an exercise treadmill test aspect, such as heart rate recovery or the base of a decrease in heart rate after a training test [61,62,63], heart rate at 1 or 2 min of recovery [63,64], determining the physiological load [65]. However, exercise testing should be completed within 12–15 min to avoid early muscle exhaustion [66].
The average VO2max values are 60.06 mL/kg/min and 62.65 mL/kg/min, which align with the recommendations of authors [13,67], who suggest that VO2max for elite football players should exceed 60 mL/kg/min to meet the demands of modern football. Our VO2max values are comparable to those of professional players in other countries, such as England (61.6 mL/kg/min) (1998–1999 season) [39], the United Kingdom (59.4 mL/kg/min) (2001–2004 seasons) [68], the Czech Republic (59.2 mL/kg/min) (2000–2001 seasons) [69], and Greece (58.8 mL/kg/min) (2019–2020 seasons) [55]. It was reported that low-ranked teams had lower VO2max than the top-ranked teams [4,52]. The significance of VO2max in football is evident from its association with team success in the Hungarian 1st Division Championship. Studies have shown that the top-ranked teams in the league also had the highest average VO2max values among their players, suggesting a clear link between aerobic fitness and competitive performance [52]. Another study found that the top-ranked club had a higher mean measured VO2max than another low-ranked club [70]. Significant differences in VO2max between the top team and the lowest-placed team in the Norwegian Professional Division have been reported. Observations have shown that players from a top-tier Norwegian international team exhibited significantly higher VO2max levels compared to those from a lower-ranked team within the same league (67.6 mL/kg/min vs. 59.9 mL/kg/min) [4]. Previous research has pointed to a positive relationship between VO2max and the rank position of the team in the elite football league. A study involving elite Danish football players found no significant difference in VO2max between regular starters and non-regular first-team members, suggesting that this physiological measure alone may not be a decisive factor for high-level performance in football [24,53]. However, it should also be added that numerous studies have reported a large variation in VO2max, which is relatively associated with the different positions of the football players within the team. The obtained results of the Danish professional footballers indicate that fullbacks and midfielders appeared to have the highest VO2max values, and goalkeepers and central defenders the lowest [11]. However, the results of the other studies indicated that the VO2max values of football players who competed at the same level of the league and played in different positions were close to each other [17,71]. In contrast, this study did not take into account the players’ positions on the field, which may also have had an impact on the results obtained.
The results emphasize the physiological differences between TR and MR football players based on the different demands on the body in professional football and the adaptations needed for those competing at the highest level. There were significant differences in the cardiorespiratory metrics between the TR and MR players. The TR players showed lower heart rate values at the anaerobic threshold (HR AT and HR AT%) and superior performance in the second minute of recovery (HR 2′ and %Re 2′). The results show that players from leading teams had better-developed aerobic and anaerobic energy systems, using energy more efficiently during the high-intensity efforts and recovering faster during the low ones. Adaptations such as these are critical for sustaining performance in match play involving rapid transition between energy systems [72,73]. Conversely, the MR players exhibited significantly higher VO2 max and related indices (VO2 max/v and VO2 max/HR). This may reflect a physiological adaptation to playing styles that rely heavily on endurance-based strategies, such as increased ball recovery and defensive responsibilities. Previous research has implied that less successful teams often perform more high-intensity running and cover greater distances, requiring robust aerobic systems to sustain performance levels [74,75,76]. The findings provide practical guidance for designing team training programs with strategies for teams and attending to player roles. Even the baseline features of cardiac capacity (HRmax, %Re 1′) were not significantly different between the groups, suggesting equivalent cardiac potential. However, the TR players’ superior recovery metrics and cardiovascular efficiency give them a competitive advantage. The key takeaways arise from this interplay between physiological capacity and tactical execution, in which elite football performance is defined [77,78,79]. The fact that TR players exhibited superior recovery and metabolic efficiency despite lower VO2max scores underscores the importance of integrated fitness attributes beyond pure aerobic capacity. These nuanced physiological adaptations are likely shaped by training specificity, tactical strategies, and overall team structure.
Metabolic parameters showed fewer differences between TR and MR players. Both groups exhibited similar lactate concentrations at rest and during recovery phases, except for the metabolic efficiency index (Index ME), which was significantly higher in TR players. This suggests that TR players are better equipped to optimize metabolic processes during high-intensity activities, allowing them to sustain performance while minimizing fatigue-inducing byproducts, such as lactate [80,81,82]. Consistent lactate levels across both groups indicate consistent anaerobic capacity within the league. Although TR players have a superior Index ME for MR players, their advanced physiological adaptations, such as enhanced lactate clearance and greater use of the anaerobic pathway, allow them to outperform MR players. These efficiencies are critical for maintaining high performance during competitive matches with significant metabolic demands [83,84].
The results emphasize the need for more tailor-made training interventions to maximize player performance. Although TR players recover and work more efficiently than other players, they can optimize their competitive edge through anaerobic thresholds and recovery strategies. For MR players, improving aerobic capacities and metabolic efficiency is crucial for closing the performance gap with more substantial teams. Integrating sport-specific conditioning, tactical drills, and recovery protocols into training programs will be vital for achieving these objectives. Individualized training regimens are likewise suggested [85,86]. For these reasons, the program for each player should be designed as follows: Coaches and sports scientists should design players’ programs based on the physiological profile of the player, the player’s position, and the team strategy. This personalized practice facilitates the identification of players’ strengths and enables a systematic focus on addressing their weaknesses, thereby contributing to the team’s overall success. Furthermore, the cross-sectional design does not permit longitudinal changes, such as seasonal adaptations or the effects of individual training programs to be determined. Further research should investigate a more comprehensive array of leagues and consider the evolution of such parameters over time (especially about the manner and sequence in which the specific training methodology and competitive conditions have been employed). Emerging technologies, such as wearable sensors and real-time monitoring systems, could enhance our understanding of players’ dynamic physiological responses during matches. In addition, understanding the interplay between physiological and psychological factors (e.g., mental resilience and decisions made under pressure) may also shed light on determinants of elite football performance.

Limitations and Future Discussion

While this study provides valuable insights, it has several limitations. First, due to its cross-sectional design, it cannot account for training effects or physiological changes over time. Second, the positional roles of players were not analyzed, although these may significantly affect VO2max and lactate-related parameters. Third, the study was conducted mid-season (March 2022), which may have influenced physiological status due to varying training loads and match exposure.
Future studies should include a sample of players from a larger number of teams and adopt longitudinal and positional specific designs, potentially integrating real-time tracking (GPS, inertial sensors) and match analytics to correlate laboratory findings with in-game performance. In our opinion, a multi-dimensional approach that includes psychological, tactical, and biomechanical data would further refine our understanding of performance determinants in professional football. Also, future research could incorporate lower-tier teams and explore the differences among top-, mid-, and lower-tier teams, which would provide a more comprehensive understanding of potential variations.
It is worth noting that, to date, only one other study has examined physiological predictors of match performance in Serbian elite football players [33], focusing on predictive modeling rather than group-based comparisons. This highlights the novelty and applied relevance of the present comparative approach.

5. Conclusions

The findings of this study show significant cardiorespiratory and metabolic physiological differences between TR and MR players of the Serbian Super League. Our study confirms that TR players display enhanced recovery and efficiency profiles, while MR players demonstrate stronger aerobic capacity. These physiological divergences suggest differing adaptations to match demands and training exposures. By incorporating individualized conditioning strategies based on such profiles, coaching staff can optimize team performance and reduce injury risk. The findings further reinforce the need to consider recovery metrics alongside VO2max in performance assessment.

Author Contributions

Conceptualization, R.R., D.M. and B.K.; methodology, N.P., V.P.A. and B.K.; software, D.M. and K.G.; validation, K.G., N.P. and B.K.; formal analysis, V.A.G. and K.G.; investigation, R.R., D.M. and B.K.; resources, R.R.; data curation, V.A.G. and V.P.A.; writing—original draft preparation, R.R., D.M., K.G. and B.K.; writing—review and editing, N.P., V.A.G. and V.P.A.; visualization, N.P. and V.P.A.; supervision, D.M. and B.K.; project administration, R.R., N.P. and V.A.G.; funding acquisition, K.G., V.A.G. and V.P.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

All procedures conducted in this study were in accordance with the Helsinki Declaration and approved by the Ethics Committee of the Faculty of Medical Sciences, University of Kragujevac (decision number: 01-15731; date: 29 December 2021).

Informed Consent Statement

Written informed consent has been obtained from the subjects to publish this paper.

Data Availability Statement

The data presented in this study are available in the article.

Acknowledgments

The authors would like to acknowledge the Serbian Ministry of Education, Science, and Technological Development for supporting this research. Additionally, the authors would like to sincerely thank the participating football teams, coaches, and players.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
TRTop-ranked team
MRMiddle-ranked team
HRmaxMaximum heart rate (bpm)
THRmaxTheoretical maximum heart rate (bpm)
V ATAnaerobic threshold speed (km/h)
%HRmaxAchieve % of the load on test (%)
HR ATHeart rate at the anaerobic threshold (bpm)
HR AT%Heart rate at the anaerobic threshold percentages (%)
HR AT/kgCardiovascular efficiency (score)
%HR AT/kgPercentage of cardiovascular efficiency (%)
VO2maxMaximum oxygen uptake (ml/kg/min)
VO2max/vRunning efficiency (score)
VO2max/HRCardiorespiratory efficiency (score)
HR 1′Heart rate at the first minute of recovery (bpm)
HR 2′Heart rate at the second minute of recovery (bpm)
%Re 1′Percentage of recovery in the first minute (%)
%Re 2′Percentage of recovery in the second minute (%)
RLRest lactate (mmol/L)
LA 4′Lactate at 4 min (mmol/L)
LA 10′Lactate at 10 min (mmol/L)
Index LAMetabolic recovery index (score)
Index MEMetabolic efficiency index (score)

References

  1. Ekblom, B. Applied physiology of soccer. Sports Med. 1986, 3, 50–60. [Google Scholar] [CrossRef] [PubMed]
  2. Matkovic, B.R.; Jankovic, S.; Heimer, S. Physiological profile of top Croatian soccer players. In Science and Football II; E&FN Spon: London, UK, 1993; pp. 37–39. [Google Scholar]
  3. Dolci, F.; Hart, N.H.; Kilding, A.; Chivers, P.; Piggott, B.; Spiteri, T. Movement economy in soccer: Current data and limitations. Sports 2018, 6, 124. [Google Scholar] [CrossRef] [PubMed]
  4. Wisloeff, U.; Helgerud, J.; Hoff, J. Strength and endurance of elite soccer players. Med. Sci. Sports Exerc. 1998, 30, 462–467. [Google Scholar] [CrossRef]
  5. Arnason, A.; Sigurdsson, S.B.; Gudmundsson, A.; Holme, I.; Engebretsen, L.; Bahr, R. Physical fitness, injuries, and team performance in soccer. Med. Sci. Sports Exerc. 2004, 36, 278–285. [Google Scholar] [CrossRef] [PubMed]
  6. Castellano, J.; Blanco-Villaseñor, A.; Alvarez, D. Contextual variables and time-motion analysis in soccer. Int. J. Sports Med. 2011, 32, 415–421. [Google Scholar] [CrossRef]
  7. Di Salvo, V.; Gregson, W.; Atkinson, G.; Tordoff, P.; Drust, B. Analysis of high intensity activity in Premier League soccer. Int. J. Sports Med. 2009, 30, 205–212. [Google Scholar] [CrossRef]
  8. Rampinini, E.; Coutts, A.J.; Castagna, C.; Sassi, R.; Impellizzeri, F.M. Variation in top level soccer match performance. Int. J. Sports Med. 2007, 28, 1018–1024. [Google Scholar] [CrossRef]
  9. Reilly, T. Energetics of high-intensity exercise (soccer) with particular reference to fatigue. J. Sports Sci. 1997, 15, 257–263. [Google Scholar] [CrossRef]
  10. Duarte, R.; Araújo, D.; Correia, V.; Davids, K. Sports teams as superorganisms: Implications of sociobiological models of behaviour for research and practice in team sports performance analysis. Sports Med. 2012, 42, 633–642. [Google Scholar] [CrossRef]
  11. Bangsbo, J.; Michalsik, L. Assessment of the physiological capacity of elite soccer players. In Science and Football IV; Reilly, T., Ed.; Routledge: London, UK, 2002; pp. 53–62. [Google Scholar]
  12. Bradley, P.S.; Di Mascio, M.; Peart, D.; Olsen, P.; Sheldon, B. High-intensity activity profiles of elite soccer players at different performance levels. J. Strength Cond. Res. 2010, 24, 2343–2351. [Google Scholar] [CrossRef]
  13. Almeida, A.M.D.; Santos Silva, P.R.; Pedrinelli, A.; Hernandez, A.J. Aerobic fitness in professional soccer players after anterior cruciate ligament reconstruction. PLoS ONE 2018, 13, e0194432. [Google Scholar] [CrossRef]
  14. Castagna, C.; Abt, G.; D’Ottavio, S. Physiological aspects of soccer refereeing performance and training. Sports Med. 2007, 37, 625–646. [Google Scholar] [CrossRef] [PubMed]
  15. Reilly, T.; Bangsbo, J.; Franks, A. Anthropometric and physiological predispositions for elite soccer. J. Sports Sci. 2000, 18, 669–683. [Google Scholar] [CrossRef] [PubMed]
  16. Tønnessen, E.; Hem, E.; Leirstein, S.; Haugen, T.; Seiler, S. Maximal aerobic power characteristics of male professional soccer players, 1989–2012. Int. J. Sports Physiol. Perform. 2013, 8, 323–329. [Google Scholar] [CrossRef] [PubMed]
  17. Aksoy, Ö.; Bozdoğan, T.K.; Soyal, M.; Beyaz, M.M. The examination of VO2max and anaerobic threshold values in elite soccer players by their positions. J. Phys. Educ. Sport 2022, 22, 2496–2503. [Google Scholar]
  18. Hoff, J.; Helgerud, J. Endurance and strength training for soccer players: Physiological considerations. Sports Med. 2004, 34, 165–180. [Google Scholar] [CrossRef]
  19. Bénézet, J.M.; Hasler, H. Youth Football; FIFA Education and Technical Development Department: Zurich, Switzerland, 2016; Available online: https://digitalhub.fifa.com/m/1b3da6976c9290aa/original/mxpozhvr2gjshmxrilpf-pdf.pdf (accessed on 15 April 2022).
  20. Löllgen, H.; Erdmann, E.; Gitt, A.K. Ergometrie. In Belastungsuntersuchungen in Klinik und Praxis [Ergometry. Stress Tests in Clinic and Practice]; Springer: Berlin/Heidelberg, Germany, 2010. [Google Scholar]
  21. Mader, A. Zur Beurteilung der sportartspezifischen Ausdauerleistungsfahigkeit [To assess sport-specific endurance performance]. Sportarzt Sportmed. 1976, 27, 80–88. [Google Scholar]
  22. Stegmann, H.; Kindermann, W.; Schnabel, A. Lactate kinetics and individual anaerobic threshold. Int. J. Sports Med. 1981, 2, 160–165. [Google Scholar] [CrossRef]
  23. Allen, W.K.; Seals, D.R.; Hurley, B.F.; Ehsani, A.A.; Hagberg, J.M. Lactate threshold and distance-running performance in young and older endurance athletes. J. Appl. Physiol. 1985, 58, 1281–1284. [Google Scholar] [CrossRef]
  24. Bangsbo, J. The physiology of soccer with special reference to intense intermittent exercise. Acta Physiol. Scand. Suppl. 1994, 619, 1–155. [Google Scholar]
  25. Stølen, T.; Chamari, K.; Castagna, C.; Wisløff, U. Physiology of soccer: An update. Sports Med. 2005, 35, 501–536. [Google Scholar] [CrossRef] [PubMed]
  26. Helgerud, J.; Engen, L.C.; Wisløff, U.; Hoff, J. Aerobic endurance training improves soccer performance. Med. Sci. Sports Exerc. 2001, 33, 1925–1931. [Google Scholar] [CrossRef]
  27. Bangsbo, J.; Nørregaard, L.; Thorsø, F. Activity profile of competition soccer. Can. J. Sport. Sci. 1991, 16, 110–116. [Google Scholar]
  28. Roi, G.S.; Sisca, G.; Perondi, F.; Diamante, A.; Nanni, G. Post competition blood lactate accumulation during a first league soccer season. J. Sports Sci. 2004, 22, 560. [Google Scholar]
  29. Krustrup, P.; Mohr, M.; Steensberg, A.; Bencke, J.; Kjær, M.; Bangsbo, J. Muscle and blood metabolites during a soccer game: Implications for sprint performance. Med. Sci. Sports Exerc. 2006, 38, 1165–1174. [Google Scholar] [CrossRef] [PubMed]
  30. Tomlin, D.L.; Wenger, H.A. The relationship between aerobic fitness and recovery from high intensity intermittent exercise. Sports Med. 2001, 31, 1–11. [Google Scholar] [CrossRef]
  31. MacRae, H.S.; Dennis, S.C.; Bosch, A.N.; Noakes, T.D. Effects of training on lactate production and removal during progressive exercise in humans. J. Appl. Physiol. 1992, 72, 1649–1656. [Google Scholar] [CrossRef]
  32. Jacobs, I. Blood lactate: Implications for training and sports performance. Sports Med. 1986, 3, 10–25. [Google Scholar] [CrossRef]
  33. Radaković, R.; Katanić, B.; Stanković, M.; Masanovic, B.; Fišer, S.Ž. The Impact of Cardiorespiratory and Metabolic Parameters on Match Running Performance (MRP) in National-Level Football Players: A Multiple Regression Analysis. Appl. Sci. 2024, 14, 3807. [Google Scholar] [CrossRef]
  34. Aquino, R.; Gonçalves, L.G.; Galgaro, M.; Maria, T.S.; Rostaiser, E.; Pastor, A.; Nobari, H.; Garcia, G.R.; Moraes-Neto, M.V.; Nakamura, F.Y. Match running performance in Brazilian professional soccer players: Comparisons between successful and unsuccessful teams. BMC Sports Sci. Med. Rehabil. 2021, 13, 93. [Google Scholar] [CrossRef]
  35. Bjelica, D.; Katanic, B.; Milosevic, Z.; Osmani, A.; Kukic, A.; Stankovic, M. Exploring the Anthropometric Profiles of Youth Footballers: Differences Between Players from Top and Bottom Teams in the Montenegrin First Cadet League. Sport. Mont. 2025, 23, 131–135. [Google Scholar] [CrossRef]
  36. Brito de Souza, D.; López-Del Campo, R.; Blanco-Pita, H.; Resta, R.; Del Coso, J. An extensive comparative analysis of successful and unsuccessful football teams in LaLiga. Front. Psychol. 2019, 10, 2566. [Google Scholar] [CrossRef] [PubMed]
  37. Misjuk, M.; Hurt, N.; Rannama, I. Soccer players training load during Estonian Premium League matches: Comparison of high and low ranking teams. J. Hum. Sport. Exerc. 2015, 10, S521–S525. [Google Scholar] [CrossRef]
  38. Colosio, A.L.; Lievens, M.; Pogliaghi, S.; Bourgois, J.G.; Boone, J. Heart rate-index estimates aerobic metabolism in professional soccer players. J. Sci. Med. Sport. 2020, 23, 1208–1214. [Google Scholar] [CrossRef]
  39. Clark, N.A.; Edwards, A.M.; Morton, R.H.; Butterly, R.J. Season-to-season variations of physiological fitness within a squad of professional male soccer players. J. Sports Sci. Med. 2008, 7, 157. [Google Scholar]
  40. Bradley, P.S.; Sheldon, W.; Wooster, B.; Olsen, P.; Boanas, P.; Krustrup, P. High-intensity running in English FA Premier League soccer matches. J. Sports Sci. 2009, 27, 159–168. [Google Scholar] [CrossRef]
  41. Ingebrigtsen, J.; Dalen, T.; Hjelde, G.H.; Drust, B.; Wisloff, U. Acceleration and sprint profiles of a professional elite football team in match play. Eur. J. Sport. Sci. 2015, 15, 101–110. [Google Scholar] [CrossRef]
  42. Bibić, E.; Barišić, V.; Katanić, B.; Chernozub, A.; Trajković, N. Acute Effects of Foam Rolling and Stretching on Physical Performance and Self-Perceived Fatigue in Young Football Players. J. FunctMorpho. Kinesiol. 2025, 10, 36. [Google Scholar] [CrossRef]
  43. Gorostiaga, E.M.; Llodio, I.; Ibáñez, J.; Granados, C.; Navarro, I.; Ruesta, M.; Izquierdo, M. Differences in physical fitness among indoor and outdoor elite male soccer players. Eur. J. Appl. Physiol. 2009, 106, 483–491. [Google Scholar] [CrossRef]
  44. Mendez-Villanueva, A.; Buchheit, M.; Kuitunen, S.; Douglas, A.; Peltola, E.S.A.; Bourdon, P. Age-related differences in acceleration, maximum running speed, and repeated-sprint performance in young soccer players. J. Sports Sci. 2011, 29, 477–484. [Google Scholar] [CrossRef]
  45. World Medical Association. World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA 2013, 310, 2191–2194. [Google Scholar] [CrossRef] [PubMed]
  46. Eston, R.G.; Reilly, T. Kinanthropometry and Exercise Physiology Laboratory Manual: Exercise Physiology; Taylor & Francis: Abingdon, UK, 2009; Volume 2. [Google Scholar]
  47. Kolic, L. Utjecaj Protokola Testa Hodanja s Progresivnim Opterecenjem na Pokretnom Sagu na Pokazatelje Energetskih Kapaciteta [The Influence of the Walking Test Protocol with Progressive Load on a Moving Carpet on Indicators of Energy Capacities]. Ph.D. Thesis, Faculty of Kinesiology, University of Zagreb, Zagreb, Croatia, 2020. [Google Scholar]
  48. Todorov, I. Efekti Specifičnog Treninga na Kardiorespiratornu Izdržljivost i Kontraktilni Potencijal Mišića Džudista [Effects of Specific Training on Cardiorespiratory Endurance and Muscle Contractile Potential of Judoka]. Ph.D. Thesis, University of Nis, Nis, Serbia, 2014. [Google Scholar]
  49. Fox, S.M., III; Naughton, J.P.; Haskell, W.L. Physical activity and the prevention of coronary heart disease. Ann. Clin. Res. 1971, 3, 404–432. [Google Scholar] [CrossRef]
  50. Von Duvillard, S.P.; Pokan, R.; Hofmann, P.; Wonisch, M.; Smekal, G.; Alkhatib, A.; Leithauser, R. Comparing blood lactate values of three different handheld lactate analyzers to YSI 1500 lactate analyzer. Med. Sci. Sports Exerc. 2005, 37, S25. [Google Scholar]
  51. Cohen, D. Statistical Power Analysis for the Behaviors Science, 2nd ed.; Lawrence Erlbaum Associates: Mahwah, NJ, USA, 1988. [Google Scholar]
  52. Apor, P. Successful formulae for fitness training. In Science and Football (Routledge Revivals); Routledge: London, UK, 2013; pp. 95–107. [Google Scholar]
  53. Bangsbo, J. Fitness Training in Football—A Scientific Approach; HO and Storm: Bagsværd, Denmark, 1994. [Google Scholar]
  54. Modric, T.; Versic, S.; Sekulic, D. Does aerobic performance define match running performance among professional soccer players? A position-specific analysis. Res. Sports Med. 2021, 29, 336–348. [Google Scholar] [CrossRef] [PubMed]
  55. Metaxas, T.I. Match running performance of elite soccer players: VO2max and players position influences. J. Strength. Cond. Res. 2021, 35, 162–168. [Google Scholar] [CrossRef] [PubMed]
  56. Sassi, R.; Reilly, T.; Impellizzeri, F. A comparison of small-side games and interval training in elite professional soccer players. In Science and Football V; Oxon: Routledge, UK, 2005; pp. 352–354. [Google Scholar]
  57. Owen, A.L.; Wong, D.P.; McKenna, M.; Dellal, A. Heart rate responses and technical comparison between small-vs. large-sided games in elite professional soccer. J. Strength Cond. Res. 2011, 25, 2104–2110. [Google Scholar] [CrossRef]
  58. Day, J.R.; Rossiter, H.B.; Coats, E.M.; Skasick, A.; Whipp, B.J. The maximally attainable VO2 during exercise in humans: The peak vs. maximum issue. J. Appl. Physiol. 2003, 95, 1901–1907. [Google Scholar] [CrossRef]
  59. Poole, D.C.; Jones, A.M. Measurement of the maximum oxygen uptake VO2max: VO2peak is no longer acceptable. J. Appl. Physiol. 2017, 122, 997–1002. [Google Scholar] [CrossRef]
  60. Aspenes, S.T.; Nilsen, T.I.L.; Skaug, E.A.; Bertheussen, G.F.; Ellingsen, Ø.; Vatten, L.; Wisløff, U. Peak oxygen uptake and cardiovascular risk factors in 4631 healthy women and men. Med. Sci. Sports Exerc. 2011, 43, 1465–1473. [Google Scholar] [CrossRef]
  61. Cole, C.R.; Blackstone, E.H.; Pashkow, F.J.; Snader, C.E.; Lauerm, M.S. Heart-rate recovery immediately after exercise as a predictor of mortality. N. Engl. J. Med. 1999, 341, 1351–1357. [Google Scholar] [CrossRef]
  62. Cole, C.R.; Foody, J.M.; Blackstone, E.H.; Lauer, M.S. Heart rate recovery after submaximal exercise testing as a predictor of mortality in a cardiovascularly healthy cohort. Ann. Intern. Med. 2000, 132, 552–555. [Google Scholar] [CrossRef] [PubMed]
  63. Nishime, E.O.; Cole, C.R.; Blackstone, E.H.; Pashkow, F.J.; Lauer, M.S. Heart rate recovery and treadmill exercise score as predictors of mortality in patients referred for exercise ECG. JAMA 2000, 284, 1392–1398. [Google Scholar] [CrossRef]
  64. Shetler, K.; Marcus, R.; Froelicher, V.F.; Vora, S.; Kalisetti, D.; Prakash, M.; Do, D.; Myers, J. Heart rate recovery: Validation and methodologic issues. J. Am. CollCardiol. 2001, 38, 1980–1987. [Google Scholar] [CrossRef]
  65. Esposito, F.; Impellizzeri, F.M.; Margonato, V.; Vanni, R.; Pizzini, G.; Veicsteinas, A. Validity of heart rate as an indicator of aerobic demand during soccer activities in amateur soccer players. Eur. J. Appl. Physiol. 2004, 93, 167–172. [Google Scholar] [CrossRef]
  66. Niederseer, D.; Löllgen, H. Medical evaluation of athletes: Exercise testing. In Textbook of Sports and Exercise Cardiology; Springer: Cham, Switzerland, 2020; pp. 181–201. [Google Scholar]
  67. Reilly, T.; Williams, A.M.; Nevill, A.; Franks, A. A multidisciplinary approach to talent identification in soccer. J. Sports Sci. 2000, 18, 695–702. [Google Scholar] [CrossRef] [PubMed]
  68. Strudwick, A.; Doran, T.R.D. Anthropometric and fitness profiles of elite players in two football codes. J. Sports Med. Phys. Fitness. 2002, 42, 239. [Google Scholar] [PubMed]
  69. Botek, M.; Krejčí, J.; McKune, A.J.; Klimešová, I. Somatic, endurance performance and heart rate variability profiles of professional soccer players grouped according to age. J. Hum. Kinet. 2016, 54, 65. [Google Scholar] [CrossRef]
  70. Aziz, A.R.; Newton, M.J.; Kinugasa, T.; Chuan, T.K. Relationship between aerobic fitness and league positional ranking of clubs in a professional soccer league over three competitive seasons. Footb. Sci. 2007, 4, 9–18. [Google Scholar]
  71. Cihan, H.; İbrahim, C.A.N.; Seyis, M. Comparison of recovering times and aerobic capacity according to playing positions of elite football players. Beden Egitim Spor Bilim. Derg. 2012, 6, 1–8. [Google Scholar]
  72. Alves, I.S.; Kalva-Filho, C.A.; Aquino, R.; Travitzki, L.; Tosim, A.; Papoti, M.; Morato, M.P. Relationships between aerobic and anaerobic parameters with game technical performance in elite goalball athletes. Front. Physiol. 2018, 9, 1636. [Google Scholar] [CrossRef]
  73. Archacki, D.; Zieliński, J.; Pospieszna, B.; Włodarczyk, M.; Kusy, K. The contribution of energy systems during 15-second sprint exercise in athletes of different sports specializations. PeerJ 2024, 12, e17863. [Google Scholar] [CrossRef] [PubMed]
  74. Psarras, I.I.; Bogdanis, G.C. Physiological responses and performance during an integrated high-intensity interval aerobic and power training protocol. Sports 2024, 12, 76. [Google Scholar] [CrossRef] [PubMed]
  75. Stankovic, M.; Djordjevic, D.; Trajkovic, N.; Milanovic, Z. Effects of High-Intensity Interval Training (HIIT) on Physical Performance in Female Team Sports: A Systematic Review. Sports Med. Open 2023, 9, 78. [Google Scholar] [CrossRef]
  76. Wang, Z.; Wang, J. The effects of high-intensity interval training versus moderate-intensity continuous training on athletes’ aerobic endurance performance parameters. Eur. J. Appl. Physiol. 2024, 124, 2235–2249. [Google Scholar] [CrossRef]
  77. Bangsbo, J.; Mohr, M.; Krustrup, P. Physical and metabolic demands of training and match-play in the elite football player. J. Sports Sci. 2006, 24, 665–674. [Google Scholar] [CrossRef]
  78. Rein, R.; Memmert, D. Big data and tactical analysis in elite soccer: Future challenges and opportunities for sports science. SpringerPlus 2016, 5, 1410. [Google Scholar] [CrossRef]
  79. Reinhardt, L.; Schulze, S.; Kurz, E.; Schwesig, R. An Investigation into the Relationship between Heart Rate Recovery in Small-Sided Games and Endurance Performance in Male, Semi-professional Soccer Players. Sports Med. Open 2020, 6, 43. [Google Scholar] [CrossRef]
  80. Chatel, B.; Bret, C.; Edouard, P.; Oullion, R.; Freund, H.; Messonnier, L.A. Lactate recovery kinetics in response to high-intensity exercises. Eur. J. Appl. Physiol. 2016, 116, 1455–1465. [Google Scholar] [CrossRef] [PubMed]
  81. Hu, J.; Cai, M.; Shang, Q.; Li, Z.; Feng, Y.; Liu, B.; Xue, X.; Lou, S. Elevated lactate by high-intensity interval training regulates the hippocampal BDNF expression and the mitochondrial quality control system. Front. Physiol. 2021, 12, 629914. [Google Scholar] [CrossRef]
  82. Wiewelhove, T.; Schneider, C.; Schmidt, A.; Döweling, A.; Meyer, T.; Kellmann, M.; Pfeiffer, M.; Ferrauti, A. Active Recovery After High-Intensity Interval-Training Does Not Attenuate Training Adaptation. Front. Physiol. 2018, 9, 362190. [Google Scholar] [CrossRef]
  83. Hinojosa, J.N.; Hearon, C.M.; Kowalsky, R.J. Blood lactate response to active recovery in athletes vs. non-athletes. Sports Sci. Health 2021, 17, 699–705. [Google Scholar] [CrossRef]
  84. Sengoku, Y.; Shinno, A.; Kim, J.; Homoto, K.; Nakazono, Y.; Tsunokawa, T.; Hirai, N.; Nobue, A.; Ishikawa, M. The relationship between maximal lactate accumulation rate and sprint performance parameters in male competitive swimmers. Front. Sports Act. Living 2024, 6, 1483659. [Google Scholar] [CrossRef] [PubMed]
  85. Arslanoglu, C.; Celgin, G.S.; Arslanoglu, E.; Demirci, N.; Karakas, F.; Dogan, E.; Cakaloglu, E.; Sahin, F.N.; Kucuk, H. An effective method of aerobic capacity development: Combined training with maximal aerobic speed and small-sided games for amateur football players. Appl. Sci. 2024, 14, 9134. [Google Scholar] [CrossRef]
  86. Ruddock, A.; James, L.; French, D.; Rogerson, D.; Driller, M.; Hembrough, D. High-Intensity Conditioning for Combat Athletes: Practical Recommendations. Appl. Sci. 2021, 11, 10658. [Google Scholar] [CrossRef]
Table 1. Description of the top- and mid-ranked teams’ football players.
Table 1. Description of the top- and mid-ranked teams’ football players.
VariablesTop-Ranked Teams’ PlayersMid-Ranked Teams’ Players
n2926
Age23.38 ± 3.3622.96 ± 3.78
Body height (cm)183.31 ± 5.64181.92 ± 6.55
Body mass (kg)78.60 ± 7.3376.12 ± 6.57
Systolic blood pressure119.66 ± 11.80119.23 ± 6.74
Diastolic blood pressure73.97 ± 8.0673.08 ± 6.64
Table 2. Cardiovascular and metabolic variables with their abbreviations.
Table 2. Cardiovascular and metabolic variables with their abbreviations.
No.VariableAbbreviation
1.Maximum heart rate (bpm)HRmax
2.Theoretical maximum heart rate (bpm)THRmax
3.Anaerobic threshold speed (km/h)V AT
4.Achieve % of the load on test (%) %HRmax
5.Heart rate at the anaerobic threshold (bpm)HR AT
6.Heart rate at the anaerobic threshold percentages (%)HR AT%
7.Cardiovascular efficiency (score) HR AT/kg
8.Percentage of cardiovascular efficiency (%)%HR AT/kg
9.Maximum oxygen uptake (ml/kg/min)VO2max
10.Running efficiency (score)VO2max/v
11.Cardiorespiratory efficiency (score)VO2max/HR
12.Heart rate at the first minute of recovery (bpm)HR 1′
13.Heart rate at the second minute of recovery (bpm)HR 2′
14.Percentage of recovery in the first minute (%)%Re 1′
15.Percentage of recovery in the second minute (%)%Re 2′
16.Rest lactate (mmol/L)RL
17.Lactate at 4 min (mmol/L)LA 4′
18.Lactate at 10 min (mmol/L)LA 10′
19.Metabolic recovery index (score)Index LA
20.Metabolic efficiency index (score)Index ME
Table 3. Differences between football players from top- and mid- ranked teams (t-test).
Table 3. Differences between football players from top- and mid- ranked teams (t-test).
VariablesTop-Ranked Team PlayersMid-Ranked Team Playersp-ValueCohen’s d
HRmax (bpm)192.79 ± 9.31191.15 ± 7.410.4770.195
THRmax (bpm)209.86 ± 4.74198.35 ± 3.520.000 **2.758
V AT (km/h)17.38 ± 1.3516.73 ± 1.250.0710.499
%HRmax (%)91.67 ± 3.7596.48 ± 3.260.000 **1.369
HR AT (bpm)162.79 ± 10.26168.77 ± 7.280.017 *0.672
HR AT % (%)84.90 ± 2.4587.96 ± 3.140.000 **1.087
HR AT/kg (score)9.39 ± 0.5610.06 ± 0.740.000 **1.009
% HR AT/kg (%)4.91 ± 0.345.25 ± 0.410.001 **0.902
VO2max (ml/kg/min)60.06 ± 3.2962.65 ± 4.480.017 *0.660
VO2max/v (score)2.82 ± 0.153.03 ± 0.210.000 **1.190
VO2max/HR (score)0.31 ± 0.020.33 ± 0.020.011 *0.709
HR 1′ (bpm)171.17 ± 13.50167.08 ± 11.450.2330.327
HR 2′ (bpm)116.45 ± 10.84142.96 ± 13.980.000 **0.119
%Re 1′ (%)12.98 ± 5.4414.69 ± 4.870.2260.332
%Re 2′ (%)66.62 ± 14.0834.53 ± 9.130.000 **0.705
RL (mmol/L)2.40 ± 0.502.21 ± 0.480.1520.393
LA 4′ (mmol/L)9.09 ± 1.829.96 ± 1.570.0640.513
LA 10′ (mmol/L)7.00 ± 1.676.84 ± 0.870.6530.124
Index LA (score)35.74 ± 40.9047.29 ± 28.360.2340.328
Index ME (score)2.42 ± 0.452.13 ± 0.350.011 *0.713
Note: Mean ± standard deviation; p—statistical significance; Cohen’s d—value of effect size; *—statistically significant result between the pre- and post-tests, p < 0.05; **—statistically significant result between the pre- and post-tests, p < 0.01.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Radakovic, R.; Martinovic, D.; Katanic, B.; Govindasamy, K.; Prvulovic, N.; Geantă, V.A.; Ardelean, V.P. Physiological Differences in Cardiorespiratory and Metabolic Parameters Between Football Players from Top- and Mid-Ranked Teams in the Serbian Super League. Appl. Sci. 2025, 15, 6685. https://doi.org/10.3390/app15126685

AMA Style

Radakovic R, Martinovic D, Katanic B, Govindasamy K, Prvulovic N, Geantă VA, Ardelean VP. Physiological Differences in Cardiorespiratory and Metabolic Parameters Between Football Players from Top- and Mid-Ranked Teams in the Serbian Super League. Applied Sciences. 2025; 15(12):6685. https://doi.org/10.3390/app15126685

Chicago/Turabian Style

Radakovic, Radivoje, Dejan Martinovic, Borko Katanic, Karuppasamy Govindasamy, Nikola Prvulovic, Vlad Adrian Geantă, and Viorel Petru Ardelean. 2025. "Physiological Differences in Cardiorespiratory and Metabolic Parameters Between Football Players from Top- and Mid-Ranked Teams in the Serbian Super League" Applied Sciences 15, no. 12: 6685. https://doi.org/10.3390/app15126685

APA Style

Radakovic, R., Martinovic, D., Katanic, B., Govindasamy, K., Prvulovic, N., Geantă, V. A., & Ardelean, V. P. (2025). Physiological Differences in Cardiorespiratory and Metabolic Parameters Between Football Players from Top- and Mid-Ranked Teams in the Serbian Super League. Applied Sciences, 15(12), 6685. https://doi.org/10.3390/app15126685

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop