{"id":6242,"date":"2019-01-17T06:30:05","date_gmt":"2019-01-17T12:30:05","guid":{"rendered":"http:\/\/thesportjournal.org\/?p=6242"},"modified":"2019-01-10T14:36:51","modified_gmt":"2019-01-10T20:36:51","slug":"study-on-professional-football-players-factors-in-recovery-and-preparation-and-performance-markers-during-scheduled-training-session","status":"publish","type":"post","link":"https:\/\/thesportjournal.org\/article\/study-on-professional-football-players-factors-in-recovery-and-preparation-and-performance-markers-during-scheduled-training-session\/","title":{"rendered":"Study on professional football players – factors in recovery and preparation and performance markers during scheduled training session"},"content":{"rendered":"\n

Authors:<\/em>Tatyana Dzimbova, Hristo Nikolov,\nRadoslav Mavrevski, Stefan Kapralov<\/strong><\/p>\n\n\n\n

Corresponding Author:<\/em>
Assoc. prof. Tatyana Dzimbova, PhD
66 Ivan Michailov Str.
Blagoevgrad, 2700 Bulgaria
tania_dzimbova@abv.bg
+359898939285<\/p>\n\n\n\n

Study on\nprofessional football players – factors in recovery and preparation and\nperformance markers during scheduled training session<\/strong><\/h3>\n\n\n\n

ABSTRACT<\/strong><\/p>\n\n\n\n

Purpose.<\/strong> The purpose of the present study is to estimate if the\nathletes can satisfy their energy needs by diet, if they are well hydrated before training, and if the training is\neffective.<\/p>\n\n\n\n

Methods.<\/strong> Ten players of the football team in the B professional\nleague participated in the study (age 23.44 \u00b1 5.98 years,\nweight 70.64 \u00b1 4.57 kg, height 176.4 \u00b1 7.35 cm; \u00b1SD). Their body composition\nwas analyzed with the Body Composition Analyzer IoI 353 and they completed food\nquestionnaires. Blood lactate concentrations were determined using the\nbiochemical analyzer BIOSEN – C Line, EKF Diagnostic. The heart rates of the\nsubjects are recorded using the activePULS, MEDION AG. Data was processed using\nSPSS and Graphpad Prism software.<\/p>\n\n\n\n

Results<\/strong>. According to the data obtained from the food\nquestionnaires all subjects received the necessary amount of energy to fully\nmeet their energy needs. From the multiple linear regression, it is seen that\nthe highest value has the standardized coefficient in front of the carbohydrate\nintake which means that it has the greatest influence (about 65%) on total\nenergy intake. The heart rates of participants in the study range from 78 to\n90% of the predicted maximum, i.e., high intensity. Differences in blood\nlactate concentration before and after exercise are significant, evidence of\neffective performance on training.<\/p>\n\n\n\n

Conclusions.<\/strong> We can\nconclude that according to the nutrition questionnaire the athletes received a\nsufficient amount of macronutrients and sufficient amount of energy for their\ntraining needs. The change in blood lactate concentrations and heart rate\nduring training is indicative of the responsible attitude of the players, and\ntherefore the target endurance is most likely to be achieved.<\/p>\n\n\n\n

Applications in Sport<\/strong>. Reported methods could be a useful\ntool for coaches to track the recovery and preparation of the athletes in\nseason and to evaluate their performance during a scheduled training session.<\/strong><\/p>\n\n\n\n\n\n\n\n

Keywords:<\/strong> football, food questionnaire, body composition analysis, blood lactate concentration, heart rate, training<\/p>\n\n\n\n

INTRODUCTION<\/strong><\/p>\n\n\n\n

Intensive training is a daily routine for elite athletes and\nis aimed at improving performance at a competition. Optimizing performance\nrequires a balance between training and recovery. The diet is particularly\nimportant for supplying the body with the necessary nutrients for its\nday-to-day activities. For athletes, this is all the more important, as\nintensive training requires higher amounts of energy from food. In Bulgaria, the\nathletes themselves or with the help of the coach determine their diet, uses\nvarious supplements and nevertheless cannot meet their energy needs. Another\nimportant issue is the athlete’s hydration. Especially during the summer\nmonths, when ambient temperatures are around and above 30\u00b0C, it is important\nfor athletes to recover water losses during daily intensive outdoor training.\nFor an athlete to cope with the challenges of the upcoming training session, it\nis necessary to fully recover from the previous, have sufficient energy\nreserves and be well hydrated. <\/p>\n\n\n\n

Several parameters are tracked during the training and we\nhave focused on heart rate (HR) and blood lactate concentrations (BLC) as\nbiomarkers widely used in elite athletes’ training to determine the\neffectiveness of the training. Maintaining a balance between heart rate and\nheart rate increase in response to growing energy needs, is crucial for a\nperson to maintain their workout. This physiological parameter is proposed as a\ngood marker for determining exercise intensity and is an easy method for\nobserving training by athletes and coaches (3).<\/p>\n\n\n\n

Blood lactate concentration is one of the most commonly\nmeasured parameters during an athletes’ performance testing. While elevated\nlevels of lactate in the blood may be indicative of ischemia or hypoxia, it may\nbe a “normal” physiological response to the athlete’s effort. In\nresponse to a maximum effort of 30-120 seconds, peak blood lactate\nconcentrations of 15-25 mM can be observed. In response to the progressive,\nincreasing load, the lactate concentration increases gradually at the beginning\nand then faster when the load becomes more intensive. The operating rate above\nwhich blood lactate concentration increases exponentially, the lactate\nthreshold is a better prediction parameter than VO2max<\/sub> and is a\nbetter indicator of exercise intensity than heart rate; thus the lactate\nthreshold is useful in determining the intensity of training (4). The combination\nof these two parameters – heart rate and blood lactate concentration – can be\nan excellent tool for tracking and controlling exercise stress (5-7). The\nobjectives of this study are to determine:<\/p>\n\n\n\n

  • Whether\nathletes are sufficiently recovered before training, especially hydration and\nenergy needs are being met.<\/li>
  • Whether\nthe training is effective enough to enable the athlete to train the appropriate\nskills  <\/li>
  • How\nbiochemical and physiological tests can be used for such assessment.<\/li><\/ul>\n\n\n\n

    To meet these goals, several specific\ntasks need to be implemented:<\/p>\n\n\n\n

    • Measuring\nanthropometric indicators and body composition using an impedance analyzer,\nanalyzing all available information obtained from the analyzer;<\/li>
    • Conduct\na nutrition study with a special questionnaire assessing the total energy value\nof the athlete’s diet and the amounts of the individual macronutrients –\ncarbohydrates, proteins and fats;<\/li>
    • Measuring\nthe blood lactate concentration before and immediately after workout to\ndetermine the difference that will provide information on the intensity of\ntraining;<\/li>
    • Measuring\nthe heart rate of the athletes during a training session, specifying the\nminimum and maximum pulse frequencies, and the average pulse frequency for the\ntraining.<\/li>
    • Determine\nany correlations between the measured parameters in order to find certain\ndependencies that will serve as a starting point for the subsequent planning of\neffective coaching strategies.<\/li><\/ul>\n\n\n\n

      METHODOLOGY OF THE\nSTUDY<\/strong><\/p>\n\n\n\n

      Subjects<\/em><\/p>\n\n\n\n

      Ten main players of the football team of the B professional\nleague of Bulgaria participate in the study, with the exception of the\ngoalkeepers, as their training is different (age 23.44 \u00b1 5.98 years, weight\n70.64 \u00b1 4.57 kg, height 176.4 \u00b1 7.35 cm; \u00b1SD). The study was conducted in\nmid-August 2018 during the active competition season. On that day, football\nplayers had a scheduled training session in the afternoon (at 6:00 pm). Anthropometric\nmeasurements were carried out in the morning of the same day (9:00 a,m.) at the\nCenter for functional research in sports and kinesiotherapy – SWU “Neofit\nRilski” in Blagoevgrad. Prior to the testing, participants were asked to\nrefrain from physical exercise, food, and fluid intake. Each participant in the\nstudy signed an informed consent form and the study was approved by the South-West\nUniversity \u201cNeofit Rilski\u201d Research Ethics Committee.<\/p>\n\n\n\n

      Determination of body composition<\/em><\/p>\n\n\n\n

      Determination of body composition was performed using the Body\nComposition Analyzer, model IoI 353. The device presents not only analyzed\nresults for body composition but also energy expenditure. The participants of\nthe study were dressed with clothes as light as possible and they took off\nsocks before the measurement. From these results we used the Body Mass Index (BMI),\nTotal Body Water (TBW), Basal Metabolite Rate (BMR) and Total Energy Expenditure\n(TEE). TBW consists of intracellular and extracellular water. In healthy\nadults, body water is 45-65% of body weight, although it varies between\nindividuals. This indicator may serve as an indication for the athlete’s body\nhydration. BMR are the calories needed to maintain vital functions of the human\nbody at rest, such as heartbeat, neural transmissions, body temperature\nregulation, and so on. BMR is proportional to Soft Lean Mass (SLM), since fat is a source of\nenergy, and SLM consumes calories. So, even if the weight is the same for two\npeople, the one who has a high value of SLM shows a larger BMR. TEE (total\nenergy expenditure) is the sum of the basal metabolism and calories required\nfor daily activity and is generally calculated by multiplying BMR with PAL (Physical\nActivity Level). In our case, this indicator does not include the energy needed\nto conduct a training session. This energy can be calculated for each player\nusing BMR and the relevant Metabolic Equivalent of Task (MET) (2).<\/p>\n\n\n\n

      Determination of the energy value of\nthe usual diet of the players<\/em><\/p>\n\n\n\n

      Determination of the energy value of the usual diet is done\nusing pre-prepared food questionnaires. Taru at el. (8) have published a simple\nquestionnaire, which we modified for the conditions in Bulgaria. Each person\nfills in a pre-encoded questionnaire that automatically calculates the total\namount of kilocalories that a person normally consumes, and respectively the amount\nof carbohydrates, proteins and fats commonly found on the player’s menu.<\/p>\n\n\n\n

      Training<\/em><\/p>\n\n\n\n

      The training session was a standard workout for speed\nendurance included in the players\u2019 training schedule. The duration is 90\nminutes. The training consists of three parts as follows:<\/p>\n\n\n\n

      Preparatory part – 20 minutes<\/p>\n\n\n\n

      1. Three laps evenly running;<\/p>\n\n\n\n

      2. Total-developing exercises;<\/p>\n\n\n\n

      3. Special-preparatory exercises;<\/p>\n\n\n\n

      4. Passing the ball between three or four in motion;<\/p>\n\n\n\n

      5. Passing the ball in pairs (with increasing and decreasing\ndistance).<\/p>\n\n\n\n

      Basic part<\/p>\n\n\n\n

      1. Special squares – three squares 10 x 10 m by six players\n(Figure 1a)<\/p>\n\n\n\n

      2. Special 20 x 20 m square – three teams of six players,\neach team consists of three players. (Figure 1b).<\/p>\n\n\n\n

      3. Bilateral game – tournament, three teams each against\neach.<\/p>\n\n\n\n

      Closing part<\/p>\n\n\n\n

      1. Light running;<\/p>\n\n\n\n

      2. Stretching.<\/p>\n\n\n\n

      Figure 1.<\/strong> Exercises from the main part of the training<\/p>\n\n\n\n

      \"Figure<\/figure>\n\n\n\n

      Determination of lactate\nconcentration in arterial blood<\/em><\/p>\n\n\n\n

      Blood lactate concentrations are determined by the\nbiochemical analyzer BIOSEN – C Line of the German company EKF Diagnostic.\nDetermination is based on electrochemical measurement with a chip sensor. The\nsample is aspirated and injected automatically. L-lactate, which is converted\nby enzyme immobilized on the chip sensor to pyruvate forms hydrogen peroxide.\nIt releases free electrons that generate an electrical current that is recorded\nby an electrode on the device. The resulting electrical signal is proportional\nto the pyruvate concentration in the sample. Samples are taken before the training\nand after the basic part of the training session.<\/p>\n\n\n\n

      Determination of heart rate during\nexercise<\/em><\/p>\n\n\n\n

      During exercise, the heart rates of the subjects are recorded\nusing the activePULS of the German company MEDION AG. The capabilities of the\napparatus are measurements in the range of 30-240 beats per minute. Each set of\nthe device is programmed in advance for the respective player. Programming\nincludes setting gender, age, height, weight. Players are instructed to put\ntheir watch in the Stopwatch mode before the start of the training, and at the\nend, they turned it off. Throughout the training, heart rate is measured and\nthe data was analyzed later in the laboratory. The device allows us to\ndetermine the minimum and maximum heart rate during exercise, and the average\nheart rate for the entire training.<\/p>\n\n\n\n

      Data processing<\/em><\/p>\n\n\n\n

      To model the TEI’s dependence on carbohydrate, fat, and protein\nintake, a multiple least-squares linear regression analysis was performed. To\ndetermine the degree of impact of the different factor variables, the\ncorresponding standardized regression coefficients were also calculated. The\nregression analysis is based on the statistical software package SPSS\nStatistics 20. GaphpadPrism was used for determining the correlations between\nthe measured BLC and HR.<\/p>\n\n\n\n

      RESULTS AND DISCUSSION<\/strong><\/p>\n\n\n\n

      A major\nproblem for Bulgaria is that there are no developments related to field\nbiochemical tests of athletes. This study is a part of a planned in-depth study\nof various biochemical parameters during exercise in various sports, and\npreliminary results for football players are presented here.<\/p>\n\n\n\n

      Players’\nanthropometric data was measured in the morning before the training and\npresented in Table 1. As can be seen from Table 1, the age, weight and height\nof the players varies, which is common to this type of sport. Various skills\nare needed in the different positions in the football game, so the body of the\nplayers is different.<\/p>\n\n\n\n

      Table 1.\nData of the participants in the study<\/p>\n\n\n\n

      \"Table<\/figure>\n\n\n\n

      As shown\nin Table 1,  all players are within the\nnormal range of the BMI score (18.5-25.4, SD \u00b1 1.01). The BMI is generally not\nused in trained athletes, as in sports where muscle mass is higher, and so this\nindicator can be misleading. Athletes with well-developed muscles usually fall\ninto the group of people with high body mass, even in some cases they are in\nthe obese category first and even second degree. Footballers are athletes with\na high lean body mass (LBM), where too much muscle is not an advantage, as the\nextra weight will be an obstacle for 90 minutes to running faster. Therefore,\nBMI of the subjects is a reliable and fair indicator of weight relative to\nheight but perhaps does not account for LBM.<\/p>\n\n\n\n

      From the\ndata obtained from IoI 353, we use total body water (TBW). Although it varies\nfrom person to person, from 36.6 to 48.6 kilograms, the tendency is that the\nmass of body water is at the upper limit and, in some cases, exceeds it\nslightly. This indicator shows, first, that players have enough muscle mass,\nwhich has a higher percentage of water compared to fat, and, on the other hand,\nthey are also well hydrated for training despite the intense training sessions\nand high ambient temperatures (temperature of the air at the time of the study\nis about 32\u00b0C).<\/p>\n\n\n\n

      The other\ntwo indicators we use from IoI 353 are basal metabolic rate (BMR) and total\nenergy expenditure (TEE). These two indicators serve as a starting point for\nour assessment of whether a person’s usual diet is able to meet their daily\nenergy needs and provide the energy needed to conduct the planned training\nsession. Together with the nutrition questionnaire, which gives information on\nthe total intake of energy from food and drink, the amount of macronutrients in\nthe food can be determined by analyzing the energy availability that is\nimportant for the health and performance of the athlete. Individual BMR and TEE\nvary considerably from person to person, because their age and body size are\ncrucial for their determination. Since the team consists of players of\ndifferent ages and sizes BMR varies from 1484 to 1820 kJ and TEE, respectively,\nfrom 2285 to 2803 kJ. The individual differences are presented in Figure 2:<\/p>\n\n\n\n

      Figure 2.\nIndividual BMR and TEE.<\/p>\n\n\n\n

      \"Figure<\/figure>\n\n\n\n

      The\nnutrition questionnaire makes it possible to calculate the total energy intake\nwith the food by the players and to estimate the amount of carbohydrates,\nproteins and fats they eat. From the analysis of the results of the\nquestionnaire (Table 2), the following conclusions can be drawn: The energy\ncosts during a training session calculated according to the Physical Activity\nCompendium (6) for each individual player are in the range of 371-425 kJ \/ 90\nminutes. The differences between total energy intake and TEE are within the\nrange 1068.71 – 2920.71 kJ, which is well above the energy requirements of the\ntraining. Consequently, according to the questionnaire, the players receive the\nnecessary amount of energy to fully meet their energy costs.<\/p>\n\n\n\n

      It is\nnoteworthy that the players include the most carbohydrates in their menu, with\nthe average ratio of macronutrients being 77\/10\/13 – carbohydrates \/ fats \/\nproteins. This diet provides enough energy to meet energy needs, as\ncarbohydrates are the most comfortable source of energy for the body. The\nrecommended intake of carbohydrates (1) in this type of physical activity is\n8-10 g \/ kg body weight, with only four of the studied group are taking less of\nthis amount. The recommended protein intake for this type of sport ranges from\n1.4-1.7 g \/ kg of weight, with all but two players consuming less than 0.88 g\nand 0.40 g \/ kg of weight respectively. Fat intake should be such as to meet\nenergy needs. Typically, the intake of fat is about 1 g \/ kg body weight, with\nall subjects receiving fewer fats below 1 g \/ kg body weight, as they receive\nthe energy they need from the large amounts of carbohydrates they consumed.<\/p>\n\n\n\n

      Of the\nsufficient amount of energy, as well as the fact that football players report\neating fruit and vegetables in meals, it can be concluded that their usual food\nsatisfies their micronutrient needs – vitamins and minerals. Another proof of\nthis is the mineral analyzer data, which is found in all norms and near the\nupper limit.<\/p>\n\n\n\n

      From the\nanalysis of the players’ diet, it can be concluded that all players take the\nnecessary amount of energy to meet their needs during a training session.<\/p>\n\n\n\n

      Table 2.\nResults of the food questionnaire<\/p>\n\n\n\n

      \"Table<\/figure>\n\n\n\n

      To\ndetermine the effect of carbohydrate (C), fat (F), and protein intake (P) on\ntotal energy intake (TEI), multiple linear least squares regression was made\nusing the SPSS software package. To determine the influence of the various\nindependent (factor) variables C, F and P on the dependent TEI variable, the\nstandardized regression coefficients of the multiple linear regression are\ntaken into account. They are derived from the regression coefficients.\nStandardized coefficients are interpreted by character but are comparable and\nin absolute value. The most influential factor is the one whose standardized\ncoefficient of regression is greatest.<\/p>\n\n\n\n

      The\nequation for multiple linear regression is:<\/p>\n\n\n\n

      \u0422\u0415<\/strong>I<\/strong> = <\/strong> <\/strong>a<\/strong> + <\/strong>b<\/strong>*(<\/strong>C<\/strong>*4) + <\/strong>c<\/strong>*(<\/strong>F<\/strong>*9) + <\/strong>d<\/strong>*(<\/strong>P<\/strong>*4)<\/strong><\/strong><\/p>\n\n\n\n

      Table 3. Results from multiple linear regression<\/p>\n\n\n\n

      \"Table<\/figure>\n\n\n\n

      From the\nabove table it is seen that the highest value has the standardized coefficient b<\/em>, in front of the carbohydrate intake which\nit means that it has the greatest influence (about 65%) on TEI.<\/p>\n\n\n\n

      At the\nsecond stage of the work, a field test was conducted during training. Prior to\nthe exercise, the first blood samples were taken to provide information about\nthe BLC prior to loading. Individual heart rate monitors were place during\ntraining and players are instructed to switch them on immediately before the\nstart of the training. The tool measures the duration of the exercise and the HR\nthroughout the training, and the software determines the minimum, maximum and\naverage HR, as well as the period during which this HR is maintained. The\nminimum and maximum frequencies in all subjects are maintained for only a few\nseconds, with the minimum heart rate at the beginning of the measurement\nperiod, and the maximum is during the basic part of the exercise when the player\nis struggling to take the ball. High intensity training tends to improve\nendurance. There are separate factors such as medical conditions, prescription\nmedications, and general exercises that affect the maximum heart rate of a\nperson. Most people have one to two minutes in maximum HR, highly trained\nathletes may have more. There are 5 heart rate zones according to the heart\nrate: 50-59% and 60-69% of maximum HR \u2013 a moderate intensity zones, 70-79% of\nmaximum HR \u2013 a moderate to vigorous intensity zone (75% of maximum HR and above\nis considered vigorous intensity), 80-89% and 90% + of maximum HR – a vigorous\nor high intensity zones.<\/p>\n\n\n\n

      Table 4.\nIndividual values \u200b\u200bof the heart rate of the subjects under study<\/p>\n\n\n\n

      \"Table<\/figure>\n\n\n\n

      As can be\nseen from the table, individuals begin the training with HR values \u200b\u200baround the\nlower limit. During training for a few seconds at the peak load, their HR\nrepeatedly exceeds the maximum. For most of the training, the HR of\nparticipants in the study range from 78.13 to 90.05 % of the maximum value,\nmeaning that they exercise at high intensity. Maintaining such a high HR\nindicates that football players are actively involved in training, and training\nwill result in improved endurance, which is the main goal of the training\nsession.<\/p>\n\n\n\n

      Whether\nthe training was effective can also be determined by the BLC. The second blood\nsample is collected before the start of the final part of the training, with\nthe players one leaving football field on the sign of the coach and the blood\nis taken immediately to prevent the lactate from being metabolized. In\nhigh-trained athletes, this happens very quickly, which would vitiate the\nresult. The results obtained are presented in Table 5.<\/p>\n\n\n\n

      Table 5.\nIndividual concentrations of lactate in the blood of the players<\/p>\n\n\n\n

      \"Table<\/figure>\n\n\n\n

      Some of\nthe players, on the advice of the coach, warm up in the stadium’s gym, so the\nvalues \u200b\u200b of their BLC exceed 2 mol\/L. As can be seen from the table, differences in BLC\nbefore and after exercise are significant, which new evidence of effective\nperformance training is and that it is able to develop the desired quality of\nfootball players, namely endurance. It is noticeable that two of the players\nhave a small difference in BLC before and after exercise, 4.51 mol\/L and 4.27 mol\/L respectively.\nSince the HR of the same players is in the intensive effort zone, respectively\n78.13 and 83.99 % of the maximum HR, perhaps the small change is due to the\nlarger amount of red muscle fibers that work in aerobic mode and produce less\nlactate.<\/p>\n\n\n\n

      No\ncorrelation can be found between heart rate and lactate concentration\n(Pearson`s correlation coefficient r = -0.16, p value = 0.65) because the\nlatter strongly depends on the type of muscle fibers of the respective player.\nDespite the intensity of exercise, people with a higher percentage of red\nmuscle fibers use glucose and fat as an aerobic fuel (oxidative\nphosphorylation), so their BLC do not increase.<\/p>\n\n\n\n

      CONCLUSIONS<\/strong><\/p>\n\n\n\n

      In\nconclusion, it can be said that according to the nutrition questionnaires, completed\nby the participants in the study, they receive a sufficient amount of\nmacronutrients and energy for their training needs; and it can be assumed that\nthey in turn had a sufficient quantity of vitamins and minerals. The change in\nblood lactate concentrations and heart rate during training is indicative of\nthe correctly conducted high intensity training, the effort made by the\nplayers, and therefore the target endurance quality was most likely to be\nachieved. <\/p>\n\n\n\n

      APPLICATIONS IN SPORT<\/strong><\/p>\n\n\n\n

      Reported\nmethods could be a useful tool for coaches to track the recovery and\npreparation of the athletes in season and to evaluate their performance during\nscheduled training session. This methodology allows determining the intensity\nof the training not only in football, but in different types of sports.\nKnowledge and skills were developed to use different biochemical parameters to\nimprove their training programs.<\/p>\n\n\n\n

      ACKNOWLEDGMENTS<\/strong><\/p>\n\n\n\n

      The study was conducted with the financial support of a\nproject RP B7\/18 of SWU \u201cN. Rilski\u201d<\/p>\n\n\n\n

      REFERENCES<\/strong><\/p>\n\n\n\n

      • Academy of Nutrition and Dietetics, American College of\nSports Medicine, & Dietitians of Canada (2016). Position of the Academy of\nNutrition and Dietetics, Dietitians of Canada, and the American College of\nSports Medicine: Nutrition and Athletic Performance. Journal of the Academy of\nNutrition and Dietetics, 116 (3), 501-528.<\/li>
      • Ainsworth B. E., Haskell W. L., Herrmann S. D., Meckes\nN., Bassett D. R. Jr., Tudor-Locke C., Greer J. L., Vezina J., Whitt-Glover M.\nC., & Leon A. S. (2011). 2011 Compendium of Physical Activities: a second\nupdate of codes and MET values. Med Sci Sports Exerc., 43(8), 1575-81.<\/li>
      • Barcelos R. P., Tocchetto G. L., Lima F. D., Stefanello\nS. T., Rodrigues H. F. M., Sangoi M. B., Moresco R. N., Royes L. F. F., Soares\nF. A. A., & Bresciani G. (2017). Functional and biochemical adaptations of\nelite level futsal players from Brazil along a training season. Medicina, 53,\n285 \u2013 293.<\/li>
      • Goodwin M. L., Harris J. E., Hern\u00e1ndez A., & Gladden\nL. B. (2007). Blood Lactate Measurements and Analysis during Exercise: A Guide\nfor Clinicians. Journal of Diabetes Science and Technology, 1 (4), 558-569.<\/li>
      • G\u00fcr E. (2012) A Comparison of Blood Lactate Level and\nHeart Rate Following a Peak Anaerobic Power Test in Different Exercise Loads.\nEuropean Journal of Experimental Biology, 2 (5),1854-1861.<\/li>
      • Kaya I., Kalkavan A., Senturk A., Harmanci H.,\nKaravelioglu M. B., Yuksel O., & Savasli M. (2013). Analysis of blood\nlactate and heart rate of indoor sports athletes as a response to various loads\nTurkish Journal of Sport and Exercise, 15 (3), 86-89.<\/li>
      • Lopes R. F., Osiecki R., & Rama L. M. P. L. (2012).\nHeart rate and blood lactate concentration response after each segment of the\nolympic triathlon event. Rev Bras Med Esporte, 18 (3), 158-160.<\/li>
      • Taru C., Tsutou A., & Miyawaki I. (2011).  A Modified Simple Questionnaire to Estimate\nDietary Energy Intake for the Japanese. Kobe J. Med. Sci., 57 (3), E106- E115.<\/li><\/ul>\n\n\n\n

        \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nolu<\/p>\n","protected":false},"excerpt":{"rendered":"

        Authors:Tatyana Dzimbova, Hristo Nikolov, Radoslav Mavrevski, Stefan Kapralov Corresponding Author:Assoc. […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_options":[]},"categories":[994,296],"tags":[1457,1456,1455,473,34],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p4btio-1CG","jetpack-related-posts":[{"id":247,"url":"https:\/\/thesportjournal.org\/article\/the-physical-and-physiological-properties-of-football-players-from-a-turkish-professional-first-division-football-league\/","url_meta":{"origin":6242,"position":0},"title":"The Physical and Physiological Properties of Football Players from a Turkish Professional First-Division Football League","date":"September 5, 2006","format":false,"excerpt":"Submitted by: S. Muniroglu & M. Koz Abstract This research aims to determine the effects of a six weeks pre-season preparation training period on the physical and physiological characteristics of a football team in the Turkish Professional First Division League. Twenty football players participated in this study. Their ages were\u2026","rel":"","context":"In "Sports Coaching"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":5359,"url":"https:\/\/thesportjournal.org\/article\/relationships-between-perfectionism-training-load-and-elite-junior-football-players-self-assessed-and-coach-assessed-skills\/","url_meta":{"origin":6242,"position":1},"title":"Relationships Between Perfectionism, Training Load and Elite Junior Football Players\u2019 Self-Assessed and Coach-Assessed Skills","date":"November 2, 2017","format":false,"excerpt":"Authors: Fredrik Klund & Stig Arve S\u00e6ther Corresponding Author: Stig Arve S\u00e6ther. Mr Norwegian University of Science and Technology Department of Sociology and Political Science, Dragvoll, 7491 Trondheim, Norway E-mail: stigarve@ntnu.no 00477-355-1133 Stig Arve S\u00e6ther are associate professor in sport science at the Norwegian University of Science and Technology. His\u2026","rel":"","context":"In "Sports Coaching"","img":{"alt_text":"Table 1","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2017\/11\/Table1.png?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":7832,"url":"https:\/\/thesportjournal.org\/article\/monitoring-cardiac-autonomic-function-and-sleep-duration-in-ncaa-division-i-football-players-during-preseason-and-in-season-using-wearable-tracking-devices\/","url_meta":{"origin":6242,"position":2},"title":"Monitoring cardiac autonomic function and sleep duration in NCAA Division I football players during preseason and in-season using wearable tracking devices","date":"March 19, 2021","format":false,"excerpt":"Authors: Portia Resnick1, Davis Hale2, Roger Kollock2, Tori Stafford2, Erich Anthony3 1Department of Kinesiology, California State University, Long Beach, Long Beach, CA2Oxley College of Health Sciences, University of Tulsa, Tulsa, OK3Department of Athletics, University of Tulsa, Tulsa, OK Corresponding Author:Portia B. Resnick, PhD, ATC, BCTMBCalifornia State University, Long BeachDepartment of\u2026","rel":"","context":"In "Research"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":438,"url":"https:\/\/thesportjournal.org\/article\/comparison-of-two-different-training-methods-for-improving-dribbling-and-kicking-skills-of-young-football-players\/","url_meta":{"origin":6242,"position":3},"title":"Comparison of Two Different Training Methods for Improving Dribbling and Kicking Skills of Young Football Players","date":"December 30, 2011","format":false,"excerpt":"Plainos, C., Patsiaouras, \u0391., Ispirlidis, I., Gourgoulis, \u0392., Laios, \u0391., Taxildaris, \u039a., & Mavromatis, G ### Abstract The purpose of this study was to examine the effectiveness of two different training methods on the performance improvement of dribbling and kicking technical skills of young football players (8-11 years old). The\u2026","rel":"","context":"In "Sports Exercise Science"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":8188,"url":"https:\/\/thesportjournal.org\/article\/stressors-associated-with-professional-australian-rules-football-athletes-across-a-competitive-season\/","url_meta":{"origin":6242,"position":4},"title":"Stressors Associated with Professional Australian Rules Football Athletes Across a Competitive Season","date":"April 15, 2022","format":false,"excerpt":"Authors: Billymo Rist1, Anthea C Clarke1, Tony Glynn2, Alan J. Pearce11 School of Allied Health, La Trobe University, Bundoora, Melbourne, AUSTRALIA2 Fit Mind Consulting, Spencer Street, West Melbourne, Melbourne, Australia Corresponding Author:Billymo RistSchool of Allied Health, La Trobe University, Bundoora, Melbourne, AUSTRALIAEmail: brist@latrobe.edu.auPh: +61 400392964 Billymo Rist is a PhD\u2026","rel":"","context":"In "Research"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2022\/04\/Figure1.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":447,"url":"https:\/\/thesportjournal.org\/article\/effects-of-american-football-on-height-in-high-school-players\/","url_meta":{"origin":6242,"position":5},"title":"Effects of American Football on Height in High School Players","date":"January 3, 2012","format":false,"excerpt":"Brian Campbell, Torie Guidry, Matt Lopez, Kristina Estis and David Bellar ### Abstract The aim of the present study was to investigate height change of high school football players during a single game. 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