Internal training load and its longitudinal relationship with seasonal player wellness in elite professional soccer

Accepted Manuscript Internal training load and its longitudinal relationship with seasonal player wellness in elite professional soccer

Filipe Manuel Clemente, Bruno Mendes, Pantelis Theodoros Nikolaidis, Francisco Calvete, Sandro Carriço, Adam Lee Owen PII: DOI: Reference:

S0031-9384(16)31068-X doi: 10.1016/j.physbeh.2017.06.021 PHB 11839

To appear in:

Physiology & Behavior

Received date: Revised date: Accepted date:

19 November 2016 7 June 2017 28 June 2017

Please cite this article as: Filipe Manuel Clemente, Bruno Mendes, Pantelis Theodoros Nikolaidis, Francisco Calvete, Sandro Carriço, Adam Lee Owen , Internal training load and its longitudinal relationship with seasonal player wellness in elite professional soccer. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Phb(2017), doi: 10.1016/j.physbeh.2017.06.021

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ACCEPTED MANUSCRIPT Internal training load and its longitudinal relationship with seasonal player wellness in elite professional soccer Filipe Manuel Clemente1,2* , Bruno Mendes3 , Pantelis Theodoros Nikolaidis4 , Francisco Calvete3 , Sandro Carriço3 , Adam Lee Owen3,5

Instituto Politécnico de Viana do Castelo, Escola Superior de Desporto e Lazer, Melgaço, Portugal

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Instituto de Telecomunicações, Delegação da Covilhã, Portugal

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Benfica LAB, Sport Lisboa e Benfica, Lisbon, Portugal

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Exercise Physiology Laboratory, Nikaia, Greece

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Centre de Recherche et d’Innovation sur le Sport, Université Claude Bernard Lyon.1, Lyon, France

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*Corresponding Author: Filipe Manuel Clemente, filipe.clemente5@g mail.co m, Adress : Complexo

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Desportivo e Lazer de Melgaço – Monte de Prado, 4960-320, Melgaço, Portugal

Abstract Monitoring internal training load has been extensively used and described within team sport environments, however when compared to internal physiological measures such as heart rate (HR) and rating of perceived exertion (RPE), the literature is sparse. The 1

ACCEPTED MANUSCRIPT primary aim of this investigation study was to assess differences of playing position on ITL, session-RPE and wellness across two different training microcycles (1 vs. 2 competitive games), in addition with examining the relationship between ITL and Hooper’s Index across an entire season. Thirty-five professional soccer players from the Portuguese premier league participated in the study (25.7 ± 5.0 years; 182.3 ± 6.4 cm; 79.1 ± 7.0 kg). Analysis of variance revealed higher values of DOMS (Means(M): 3.33 vs. 3.10; p = 0.001; effect Size (ES) = 0.087), fatigue (M: 3.18 vs. 2.99; p = 0.001; ES =

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0.060) and HI (M: 11.85 vs. 11.56; p = 0.045; ES = 0.034) in 2-game weeks compared

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with 1-game weeks. Correlation between ITL and HI levels found significant negative correlations between ITL and DOMS (ρ = -0.156), ITL and sleep (ρ = -0.109), ITL and fatigue (ρ = -0.225), ITL and stress (ρ = -0.188), and ITL and HI (ρ = -0.238) in 2-game weeks. Results from 1-game microcycle only highlighted negative correlations between

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ITL and stress (ρ = -0.080). It was concluded from the study that greater fatigue potential, muscle soreness, stress and ITL was significantly more apparent within a 2game microcycle. As a result, care should be taken when planning the lead into and out

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of a 2-game fixture microcycle highlighting key specific recovery strategies to damped the increased stress effect. Additionally, the potential utilization of squad rotation

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strategies may be a positive approach with aim of managing the fatigue effect.

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Keywords: soccer; congested fixture; training; RPE; monitoring.

1. Introduction Monitoring internal training load has been used extensively and well discussed in sports, especially in team sports (1). Additionally, compared to internal physiological 2

ACCEPTED MANUSCRIPT measures, such as heart rate (HR) and rate of perceived exertion (RPE), other measures of physiological status are less known. Recent literature has reported the use of the Hooper index (2) as a reliable method for the monitoring of athlete wellness providing further information concerning the detail of player fatigue, stress, muscle soreness and sleep perception. The Hooper index has recently been utilized to monitor player wellness during a 4-day FIFA international futsal tournament (2) in addition with a 2month study on cycling performance (3). However, apart from the aforementioned

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studies, the relationship between use of the Hooper index and session-RPE is limited

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amongst the research. One investigation observed no association between the Hooper index and RPE (4), however, further research is needed in this subject to validate the findings further.

Recent literature using team sport players competing in one game microcycle

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have shown that internal training load might be more intense towards the beginning of the microcycle as a way to ensure fatigue is minimal close to competitive match play (5–7) and a one-month mesocycle (8). However, competing in 2-game microcycles

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occurs often in team sports such as soccer, when teams are more successful based on their need for domestic and European competition (6,9). A recent study also suggests

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that there are evidences of a negative impact of a longitudinal fixture congestions cross the season (10). Only a few studies have so far investigated the quantification of training of microcycles varying for scheduled matches focusing on the external load, i.e.

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distance covered per training unit (6,11,12). The effect of game and training load on fatigue have been also analysed in the

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context of soccer (13,14). The immediate effect of a game is to reduce the maximal voluntary contraction and increase the muscle soreness (15). Decreases in repeated

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sprint ability after the game is also commonly observed (16,17). However, the extension of the fatigue effect after game or training seems to be influenced by the competitive level in which elite recover faster than amateur players (15). The daily training load may also constrain the perception of fatigue and the risk of illness and injury (18). In a study conducted in elite soccer players it was found that ratings of fatigue were sensitive to fluctuations in acute total high-speed running distance accumulation (19). Moreover, the high perception of leg muscular effort after high training volume can impair the improve of physical fitness variables (20). The quality of sleep and the stress are also sensitive to the training volume (21).

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ACCEPTED MANUSCRIPT Although the abovementioned research has enhanced our understanding of the variation of fatigue in different periods, namely identifying some decreases in performance variables (9) and the association of training load with quality of life variables, we believe that is still necessary to cross in a single study the variables of training load, perception of fatigue, stress, muscle soreness and stress and analyze such variance in different types of week. Such information would be of practical and theoretical value for coaches and researchers, respectively, as it may help coaches tailor

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training sessions with the aim of minimizing fatigue and lead to the player’s

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perceptions. Therefore, as a result of the limited investigations in this area, the aim of this study was to i) to analyse the microcycle variance using the Hooper index scales amongst positional roles (1 vs 2 games per week), and ii) study the association between

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internal training load (ITL) and Hooper index scales.

2. Methods

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2.1. Participants

Thirty-five professional soccer players from the Portuguese premier league participated

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in this study (25.7 ± 5.0 years; 182.3 ± 6.4 cm; 79.1 ± 7.0 kg). Two inclusion criterions were selected to analyze the variance of HI and ITL between microcycles: i) ensure regular participation in the majority of training sessions (80% of weekly training

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sessions); ii) possesses medical clearance at the beginning of the microcycle to participate in full training. The study of HI levels between weeks with one or two

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matches met the following criteria: i) completing at least 75 min in three consecutive games to be included in the analysis of the week(s).

The study was approved by the

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local institute’s research ethics committee and written informed consent was obtained from each player before participation. The study followed the ethical recommendations for the study in humans as suggested by the Declaration of Helsinki. All the players were accustomed to the daily procedures used in this research as part of their habitual training routines.

2.2. Design A correlational research design was used to test the relationships between internal load and the variables of sleep quality, perception of fatigue, stress and muscle soreness 4

ACCEPTED MANUSCRIPT (DOMS). Analysis of variance design was used to test differences in dependent variables of internal load and Hooper index between the factors (independent variables): i) microcycle (1 vs. 2 game weeks); and ii) playing positions (GK: goalkeeper; WD: wide defender; CD: central defender; MF: midfielder; WMF: wide midfielder; FW: forward).

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2.3. Experimental procedures

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Training data were collected during the entire season (Figure 1) which commenced

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Figure 1. Timeline of the study.

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August 2015 and ended at May 2016 (European schedule).

All training programs were planned by the coach and staff and the researchers only

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standardized the first 30 minutes and the final 30 minutes before and after session. The wellness questionnaire and session-RPE questionnaire were applied in the beginning and in the end of the session, respectively. The familiarization of the subjective scales

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(Hooper’s Index and session-RPE) was held during the pre-season period. Two types of training microcycle (TM) were analyzed in this study: i) week with one official match;

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and ii) week with two official matches. Playing positions were codified in: i) goalkeeper (GK); ii) external defender (ED); iii) central defender (CD); iv) midfielder (CMF); v) external midfielder (EMF); and vi) forward (FW).

2.4. Hooper Index (HI) Approximately 30 minutes before each training session, each player was asked to rate the perception of the quantity of fatigue, stress and DOMS and quality of sleep of the night that have preceded the evaluation. The hooper index scale of 1-7 (22) was used in which 1 is very, very low and 7 is very, very high (for stress, fatigue and DOMS levels)

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ACCEPTED MANUSCRIPT and 1 is very, very bad and 7 is very, very good (for sleep quality). The Hooper Index is the summation of the four subjective ratings.

2.5. Session-RPE and internal training load (ITL) The session-RPE was collected approximately 30 minutes after each training session. The Borg’s CR-10 scale was applied (1 is very light activity and 10 is the maximal exertion) in order to determine the perception of effort made during the training. The

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value rated by the player was multiplied by the time of session in minutes (from warm-

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up until the last moment of cool-down) as suggested by previous studies (23,24). Match data was not considered for use within the investigation.

Internal Training Load (ITL) = session-RPE (AU) x training duration (mins)

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Each player rated the session-RPE in an individual portable computer tablet (Microsoft Surface Pro 3, USA) with a custom-designed application, where the subjects were able to answer the scales.

This application was specifically developed for HI and session-

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RPE. Each player’s answer was automatically saved in the player’s profile in the system. This method helped to minimize the influence of hear or observe the rating of

2.6. Statistical analysis

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their peers (25), thus ensuring a more precise and non-influenced individual answer.

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The results were expressed as means ± standard deviation (SD). Analysis of variance have tested possible difference of HI and session-RPE ordinal scales between type of

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microcycle and positions of players. Based on the type of the data, non-parametric tests of Mann-Whitney U (to test the variance between two types of microcycle) and

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Kruskal-Wallis H (to teste the variance between playing positions) were executed (26). The effect size (ES) was calculated for Mann-Whitney U test by using the r technique (27).

𝑟=

𝑧 √𝑁

where r is the effect size (ES), z value in addition to the values for U (Mann-Whitney) and N is the sample. The following score was used to classify the effect of r (ES): small effect is 0.1; a medium effect is 0.3; and large effect is 0.5 (28). ES can be interpreted as the magnitude of a study’s findings and complement the interpretation of statistical significance (27).

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ACCEPTED MANUSCRIPT The Mann-Whitney U test was also used as post hoc for Kruskal-Wallis U. The value of p was adjusted to avoid Type I error inflation (26). The associations between ITL and HI scales were tested with Spearman correlation (26). The magnitude of the correlations was classified as follows (29): r ≤ 0.1, trivial; 0.1 < r ≤ 0.3, small; 0.3 < r ≤ 0.5, moderate; 0.5 < r ≤ 0.7, large; 0.7 < r ≤ 0.9, very large; > 0.9, nearly perfect. All statistical analysis was computed using the Statistics Package for Social Sciences (version 23.0; IBM Corporation, New York, USA) for a p ≤

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0.05.

3. Results

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Analysis of variance found that DOMS (p = 0.001; ES = 0.087), fatigue (p = 0.001; ES = 0.060), Hooper index (p = 0.045; ES = 0.034) were higher in weeks with two matches and stress (p = 0.003; ES = 0.050) and internal training load (p = 0.001; ES

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= 0.195) were higher in weeks with one match. DOMS, fatigue and HI were 7.42%, 6.35% and 2.51% higher in weeks with two matches than with one match, respectively.

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In the other hand, stress and ITL were 5.49% and 25.49% higher in weeks with one match, respectively. Descriptive statistics of hooper index and internal load per

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microcycle can be found in table 1.

Table 1. Descriptive statistics (M±SD) of hooper index and internal load variables per

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type of microcycle.

Two matches/week

Muscle soreness (DOMS)

3.10±1.13**

3.33±1.26**

Sleep

2.97±1.13

2.99±1.18

Fatigue

2.99±1.19**

3.18±1.35**

Stress

2.50±1.30**

2.37±1.28**

Hooper Index

11.56±3.43*

11.85±3.76*

Internal Training Load (ITL)

308.28±159.82**

245.66±153.97**

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One match/week

*Significant different between one and two matches at the 0.05; **Significant different between one and two matches at the 0.01

The Kruskal-Wallis H tested the variance of HI scales and ITL between playing positions. Analysis of variance revealed differences between playing positions in the

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ACCEPTED MANUSCRIPT DOMS (H = 53.58; p = 0.001), sleep (H = 194.86; p = 0.001), fatigue (H = 104.50; p = 0.001), stress (H = 524.66; p = 0.001), HI (H = 136.91; p = 0.001) and ITL (H = 190.74; p = 0.001). Pairwise comparison between playing positions can be found in the next paragraphs. The descriptive statistics can be found in table 2.

Table 2. Descriptive statistics (M±SD) of hooper index and internal load variables per playing position. CD

MF

(n=3)

(n=6)

(n=4)

DOMS

3.29±0.87 b,e,f

2.97±0.95 a,c,d,e

3.25±1.12 b,e

Sleep

3.48±0.86 b,c,d,e,f

3.26±1.13 a,c,d,e,f

2.82±0.99 a,b,d,e

Fatigue

2.75±0.96 b,c,e,f

3.21±1.07 a,d

3.24±1.11 a,d

Stress

1.70±0.94 b,c,d,e,f

2.72±1.13 a,c,d,e,f

3.15±1.20 a,b,d,e,f

HI

11.21±2.15 b,c,e

12.16±3.04 a,d,f

12.46±2.54 a,d,f

307.87±149.78

249.12±150.08

a,c,d

(n=9)

226.86±141.16

a,b,d,e

EMF

FW

(n=8)

(n=5)

3.15±1.17 b,e

3.47±1.08 a,b,c,d

3.48±1.79 a,e

2.55±1.32 a,b,c,e,f

3.02±1.04 a,b,c,d,f

3.00±0.83 a,b,d,e

2.68±1.33 b,c,e,f

3.35±1.02 a,d,f

3.46±1.85 a,d,e

1.96±1.21 a,b,c,e

2.59±1.35 a,b,c,d,f

2.24±1.35 a,b,c,e

10.34±3.87 b,c,e

12.42±3.44 a,d,f

12.18±4.84 b,c,e

326.00±165.39

b,c,e,f

252.05±150.97

a,c,d,f

231.77±152.23 a,d,e

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Statistical different from GK a, EDb , CDc, MFd , EMFe and FW f for a p<0.05.

DOMS: muscle soreness; HI: hooper index; IT L: internal training load (session-RPE*time of training); GK: goalkeeper; ED:

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external defender; CD: central defender; MF: midfielder; EMF: external midfielder; FW: forward.

Pairwise comparisons for Kruskal-Wallis H were made with Mann-Whitney. GKs had worst values than CDs in sleep (p = 0.001; ES = 0.292), smaller values in fatigue (p

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= 0.001; ES = 0.230), stress (p = 0.001; ES = 0.569) and HI (p = 0.001; ES = 0.265) and higher values of ITL (p = 0.001; ES = 0.292). GKs had higher values than EDs in

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DOMS (p = 0.001; ES = 0.126), Sleep (p = 0.001; ES = 0.104) and ITL (p = 0.001; ES = 0.226) and smaller values of fatigue (p = 0.001; ES = 0.224), stress (p = 0.001; ES =

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0.448) and HI (p = 0.001; ES = 0.242). GKs had greater values than MFs in sleep (p = 0.001; ES = 0.319) and smaller in stress (p = 0.001; ES = 0.154). GKs had greater values than EMFs in DOMS (p = 0.004; ES = 0.082), Sleep (p = 0.001; ES = 0.179),

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IT L

b,c,e,f

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GK

fatigue (p = 0.001; ES = 0.251) and ITL (p = 0.001; ES = 0.181) and smaller in stress (p = 0.001; ES = 0.344) and HI (p = 0.001; ES = 0.190). GKs had greater values than FWs in DOMS (p = 0.045; ES = 0.069), sleep (p = 0.001; ES = 0.295) and ITL (p = 0.001; ES = 0.292) and smaller in fatigue (p = 0.001; ES = 0.098) and stress (p = 0.001; ES = 0.171). EDs had smaller values than CDs in DOMS (p = 0.001; ES = 0.117) and stress (p = 0.001; ES = 0.138) and higher in sleep (p = 0.001; ES = 0.168) and ITL (p = 0.044; ES = 0.068). EDs had higher values than MFs in sleep (p = 0.001; ES = 0.224), fatigue (p = 0.001; ES = 0.130), stress (p = 0.001; ES = 0.279) and smaller in DOMS (p =

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ACCEPTED MANUSCRIPT 0.001; ES = 0.126), HI (p = 0.001; ES = 0.183) and ITL (p = 0.001; ES = 0.256). EDs had higher values than EMFs in sleep (p = 0.001; ES = 0.071) and stress (p = 0.001; ES = 0.072) and smaller in DOMS (p = 0.001; ES = 0.189). EDs had higher values than FWs in sleep (p = 0.001; ES = 0.150) and stress (p = 0.001; ES = 0.291) and smaller in HI (p = 0.006; ES = 0.086). CDs had higher values than MFs in sleep (p = 0.001; ES = 0.082), fatigue (p = 0.001; ES = 0.129), stress (p = 0.001; ES = 0.414) and HI (p = 0.001; ES = 0.214) and

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smaller in ITL (p = 0.001; ES = 0.309). CDs had higher values than EMFs in DOMS (p

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= 0.003; ES = 0.080) and stress (p = 0.001; ES = 0.213) and smaller in sleep (p = 0.001; ES = 0.092) and ITL (p = 0.001; ES = 0.109). CDs had higher values than FWs in stress (p = 0.001; ES = 0.410) and smaller in HI (p = 0.001; ES = 0.114).

MFs had smaller values than EMFs in DOMS (p = 0.012; ES = 0.062), sleep (p =

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0.001; ES = 0.166), fatigue (p = 0.001; ES = 0.166), stress (p = 0.001; ES = 0.199) and HI (p = 0.001; ES = 0.186) and smaller in ITL (p = 0.001; ES = 0.217). MFs had smaller values than FWs in sleep (p = 0.001; ES = 0.099) and fatigue (p = 0.028; ES =

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0.062) and higher ITL (p = 0.001; ES = 0.288).

EMFs had higher values than FWs in sleep (p = 0.027; ES = 0.065), stress (p =

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0.001; ES = 0.188), HI (p = 0.001; ES = 0.101) and ITL (p = 0.005; ES = 0.104) and smaller in fatigue (p = 0.024; ES = 0.067). The association between internal load and perceived hooper’s index was tested

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with Spearman. The values of spearman rho (ρ) can be found in the following table 3.

load (ITL).

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Table 3. Correlation values (ρ) between hooper index variables and internal training

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DOMS

Sleep

Fatigue

Stress

HI

General (without split the data in type of weeks) ITL

-0.093**

-0.041*

-0.132**

-0.133**

-0.142**

0.025

0.041

0.017

-0.080*

-0.005

-0.156*

-0.109**

-0.225**

-0.188**

-0.238**

One match per week ITL

Two matches per week ITL

*Correlation is significant at the 0.05; **Correlation is significant at the 0.01

There were negative correlations between ITL and DOMS (ρ = -0.093), ITL and sleep (ρ = -0.041), ITL and fatigue (ρ = -0.132), ITL and stress (ρ = -0.133) and ITL

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ACCEPTED MANUSCRIPT and HI (ρ = -0.142). The data sample was than split per type of microcycle. In the case of weeks with only one match it was found a negative correlation between ITL and stress (ρ = -0.080). In the case of two matches per week it were found negative correlations between ITL and DOMS (ρ = -0.156), ITL and sleep (ρ = -0.109), ITL and fatigue (ρ = -0.225), ITL and stress (ρ = -0.188) and ITL and HI (ρ = -0.238).

4. Discussion

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The primary aim of this investigation study was to assess positional playing

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differences on ITL, session-RPE and wellness across two-different training microcycles (1 vs. 2 competitive games). Furthermore, the investigation aimed to examine the relationship between ITL and psychophysical monitoring levels (i.e. Hooper’s Index) across the entire season. To the authors knowledge, this is the first study investigating

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the variance of HI and ITL across playing positions within different microcycles in elite professional soccer players. It is one of the first studies to have analyzed the relationships between HI scales and ITL in different types of microcycle. Results from

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the current study highlighted significant correlations between ITL and HI scales across 2-game weeks. The analysis of variance revealed significantly higher subjective values

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of fatigue, DOMS and HI in weeks with two official matches but no significant differences were found across sleep quality markers. This is in-line with current literature who suggested non-significant correlations (r = 0.20) between TL (RPE x

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duration) and perceived quality of sleep (from Hooper questionnaire) (21). Furthermore, findings of Thorpe et al. (30) reported associations between ITL and perceived fatigue,

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but not perceived quality of sleep. Internal training load has been measured by objective variables (heart rate or

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blood lactate concentrations) and also by subjective scales (session-RPE) that are an alternative to the objective measures but that allow the quantification, in a user-friendly and cost-effective way, of the load imposed on the players by the training (4,23,24,31). Session-session-RPE seems to be an effective scale to measure the intensity of training and recent findings suggest that it is not sensitive to the subjective perception of fatigue, DOMS or stress levels (4). The reliability of session-RPE to quantify the load should be understood as a good indicator for coaches and for the practical applications in team sports training. Recent literature has discussed the effects of congested fixtures (two matches in a period of five to six days) on physical performance (9,32), with the majority of findings 10

ACCEPTED MANUSCRIPT revealing small to non-existent effects of congested fixtures on physical performance measured by time–motion analysis (32). Nevertheless, to the best of our knowledge, the effects of congested periods on ITL have not been assessed or revealed. Interestingly, the analysis revealed significant small and negative correlations between ITL and all the HI variables in weeks with two official matches, with one level of significance between ITL and stress in weeks with one official match. Evidence from the results suggests that session-RPE may be sensitive to congested fixture periods but not sensitive to regular

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periods of training with one game week. Additionally, results from the current study

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revealed a small inverse relationship between ITL and sleep quality in 2-game microcycles. This can be justified by the stress levels imposed by the 2-games and the subsequent induced DOMS, or even the psychological demand and total volume imposed on the players within this microcycle structure. Nevertheless, the training

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intensity seems not be related with sleep quality per se (33,34), which could suggest that in a competitive period, with different training and travel regimes, a perceived-

association with TL in elite soccer.

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sleep marker might only bring information on potential recovery status rather than any

Based on such findings, analysis of variance of HI scores between types of

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microcycle was also conducted. Small-to-medium-effect sizes were found between microcycles with one and two official matches. DOMS and fatigue scores (with the exception of sleep quality) were significantly higher in weeks with two official matches,

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suggesting possible effects of congested fixtures on the perception of fatigue and muscle soreness. A possibility to reduce the impact of congested fixtures is to improve

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the strength of lower limb based on the fact that be stronger seems to be associated with lower creatine kinase levels in the 48 hours after match (14) comparable-study

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conducted in a younger participants (U16) has revealed that congested periods led to significant changes in testosterone levels, which may influence the training motivation, performance, training outcomes, and effort during competition (35) and possibly justifying the higher perception of fatigue, stress, DOMS, and ITL revealed in our study. Results in our study also found smaller values of internal training load in weeks with two official matches, indicating how the impact of the games may lead to a management of the load and with recovery strategies adopted by coaches and fitness coaches (36). Interestingly, significant differences in HI scales and ITL were found between playing positions with results revealing that EMF and FW had greater values of DOMS 11

ACCEPTED MANUSCRIPT and fatigue which is in-line with recent literature highlighting the RPE effects on positional roles (7) who found WFs producing significantly increased ITL values compared across other positions. This was attributed to the link function these positional roles play in both supporting the defensive and attacking functions of the game. GK and ED had significantly better values of sleep quality with CDs having significantly greater values of stress which is in line with a previous study (7). GK and MF had the greatest perceptions of ITL. GKs generally train more through power and

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high-intensity based activities which as result may psychologically influence the

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reporting of RPE and subsequent ITL. Midfielder players however generally cover most distance compared to other positions (37), and as a result the link between RPE and volume metrics (25) would concur with the fact that MF players induce a higher ITL demand in both games and training scenarios. These changes between players’

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perceptions are also an innovation, as far we know. In a study conducted in professional soccer players from the English Premier League, the internal and external training load was analyzed during an entire season (25). The variations in session-RPE were not

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significant between positions, thus suggesting nonexistent differences in the perception of the training load. In our case, significant differences were found in ITL measures by

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session-RPE. Moreover, significant differences were also found in fatigue, muscle soreness, stress, and sleep quality, thus suggesting that the training may induce different responses from the players and different reactions to the load. Further studies must to

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cross objectively measurements based on quantitative information to determine the real effects of internal and external training load and the relationships with HI, considering

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the variance between positions. In fact, the specificity of positions leads to different frequency of actions (38). Differences in the player load, acceleration or deceleration

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are different from position to position and the specificity of these patterns may constrain the general perceptions of HI scores and even the ITL (39).

Limitations

Internal training load was only measured by session-RPE and this may have constrained the real quantification of the physiological impact of the training. External load was not used in this study, nevertheless the physical quantification of training impact may be an interesting set of variables to justify the perception of DOMS and fatigue. Based on that, future research should monitor the external load by using GPS trackers and inertial 12

ACCEPTED MANUSCRIPT measurement units and correlate these variables with HI scores. Although with some limitations, this study has contributed some new approaches with which to associate ITL with the perception of fatigue, stress, DOMS, and quality of sleep and is also, as far as we know, the first study to compare the effects of different types of microcycle on the HI scores and ITL levels. Finally, the effect sizes are trivial-to-small. Based on that, more data from different teams must be used to generalize the results.

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Practical applications

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Congested fixtures seem to have an impact on the player’s perception of fatigue, DOMS, stress, and ITL. Results found in this study may suggest that ITL may be sensitive to HI and vice versa, nevertheless future studies are needed to confirm this result. Future studies should include GPS trackers and inertial technology to correlate

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the external load with HI scores. The evidences found in this study may help coaches to be careful to invest in recovery strategies during congested fixtures. Moreover, the training load may be readjusted in the weeks with two official matches, based on the HI

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scores provided by players. The using of objectively instruments and methods to monitoring training load and to assess fatigue levels of players during the season is the

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main key message from this study. Variation in training load and adjustments to congested features are the main practical applications to fitness coaches.

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5. Conclusion

Microcycles with two official matches revealed significantly greater values of DOMS

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and fatigue scores. In the other hand, higher values of internal training load were found in weeks with one match. Relationship tests between ITL and HI scores have revealed

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significant and negative small-to-moderate correlations in the weeks with two official matches but not in the weeks with only one match. Finally, HI scores and ITL differed significantly from position to position, thus suggesting that the specificity of muscular recruitment in the players may constrain the perception of fatigue.

Acknowledgements The authors would like to thank to BenficaLab and the soccer players for their participation. This work was supported by the FCT project PEst-OE/EEI/LA0008/2013.

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ACCEPTED MANUSCRIPT Highlights

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 Weeks with two official matches revealed significantly greater values of DOMS and fatigue scores.  Higher values of internal training load were found in weeks with one match. Relationship tests between ITL and HI scores have revealed significant and negative small-to-moderate correlations in the weeks with two official matches but not in the weeks with only one match.  HI scores and ITL differed significantly from position to position, thus suggesting that the specificity of muscular recruitment in the players may constrain the perception of fatigue.

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