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Journal Pre-proof
Changes in markers of body composition of professional male soccer players during
pre-season
Gary Paul McEwan, Franchek Drobnic, Antonia Lizarraga, Antonio Gómez Díaz,
Eduard Pons, Antonio Dello Iacono, Viswanath Unnithan
PII: S2666-3376(20)30044-5
DOI: https://doi.org/10.1016/j.smhs.2020.08.004
Reference: SMHS 32
To appear in: Sports Medicine and Health Science
Received Date: 27 July 2020
Revised Date: 31 August 2020
Accepted Date: 31 August 2020
Please cite this article as: McEwan GP, Drobnic F, Lizarraga A, Díaz AG, Pons E, Iacono AD, Unnithan
V, Changes in markers of body composition of professional male soccer players during pre-season,
Sports Medicine and Health Science, https://doi.org/10.1016/j.smhs.2020.08.004.
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© 2020 Chengdu Sport University. Production and hosting by Elsevier B.V. on behalf of KeAi.
2
Changes in markers of body composition of professional male soccer
1
players during pre-season
2
Authorship: 3
Gary Paul McEwan
1
, Franchek Drobnic
2,3
, Antonia Lizarraga
3
, Antonio Gómez Díaz
4
, 4
Eduard Pons
4
, Antonio Dello Iacono
1
, Viswanath Unnithan
1
5
1
Division of Sport and Exercise, University of the West of Scotland, Glasgow, UK 6
2
Medical Department, Shanghai Greenland Shenhua FC, Shanghai, China
7
3
Medical, Sport Science and Health Department, FC Barcelona, Barcelona, Spain 8
4
Sports Performance Department, FC Barcelona, Barcelona, Spain 9
Corresponding Authors: 10
Professor Viswanath Unnithan and Mr Gary P McEwan 11
Division of Sport and Exercise, University of the West of Scotland, Glasgow, UK, G72 0LH 12
Email addresses: Vish.Unnithan@uws.ac.uk and Gary.McEwan@uws.ac.uk 13
14
15
16
17
18
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Changes in markers of body composition of professional male soccer
19
players during pre-season
20
Abstract 21
To evaluate changes achieved in whole-body and regional (upper limbs, lower limbs, and 22
trunk) estimates of body composition, twenty professional male soccer players (7 defenders, 23
7 midfielders, 6 forwards) underwent dual-energy x-ray absorptiometry (DXA) analysis at the 24
beginning and end of pre-season. Measures included: mass, fat mass (FM), fat-free mass 25
(FFM), and body fat per cent (BF%). Players’ activity during on-field training sessions was 26
monitored using Global Positioning System (GPS) units, with GPS data used to obtain 27
estimations of energy expenditure (EE). Whole-body mass remained unchanged across the 28
pre-season. Moderate significant increases and decreases were achieved in whole-body FFM 29
(Pre: 59.58±5.27 kg; Post: 60.61±5.18 kg; P=0.001; d=0.87) and FM (Pre: 10.60±1.88 kg; 30
Post: 9.56±1.81 kg; P=0.001; d=0.85), respectively. Moderate significant decreases were 31
achieved in whole-body BF% (Pre: 14.4±2.3 %; Post: 12.9±2.0 %; P<0.001; d=0.94). No 32
significant inter-positional differences were observed for the changes achieved in any global 33
or regional estimate of body composition. Total EE was significantly correlated with ΔFM 34
(r=0.65, P=0.002), ΔFFM (r=0.46, P=0.03), and ΔBF% (r=0.67, P=0.002). The total EE of 35
pre-season training accounted for 42%, 21%, and 45% of the variance in ΔFM, ΔFFM, and 36
ΔBF%, respectively. These findings suggest that the pre-season period is a suitable time for 37
initiating favourable alterations in body composition following the off-season in elite soccer 38
players. 39
Key Words: DXA; association football; team sport; GPS 40
41
42
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Introduction 43
The maintenance of an appropriate body composition is an important requisite in the physical 44
conditioning of elite soccer players.
1
Intuitively, excess body fat represents an inert load 45
likely to impair physical performance and predispose players to a heightened risk of all-cause 46
injury.
2
Conversely, the fat-free compartment of the body, constituting lean muscle and bone 47
mineral mass, plays a key role in strength and power performance and forms an integral 48
component of the physical make-up of the elite soccer player.
3
The routine measurement of 49
body composition is therefore a useful practice in professional soccer and is commonly 50
undertaken to assess players’ readiness for competition and monitor the effectiveness of 51
dietary and training interventions.
1
52
As is commonplace within many team sports, soccer adopts a cyclical pattern of competition, 53
where the cessation of the competitive season is followed by a period of planned rest and 54
recuperation. This period of inactivity and reduced training, the so-called off-season, 55
typically lasts between 4-6 weeks and may adversely affect measures of body composition.
4
56
In a recent study of 19 elite male soccer players, significant increases in body fat per cent 57
(BF%) were observed following a 6-week off-season period, with changes mediated through 58
increases in whole-body fat mass (FM) and reductions in the fat-free mass (FFM) of the 59
lower limbs.
5
Given the deleterious effects that such outcomes may have on parameters of 60
match-related fitness such as speed, power, and high-intensity running performance,
6
61
reversing such trends prior to the return to competition is desirable. 62
To facilitate the return to competition and provide players with the opportunity to establish 63
the physical base from which technical and tactical development can occur, an intensive pre-64
season training programme is commonly undertaken.
7
In comparison to the in-season where 65
professional players may complete an average of three training sessions per week,
8
training 66
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loads (TL) are generally increased up to 2-4 times during the pre-season.
9
Consequently, 67
energy expenditure (EE) will be elevated during this phase of the season.
10
Accordingly, 68
energy intake (EI) should be modified in relation to the body composition goals of the 69
player.
11
During the in-season, players typically match EI with their daily energy 70
requirements to avoid hindering performance.
12
However, when alterations in FM and body 71
composition are sought, energy deficits may be necessary.
13
Pre-season therefore represents 72
a unique opportunity to reverse the negative changes observed in markers of body 73
composition following the off-season through the systematic increase of TL and the provision 74
of individualised dietary regimes. 75
In contrast to the volume of research concerning the impact of pre-season training on 76
parameters of physical fitness,
14,15
a dearth of information appears available on its impact on 77
markers of body composition. Literature examining seasonal changes in the body 78
composition of professional soccer players have typically observed decreases in FM and 79
increases in FFM from the beginning of pre-season to mid-season.
16
However, without a post 80
pre-season assessment of body composition, the role of the pre-season in these changes is 81
unclear. Additionally, studies utilising two-compartment techniques such as skinfolds and 82
bioelectrical impedance analysis (BIA) have returned conflicting results.
7,17,18
Although such 83
techniques represent practical methods within the field, the accuracy in which BF% may be 84
estimated from skinfold thicknesses can vary greatly depending upon the anthropometric 85
equation utilised.
19,20
Dual-energy x-ray absorptiometry (DXA), however, is widely regarded 86
as the criterion reference standard for assessing body composition within team sport athletes 87
given its potential to provide a three-compartmental overview of body composition.
19
88
Nevertheless, the use of DXA within most sports settings is often limited due to its associated 89
logistical and financial costs.
20
90
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To our knowledge, two studies have previously utilised DXA to document body composition 91
changes during the pre-season within elite soccer players.
21,22
In a cohort of 18 A-League 92
soccer players, improvements in body composition were achieved following a ~3-month pre-93
season
.22
Similarly, favourable alterations (decreases/increases in FM/FFM, respectively) 94
were observed within English Premier League players following 6 weeks of pre-season 95
training.
21
However, given the potential impact that differences in culture, competition 96
demands and playing position have upon playing style and training practices,
23
additional 97
research is required to document the changes incurred in body composition during the pre-98
season amongst elite cohorts from varying competitions. Furthermore, the extent to which 99
changes in body composition may be attributed to the TL and EE induced during pre-season 100
remains unclear. Understanding such relationships may be of benefit to support staff working 101
with elite soccer players during the pre-season, and provide valuable information from which 102
to base the prescription of TL and nutritional guidelines. This investigation therefore aimed 103
to expand upon the available literature and document body composition changes induced 104
during the pre-season within players belonging to one of Europe’s leading soccer clubs (FC 105
Barcelona). Accordingly, we sought to: 1) evaluate changes in global and regional markers 106
of body composition over the pre-season period; 2) examine the impact of playing position 107
upon these changes; and 3) explore what proportion of the variability in changes in body 108
composition may be explained by the total EE associated with pre-season training. 109
Methods 110
Participants 111
Twenty male soccer players (age: 25.1±4.1 y; stature: 177.0±6.9 cm; body mass: 73.8±6.0 112
kg) belonging to the first team of FC Barcelona provided informed consent to participate in 113
this study. Players were separated into their outfield playing positions for analyses 114
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(defenders: n=7; midfielders: n=7; forwards: n=6). Over the course of the two competitive 115
seasons evaluated (2014-2015 and 2015-2016), the club achieved considerable success, 116
winning two La Liga titles, two Copa del Rey titles, and one UEFA Champions League title. 117
Whilst assessments of body composition were completed as part of the routine medical 118
screening of players, data procurement and handling conformed to the recommendations 119
outlined within the Declaration of Helsinki and the study received approval from the Ethics 120
Committee for Clinical Research of the Catalan Sports Council. 121
Design 122
Measures of whole-body and regional (upper limb, lower limb, trunk) mass, FM, FFM, and 123
BF% were assessed by DXA (GE Healthcare Lunar, Madison, WI). Assessments were 124
undertaken 38±10 days apart at the start and end of the pre-season during either the 2014-15 125
(n=16) or 2015-16 (n=4) competitive seasons. These timeframes were dictated by the club 126
and reflect previous literature.
18,21
In accordance with standardised protocols that are 127
recognised as best practice, scans were performed and analysed by the same trained operator 128
and were undertaken in a rested and hydrated state.
24
Specifically, players presented to the 129
lab having not undertaken any exercise on the morning of the scans and had refrained from 130
the consumption of food in the 3-4 hours previous.
24
The players had also been instructed to 131
consume fluids ad-libitum prior to scans. The test-retest reliability of the DXA scanner for 132
measurement of whole-body and regional body composition in non-obese adults, with 133
repositioning between scans, has been previously documented.
25
Briefly, the coefficient of 134
variation (CV) for whole-body FM and FFM were 1.0% and 0.5%, respectively. Regional 135
reliability estimates for FM were as follows: upper limbs, 2.8%; lower limbs, 1.6%; and 136
trunk, 2.0%. Regional reliability estimates for FFM were: upper limbs, 1.6%; lower limbs, 137
1.3%; and trunk, 1.0%. 138
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Pre-season training and nutritional practices 139
Pre-season training, as programmed and directed by the coaching staff, was comparable prior 140
to the start of both the 2014-15 (36 sessions, 5 matches) and 2015-16 (33 sessions, 8 matches) 141
competitive seasons. The mean number of on-field training sessions performed was 21±10 142
sessions, with variation attributable to each player’s unique circumstances (date of return to 143
pre-season following international competition, injury, fatigue management etc.). In line 144
with the unique playing and training philosophy embedded at FC Barcelona, training sessions 145
incorporated integrated content whereby tactical, technical, and physical factors were 146
amalgamated.
23
Players’ locomotive activities were recorded during each training session 147
using portable 10-H
Z
Global Positioning System (GPS) units (Viper Pod, Statsports, Northern 148
Ireland). To avoid inter-unit error, each player wore the same device during the entirety of 149
the study period.
26
Following each training session, GPS data were extracted and analysed 150
using propriety software (Viper, Statsports) to derive: total distance (TD); high-speed running 151
distance (HSR; 19.8-25.09 km·h
-1
); sprinting distance (SPR; ≥25.1 km·h
-1
); and number of 152
accelerations (ACC; >3 m·s
-2
) and decelerations (DEC; >3 m·s
-2
). Intensity thresholds were 153
established based upon previous literature and are consistent with those commonly used by 154
professional soccer clubs.
27,28
GPS data were also used to estimate the average metabolic 155
power (AMP; W·kg
-1
), total energy cost (EC; kJ·kg
-1
), and EE (kcal) associated with on-field 156
training sessions according to the approach of di Prampero and Osgnach (2018).
29
In 157
particular, this approach relies on the theoretical construct that metabolic demands can be 158
estimated from the instantaneous speed and acceleration, and the known EC of 159
accelerated/decelerated locomotion which characterise soccer-related activities.
30
Acceptable 160
accuracy and validity have been advocated in support of these metabolic estimates as 161
practical tools in team-sport demands analysis, especially following a recent update of the 162
original model,
31
which now differentiates between the EC of running and walking, and also 163
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considers the cost of air resistance. The full GPS data set included 18 players with weekly 164
analyses inclusive only of those who completed ≥75% of on-field sessions for that week. 165
Nutritional practices were informed by the club’s nutritional adviser and remained consistent 166
across each pre-season. The general objective of the nutritional advice provided to the 167
players was to support an optimal adaptation to the enhanced TL induced during pre-season 168
as well as promote decreases/increases in FM/FFM, respectively. Additionally, players were 169
provided with individualised nutritional goals based upon the result of their baseline DXA 170
measurement. Subject to the specific nutritional goals of the player, recommended 171
macronutrient intakes were as follows: carbohydrate (4.0-6.0 g/kg/day); protein (1.8-2.0 172
g/kg/day); and fat (1.0 g/kg/day). Based upon these guidelines, the recommended daily EI 173
was ~2795 kcal (range: 2648-3080 kcal). During pre-season, all meals and snacks were 174
provided by the club and players were encouraged to work closely with the club’s nutritional 175
advisor to translate their recommended nutrient guidelines into food equivalents. 176
Statistical Analysis 177
Prior to the use of parametric statistical test procedures, normality of distribution and 178
homogeneity of variance were verified using Shapiro-Wilk’s and Levene’s tests, respectively. 179
Changes in estimates of body composition were assessed using one-way analysis of variance 180
(ANOVA) with two-way ANOVAs (factor: time; playing position) used to examine whether 181
the changes achieved in estimates of body composition were related to playing position. 182
Mean standardised differences are reported as Cohen’s d with the following criteria used to 183
interpret the practical significance of findings: trivial, <0.2; small, 0.21-0.6; moderate, 0.61-184
1.2; large, 1.21-1.99; and very large, ≥2.0.
32
In addition, the smallest worthwhile change 185
(SWC) was calculated for each variable as the between-player standard deviation multiplied 186
by 0.2.
33
To assess the relationship between independent (total EE of pre-season training) 187
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and dependent (ΔFM, ΔFFM, ΔBF%) variables, multiple linear regressions were performed. 188
Prior to regression analyses, Pearson’s correlation coefficients (r) were used to indicate 189
whether the magnitude of the relationship between variables was small (0.10-0.29), moderate 190
(0.30-0.49), large (0.50-0.69), very large (0.70-0.89), and nearly perfect (≥0.90).
32
Data are 191
presented as means and standard deviations (mean±SD). Weekly TL and EE data are 192
presented for descriptive purposes only. Statistical procedures were completed using 193
Statistical Package for Social Sciences (SPSS 22.0, IBM, USA) and statistical significance 194
was set at P<0.05. 195
Results 196
Changes in global and regional markers of body composition 197
Table 1 reports the changes in markers of body composition between the beginning and end 198
of pre-season. 199
Whole-body total mass remained unchanged following pre-season (d=0.00; 95% CI: -0.66 to 200
0.66 kg; P=0.99). When analysed regionally, no differences were observed in total mass of 201
the upper limbs (d=0.37; 95% CI: -0.15 to 0.02 kg; P=0.11), lower limbs (d=0.19; 95% CI: -202
0.36 to 0.15 kg; P=0.41), or trunk (d=0.34; 95% CI: -0.12 to 0.76 kg; P=0.14). 203
Moderate significant reductions in whole-body FM (d=0.85; 95% CI: -0.47 to -0.28 kg; 204
P=0.001) were observed following pre-season with reductions occurring in the upper limbs 205
(d=0.69; 95% CI: -0.18 to -0.04 kg; P=0.006), lower limbs (d=0.97; 95% CI: -0.53 to -0.19 206
kg; P<0.001) and trunk (d=0.70; 95% CI: -0.91 to -0.18 kg; P=0.006). 207
Moderate significant increases in whole-body FFM (d=0.87; 95% CI: 0.48 to 1.59 kg; 208
P=0.001) were mediated through increases in FFM of the lower limbs (d=0.51; 95% CI: 0.02 209
to 0.48 kg; P=0.03) and trunk (d=1.17; 95% CI: 0.52 to 1.21 kg; P<0.001). The FFM of the 210
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upper limbs remained unchanged (d=0.22; 95% CI: -0.05 to 0.13 kg; P=0.34) following pre-211
season. 212
Moderate significant decreases occurred in whole-body BF% following pre-season (d=0.94; 213
95% CI: -2.2 to -0.7%; P<0.001) with reductions occurring in the upper limbs (d=0.68; 95% 214
CI: -2.1 to -0.4%; P=0.006), lower limbs (d=1.03; 95% CI: -1.89 to -0.70%; P<0.001), and 215
trunk (d=0.87; 95% CI: -2.91 to -0.87%; P=0.001). 216
No significant inter-positional differences were observed for any global (P≥0.10; d≤0.50) or 217
regional (P≥0.08; d≤0.59) estimate of body composition across the pre-season period. 218
Weekly training load (TL) and energy cost (EC) of on-field training sessions 219
An overview of the TL accumulated across weeks 1-6 of the pre-season is presented in Table 220
2 whilst the mean EC of on-field training sessions during each of these weeks is presented 221
within Table 3. The data presented pertains to on-field training sessions only and does not 222
include data from pre-season match play. 223
Relationship between changes in body composition and the total energy expenditure (EE) 224
associated with pre-season training 225
The total EE of pre-season training was 9369±5424 kcal. Total EE was significantly 226
correlated with ΔFM (r=0.65, P=0.002), ΔFFM (r=0.46, P=0.032), and ΔBF% (r=0.67, 227
P=0.002). The total EE of pre-season training accounted for 42%, 21%, and 45% of the 228
variance in ΔFM, ΔFFM, and ΔBF%, respectively. 229
Discussion 230
We sought to investigate the changes incurred in global and regional markers of body 231
composition during the pre-season within a cohort of elite male soccer players. At the global 232
level, reductions in BF% were mediated through reductions in FM and increases in FFM. 233
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Regionally, reductions in the FM of the upper limbs, lower limbs and trunk were 234
accompanied by concomitant increases in the FFM of the lower limbs and trunk. Moreover, 235
the changes observed in all global and regional estimates of body composition were similar 236
between playing positions. An additional aim was to identify what proportion of the 237
variability in changes in body composition could be explained by the total EE associated with 238
pre-season training. The total EE of pre-season training accounted for 42%, 21%, and 45% 239
of the variance in ΔFM, ΔFFM, and ΔBF%, respectively. 240
As evidenced, pre-season presents a suitable time by which favourable alterations in body 241
composition may be achieved within elite soccer players. Our findings support those 242
observed within English Premier League players whereby reductions (~2%) in BF% were 243
achieved following a 6-week pre-season.
21
Conversely, the FFM and BF% of French League 244
1 players remained unchanged following pre-season.
17
Although we are unable to discount 245
whether such discrepancies are simply an artefact of the different assessment methods, one 246
explanation may reside in potential disparities in the pre-season duration. In the present 247
study, measurements were obtained ~6 weeks apart; however, the duration of the pre-season 248
employed by Carling and Orhant was not noted.
17
The duration of pre-season employed 249
within the aforementioned study may therefore have been insufficient to promote such 250
changes; however, without such information, this remains speculative. Another explanation 251
likely relates to the type and intensity of the pre-season training stimulus. As shown, 252
differences in the total EE associated with pre-season training accounted for 42% of the 253
variance in ΔFM. The increased energy cost of training reflects the up-regulation of 254
oxidative metabolism, with exercise intensity representing the greatest moderator of substrate 255
utilization.
34
Additionally, the intermittent nature of soccer-specific exercise has been found 256
to promote a high rate of lipolysis and the release of free fatty acids into the blood.
35
In the 257
context of the studied club, a unique training philosophy is embedded whereby there is a 258
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marked disposition for on-field game-related training, through which tactical, technical and 259
physical factors are amalgamated.
23
Conversely, only 21% of the variance in ΔFFM was 260
attributable to the total EE associated with pre-season training. This is perhaps unsurprising 261
given that training-induced increases in muscle hypertrophy are not driven by EE per se.
36
262
As discussed, favourable alterations in DXA-derived estimates of body composition have 263
previously been reported within elite English Premier League players following ~6-weeks of 264
pre-season training.
21
Nevertheless, as differences in culture and competition demands may 265
result in distinct training practices, data derived from additional competitions is warranted.
23
266
Additionally, the present investigation is the first to report body composition changes induced 267
during pre-season within elite soccer players, in relation to metrics of TL. This represents an 268
important contribution to the literature as indications of TL and the associated EE are 269
necessary when interpreting alterations in body composition.
11
When considering the TL 270
accumulated across each week of pre-season, the mean weekly TD and HSR distance 271
observed in the present study was 23193 m and 1048 m, respectively. Such values exceed 272
those reported for elite players during the in-season,
12
thus supporting observations of 273
enhanced TL during the pre-season in comparison to the in-season.
9
Interestingly, the mean 274
weekly TD observed within the present study is substantially lower than that reported for elite 275
English Premier League players during pre-season.
9
As FC Barcelona adopt a unique playing 276
style, such discrepancies in loading patterns likely relate to differences in training practices.
23
277
Based upon measures of metabolic power, the mean EC of on-field training during weeks 1-3 278
was ~36 kJ·kg
-1
.
29
Whilst such figures remain below those associated with match play,
27
they 279
exceed the ~25 kJ·kg
-1
reported for elite players during the in-season.
37
Conversely, the 280
reduced training volume observed during weeks 4-6 resulted in a mean EC of training more 281
closely aligned with that of the in-season. A likely explanation for this pertains to the more 282
frequent scheduling of matches during the latter stages of pre-season. Whilst we report TL 283
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and EE data to aid the interpretation of our findings, this data relates to on-field sessions only, 284
and is not reflective of gym-based training sessions or the load associated with match play. 285
Consequently, a conservative account of the demands imposed during pre-season is 286
presented. Nevertheless, given that the estimated EE of match play ranges from 1200-1500 287
kcal,
27
the greater match participation exhibited during weeks 4-6 is likely to have 288
compensated for the reduced training volume. This represents an important consideration for 289
applied practitioners preparing athletes during the pre-season, as the scheduling of matches 290
will impact upon the programming of training, and will ultimately contribute towards their 291
physical conditioning. 292
Several limitations warrant consideration when interpreting these results. Whilst we provide 293
surrogate markers of EE to contextualise our findings, the limitations of the adopted approach 294
should be acknowledged in comparison to the doubly labelled water method. Additionally, 295
although we provide details concerning the nutritional guidelines provided to the players, we 296
are unable to confirm their actual EI. Future research incorporating direct measurements of 297
EE and EI is therefore necessary in order to fully examine the interaction of energy balance 298
and body composition changes within elite soccer players during the pre-season. Another 299
limitation relates to our relatively small sample size, a challenge commonly encountered 300
when conducting applied research with elite cohorts. In the context of the present 301
investigation, the two studied pre-seasons coincided with international competitions (FIFA 302
World Cup 2014 and CONMEBOL Copa América 2015). Consequently, although we report 303
the impact of ~6 weeks of pre-season (38±10 days) on markers of body composition, the 304
return of players to the club for pre-season training was dictated by the player’s individual 305
commitments to their national teams. This represents an important consideration in the 306
applied setting as the timing of a player’s return will influence the programming of pre-307
season training. Future research may wish to examine the impact that such logistical 308
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challenges have upon the loading patterns programmed during the pre-season and their 309
subsequent impact upon markers of physical performance and body composition. 310
The present findings provide additional evidence supporting the pre-season to be a suitable 311
period for elite soccer players to achieve concomitant reductions/increases in FM/FFM, 312
respectively. These findings have practical implications for support staff working to prepare 313
elite soccer players for the upcoming competitive season and further demonstrate the 314
potential for favourable alterations in body composition to be achieved during a ~6-week pre-315
season period. 316
Acknowledgements 317
The authors wish to express their gratitude to all the players who participated in this 318
investigation and would like to thank FC Barcelona for their cooperation and input to this 319
article. 320
Submission statement 321
The data reported in this manuscript have not been published elsewhere and the manuscript is 322
not under consideration for publication in another journal. 323
Authors’ contributions 324
All authors have participated in the research and/or article preparation. All authors have 325
approved the final submitted article. Study concept and design: GPM, FD, VU; Data 326
collection: FD, AL, AGD, EP; Data analysis: GPM, ADI, VU; Manuscript development: 327
GPM, VU; Contribution to manuscript: FD, AL, AGD, EP, ADI. 328
Ethics statement 329
The study received approval from the Ethics Committee for Clinical Research of the Catalan 330
Sports Council and all players provided informed written consent to participate in the study. 331
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Disclosure of interest 332
The authors report no conflicts of interest. 333
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Table 1. Changes in global (whole-body) and regional (upper limbs, lower limbs, trunk) markers of body composition between start and end of pre-season within outfield
players (n = 20).
Defenders (n = 7) Midfielders (n = 7) Forwards (n = 6) All players (n = 20) SWC
Start End Start End Start End Start End
Global
Whole-body
Total mass (kg) 75.37 ± 5.64 74.79 ± 5.85 72.34 ± 4.35 73.76 ± 4.64 73.51 ± 8.15 75.25 ± 9.14 73.75 ± 5.93 73.75 ± 6.35 1.19
FM (kg) 9.84 ± 1.89 8.62 ± 1.77 11.55 ± 2.07 10.43 ± 1.65 10.40 ± 1.36 10.04 ± 1.75 10.60 ± 1.88 9.56 ± 1.81
¥
0.38
FFM (kg) 61.83 ± 4.58 62.49 ± 4.47 57.36 ± 2.72 59.81 ± 3.10 59.54 ± 7.58 61.55 ± 7.99 59.58 ± 5.27 60.61 ± 5.18
¥
1.05
BF% (%) 13.0 ± 1.9 11.5 ± 1.7 16.0 ± 1.8 14.1 ± 1.5 14.0 ± 2.3 13.4 ± 2.0 14.4 ± 2.3 12.9 ± 2.0
#
0.5
Regional
Upper limbs
Total mass (kg) 8.54 ± 0.56 8.41 ± 0.54 8.01 ± 0.59 8.18 ± 0.63 8.20 ± 0.98 8.31 ± 1.06 8.25 ± 0.72 8.19 ± 0.73 0.14
FM (kg) 0.98 ± 0.12 0.86 ± 0.11 1.13 ± 0.16 1.00 ± 0.19 0.94 ± 0.11 0.89 ± 0.15 1.02 ± 0.15 0.91 ± 0.14
¥
0.03
FFM (kg) 7.10 ± 0.54 7.09 ± 0.47 6.47 ± 0.47 6.75 ± 0.46 6.83 ± 0.98 6.97 ± 1.04 6.80 ± 0.70 6.84 ± 0.66 0.14
BF% (%) 11.6 ± 1.6 10.2 ± 1.2 14.0 ± 1.5 12.1 ± 1.7 11.6 ± 2.4 10.9 ± 2.3 12.4 ± 2.1 11.1 ± 1.9
¥
0.4
Lower limbs
Total mass (kg) 27.81 ± 2.33 27.46 ± 2.14 26.72 ± 1.95 27.21 ± 2.30 27.23 ± 2.52 27.92 ± 3.25 27.25 ± 2.19 27.15 ± 2.35 0.44
FM (kg) 3.36 ± 0.69 2.99 ± 0.55 4.05 ± 0.64 3.71 ± 0.69 3.51 ± 0.52 3.37 ± 0.42 3.65 ± 0.67 3.29 ± 0.58
#
0.13
FFM (kg) 22.91 ± 2.20 22.93 ± 1.92 21.25 ± 1.43 22.04 ± 1.63 22.24 ± 2.46 23.02 ± 3.03 22.13 ± 2.07 22.38 ± 2.08
*
0.41
BF% (%) 12.1 ± 2.6 10.9 ± 1.9 15.1 ± 1.8 13.6 ± 1.6 13.0 ± 2.5 12.2 ± 2.0 13.4 ± 2.5 12.1 ± 2.0
#
0.5
Trunk
Total mass (kg) 33.41 ± 3.21 33.45 ± 3.41 31.81 ± 2.16 32.70 ± 2.01 32.48 ± 4.43 33.52 ± 4.56 32.57 ± 3.22 32.89 ± 3.36 0.64
FM (kg) 4.50 ± 1.12 3.81 ± 1.18 5.32 ± 1.43 4.71 ± 0.90 4.95 ± 1.12 4.79 ± 1.30 4.92 ± 1.23 4.38 ± 1.21
¥
0.25
FFM (kg) 27.82 ± 2.29 28.56 ± 2.31 25.46 ± 1.37 26.93 ± 1.35 26.45 ± 3.90 27.62 ± 3.69 26.58 ± 2.70 27.44 ± 2.55
#
0.54
BF% (%) 13.4 ± 2.3 11.2 ± 2.3 16.6 ± 3.4 14.3 ± 2.0 15.3 ± 3.3 14.3 ± 2.8 15.1 ± 3.2 13.2 ± 2.7
¥
0.6
Data presented as mean ± SD.
FM, fat mass; FFM, fat-free mass; BF%, body fat per cent; SWC, smallest worthwhile change.
*
significantly different from start of pre-season (P < 0.05)
¥
significantly different from start of pre-season (P < 0.01)
#
significantly different from start of pre-season (P < 0.001)
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Table 2. Accumulated training loads (TL) reported across each 1-week microcycle of the pre-season
Duration
(min) TD
(m) HSR
(m) SPR
(m) ACC
(n) DEC
(n)
Week 1
DEF (n = 1) 565 ± 0 32752 ± 0 942 ± 0 61 ± 0 938 ± 0 860 ± 0
MID (n = 3) 535 ± 45 30219 ± 3568 1467 ± 1307 112 ± 157 896 ± 77 842 ± 81
ATT (n = 2) 655 ± 346 27740 ± 2161 830 ± 337 85 ± 74 250 ± 45 273 ± 18
ALL (n = 6) 580 ± 168 29815 ± 3094 1167 ± 903 95 ± 107 688 ± 344 655 ± 301
Week 2
DEF (n = 2) 529 ± 250 31354 ± 14137 907 ± 341 130 ± 93 1035 ± 540 953 ± 538
MID (n = 7) 544 ± 176 31013 ± 10533 1736 ± 1439 76 ± 79 962 ± 388 870 ± 431
ATT (n = 3) 262 ± 114 14507 ± 5617 523 ± 342 65 ± 58 262 ± 311 281 ± 270
ALL (n = 12) 471 ± 202 26943 ± 11861 1294 ± 1215 82 ± 73 799 ± 482 737 ± 466
Week 3
DEF (n = 2) 645 ± 175 36580 ± 6205 1061 ± 1 231 ± 123 1049 ± 268 961 ± 212
MID (n = 7) 739 ± 39 39933 ± 3531 2144 ± 1502 32 ± 27 1114 ± 158 1079 ± 109
ATT (n = 4) 363 ± 301 21370 ± 15834 832 ± 580 144 ± 174 467 ± 529 394 ± 534
ALL (n = 13) 609 ± 237 33705 ± 12118 1574 ± 1277 97 ± 124 905 ± 426 850 ± 428
Week 4
DEF (n = 5) 215 ± 108 12437 ± 6327 454 ± 229 84 ± 161 351 ± 164 323 ± 158
MID (n = 7) 332 ± 105 17644 ± 6358 976 ± 658 71 ± 75 483 ± 195 446 ± 204
ATT (n = 4) 258 ± 102 16104 ± 5225 653 ± 295 153 ± 134 318 ± 248 304 ± 225
ALL (n = 16) 277 ± 111 15632 ± 6137 732 ± 510 96 ± 118 400 ± 201 372 ± 195
Week 5
DEF (n = 5) 242 ± 51 14835 ± 2722 424 ± 124 88 ± 92 410 ± 79 377 ± 67
MID (n = 7) 248 ± 97 14762 ± 5684 795 ± 641 16 ± 14 383 ± 146 383 ± 144
ATT (n = 4) 204 ± 109 12231 ± 6799 520 ± 146 83 ± 105 274 ± 218 277 ± 203
ALL (n = 16) 235 ± 85 14152 ± 5046 611 ± 450 55 ± 76 364 ± 151 355 ± 141
Week 6
DEF (n = 5) 386 ± 44 22468 ± 2292 895 ± 169 228 ± 87 572 ± 43 535 ± 59
MID (n = 7) 379 ± 84 20365 ± 5572 956 ± 502 61 ± 66 494 ± 186 474 ± 184
ATT (n = 4) 256 ± 175 13323 ± 8547 854 ± 1146 121 ± 65 301 ± 284 279 ± 266
ALL (n = 16) 345 ± 119 18912 ± 6772 908 ± 657 128 ± 98 460 ± 214 435 ± 206
Data presented as mean ± SD and are stratified by playing position (DEF, defender; MID, midfielder; ATT, attacker; ALL, all positions).
TD, total distance; HSR, high-speed running distance (m >19.8 km·h
-1
); SPR, sprinting distance (m >25.2 km·h
-1
); ACC, number of accelerations (>3 m·s
-2
); DEC, number of
decelerations (<-3 m·s
-2
)
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Table 3. Mean estimated energy cost of on-field training sessions during each 1-week microcycle of the pre-
season
AMP
(W·kg
-1
) EC
(kJ·kg
-1
) EE
(kcal)
Week 1
DEF (n = 1) 5.5 ± 0.5 46.1 ± 12.4 824 ± 222
MID (n = 3) 5.5 ± 0.2 42.8 ± 12.3 727 ± 223
ATT (n = 2) 6.8 ± 0.7 31.9 ± 11.1 581 ± 201
ALL (n = 6) 5.9 ± 0.2 36.6 ± 10.8 641 ± 179
Week 2
DEF (n = 2) 5.6 ± 0.5 40.0 ± 14.4 715 ± 258
MID (n = 7) 5.5 ± 0.4 36.8 ± 9.2 636 ± 162
ATT (n = 3) 5.6 ± 1.2 26.7 ± 11.6 435 ± 189
ALL (n = 12) 5.5 ± 0.5 35.4 ± 8.4 611 ± 148
Week 3
DEF (n = 2) 5.0 ± 1.0 46.7 ± 22.9 836 ± 409
MID (n = 7) 5.0 ± 0.8 46.1 ± 21.1 796 ± 363
ATT (n = 4) 5.6 ± 0.8 40.7 ± 27.9 644 ± 400
ALL (n = 13) 5.2 ± 0.8 37.5 ± 24.0 650 ± 399
Week 4
DEF (n = 5) 5.0 ± 0.4 23.4 ± 9.8 421 ± 171
MID (n = 7) 4.9 ± 0.5 27.4 ± 13.7 477 ± 239
ATT (n = 4) 6.4 ± 1.8 22.7 ± 8.7 368 ± 134
ALL (n = 16) 6.1 ± 1.7 24.6 ± 10.2 418 ± 172
Week 5
DEF (n = 5) 5.6 ± 0.1 38.6 ± 16.3 708 ± 310
MID (n = 7) 5.4 ± 0.5 43.1 ± 17.2 780 ± 258
ATT (n = 4) 6.0 ± 1.3 25.7 ± 19.7 422 ± 314
ALL (n = 16) 6.0 ± 1.3 24.2 ± 16.9 418 ± 302
Week 6
DEF (n = 5) 5.3 ± 1.2 26.8 ± 7.1 490 ± 134
MID (n = 7) 5.1 ± 1.2 25.1 ± 7.8 433 ± 135
ATT (n = 4) 5.1 ± 0.9 23.3 ± 5.8 424 ± 114
ALL (n = 16) 5.2 ± 1.2 25.2 ± 7.0 447 ± 129
Data presented as mean ± SD and are stratified by playing position (DEF, defender; MID, midfielder; ATT,
attacker; ALL, all positions).
AMP, average metabolic power; EC, energy cost; EE, energy expenditure.
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Signed by all authors as follows:
Gary Paul McEwan G. McEwan 27/07/2020
Franchek Drobnic F. Drobnic 27/07/2020
Antonia Lizarraga A. Lizarraga 27/07/2020
Antonio Gómez Díaz A. Gómez Díaz 27/07/2020
Eduard Pons E. Pons 27/07/2020
Antonio Dello Iacono A. Dello Iacono 27/07/2020
Viswanath Unnithan V. Unnithan 27/07/2020
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