Inter- and intra-microcycle external load analysis in female professional soccer players: A playing position approach.

This study analyzes the inter- and intra-differences in external load across the microcycle in professional female soccer players. External load during four consecutive microcycles (i.e., M1, M2, M3, and M4) and training sessions (i.e., MD-4, MD-3, MD-2, and MD-1) and a match day (i.e., MD) were registered in seventeen female professional soccer players (age: 26.3 ± 4.6 years; height: 166.3 ± 6.1 cm; body mass: 59.8 ± 6.8 kg; and body mass index: 21.6 ± 1.7 kg·m-2) who belonged to the same team in Spanish first division. A 10-Hz GPS that integrated a 100-Hz triaxial accelerometer was used to register external load. The results showed lower decelerations in M2 compared to M1 and M3 (p < 0.05), lower high-intensity distance (>16.0 km·h-1) in M3 vs. M2, and greater relative sprint distance (>21.0 km·min-1) in M4 vs. M1 and M3 (p < 0.05). MD-3 registered the highest load for all variables (p < 0.05). Forwards (FWs) performed (p < 0.05) significantly more sprints (meters and number > 21.0 km·h-1) than central midfielders (CMs) and central defenders (CDs) in MD-2 and MD. Both, fitness and conditioning staff should pay special attention to the external loads for each playing position in training sessions to optimize the training process.

Introduction

The analysis of external load encountered by female soccer players throughout match play has gained great attention in recent years [1-3]. Previous research reported that elite female soccer players cover around 10000 m during a match [4,5], of which almost 300 m are covered sprinting (20.1–32.0 km·h−1) [3]. These athletes perform close to 125 high-intensity actions, with an average duration of 2.3 s each, during a match [6]. Likewise, the literature shows that match play is the most demanding session of the microcycle [7]. As such, strength and conditioning staff could consider this aspect when planning a team’s training strategies. In addition, coaches should attend to the quantification of external loads imposed by the weekly training microcycle to understand the dose-response nature of the training process and optimize player performance [8].

One of the main goals of coaching staff in elite soccer is to learn the best training periodization to improve players’ physical fitness and reduce injury risk, with the intent of optimizing the team’s performance [9]. In this sense, some periodization models have been used [10], most of which coincide with proposed high load reduction during the session prior to a competition [11], confirming the concept of tapering [12]. The typical microcycle, when playing a match once a week, is composed of strength, endurance, and speed acquisition training sessions located in the central days of the microcycle in male [13] and female [2] professional soccer players. This distribution across the week allows players to follow the horizontal alternation principle, which consists of maximizing a particular physical capacity while the others recover [14]. As such, lower external training load (total distance and high-speed distance) in comparison to the match day load has been reported in professional male [15] and female [16] soccer players. External load on acquisition microcycle days is characterized by higher distance covered (total and relative) and time > 90% of maximal heart rate on endurance days and high-sprint and high-intensity distance on speed days [14]. Although training periodization is relevant to enhance a team’s performance, the organization of the microcycle seems to be a more realistic strategy due to the chaotic nature of women’s soccer [15]. Additionally, other authors have demonstrated a higher coefficient of variability in the distances covered at high intensity (20.8%, 26.1%, and 54.5%) and sprinting (65.1%, 94.2%, and 100.2%) in neuromuscular, endurance, and speed sessions, respectively [17].

Inappropriately training loads can cause overuse injuries [18] and increased injury risk is associated with spikes in workload (i.e., overloading) and low chronic workloads (i.e., underloading) [19] so. Given that quantification of the workload has become an essential aspect in soccer performance [11]. Some external factors, such as sex [20], performance level [9], playing surface, and/or match outcomes [3] could influence the external load encountered by female players during matches. However, playing position is considered the most influential variable on external load [21], mainly in terms of high-intensity actions (e.g., sprints or jumps). In this sense, elite female defenders covered significantly less high-intensity distance (1260 ± 110 m) than midfielders and attackers (1650 ± 110 and 1630 ± 110 km, respectively) [10]. In addition, attackers were able to sprint greater distances compared to defenders (0.52 ± 0.03 km vs. 0.33 ± 0.05 km) [9]. Understanding the external training and match loads in female soccer players according to position would allow coaching staff to establish specific training sessions and an adequate distribution of training content within the microcycle.

As research on the analysis of external training and match loads in female professional soccer players is scarce, the aim of this study was to analyze the inter- or intra-differences in external load across the microcycle and compare the external load considering playing positions among microcycles and between training sessions and a match day in professional female soccer players. We hypothesized that there is similar distribution of external loads between each microcycle, but that differences could exist in each training session and match day external load according to playing position.

Material and methods

Study design

An observational and descriptive design was implemented to analyze the inter- and intra-differences in the external load encountered by female professional soccer players during four consecutive microcycles, according to playing position. This study was carried out during the 2019–2020 in-season period when each microcycle was composed of four training sessions and one official match; thus, 16 training sessions and four matches (i.e., 340 individual observations) were registered. Microcycle 1 was performed in the middle of the first part of the season, 4 weeks after the end of the pre-season and demanding similar workload in all players. Training sessions were conducted on the same playing surface (third generation artificial turf) and at the same time (4:30 P.M.). Matches were played on four pitches with similar dimensions (100 × 64 m) and artificial surfaces, comprising two matches at home and two matches away. Two matches were won and two matches lost. During the training sessions, the researchers did not influence the training exercises.

Participants

Seventeen female professional soccer players (age: 26.3 ± 4.6 years; height: 166.3 ± 6.1 cm; body mass: 59.8 ± 6.8 kg; and body mass index: 21.6 ± 1.7 kg·m-2) who belonged to the same team in Spanish first division participated in this study. Because the team played in a 1–5–3–2 formation during the four official matches, players were classified according to their playing position: central backs (CBs, n = 3), full backs (FBs, n = 3), central midfielders (CMs, n = 6), and forwards (FWs, n = 5). Goalkeepers were excluded from the subsequent analysis due to their specific role. Players were excluded from further analysis if they did not complete a full competitive match or if they had suffered an injury in the 2 months prior to the investigation. Before beginning the study, subjects were informed of the study’s objectives, risks, and benefits, and signed the informed consent form. The study was conducted according to the requirements of the Declaration of Helsinki and was approved by the ethics committee of ***for blinded purposes*** code: 004–2021.

Procedures

External loads were registered during the 4-week period according to the microcycle number (microcycle 1 = M1; microcycle 2 = M2; microcycle 3 = M3; and microcycle 4 = M4) and training session (i.e., days before match day [MD], MD-4, MD-3, MD-2, MD-1, and MD) [15,22]. The usual distribution through microcycle was the following: MD-4: recovery session and general resistance in gym; MD-3: specific resistance and endurance session (i.e., plyometric drills, strength stations and small and medium sided games); MD-2: speed and tactical approximation (i.e., sprint running and large small sided games); and MD-1: activation session (reaction speed and small sided games) similar distribution of male soccer players [14,17] and development/maintenance of the main three physical capacities. Tactical task (i.e., conditioned games in medium and large spaces simulating competition situations, superiorities and inferiorities) represents 20%, 40% and 40% in MD-4, MD-3 and MD-2 respectively. The external load of the microcycle was analyzed only in those players who played ≥ 60 min in MD. In all training sessions and match play, the players performed a similar standardized 15–20 min warm-up that included running, dribbling, and specific tasks (drills).

The external loads across the training sessions (n = 16) and matches (n = 4) were registered individually for each player using a 10-Hz GPS that integrated a 100-Hz triaxial accelerometer (WIMU PRO, RealTrack Systems, Almería, Spain). This technology has been previously used in soccer research on activity-demand profiles [23] and reported high levels of validity and reliability [24]. To avoid inter-unit variability, each player wore only their assigned unit, which was inserted into the manufacturer-provided vest that holds the receiver tightly between the scapulae. The units were activated 15 min before the start of each training session and match. Following each training session and match, GPS data were downloaded using the specific software package (WIMU SPRO, Almería, Spain) on a personal computer and exported for further analysis. In the absence of unanimity in the determination of thresholds in female soccer players [25], total distance (TD; in meters), relative distance (RD; in meters/minute), high-intensity distance (HID; meters and m·min-1 > 16.0 km·h-1), sprint distance (SPD; meters, number, and m·min-1 > 21.0 km·h-1), acceleration (ACC; number and m·min-1), deceleration (DCC; number and m·min-1), and maximal speed (km·h-1) were registered. In addition, player load (PL; AU·min-1) was computed. The average number of satellites registering data during the measurements was 9.1±1.0 and horizontal dilution of precision was 0.96.

Statistical analysis

Results are presented as mean ± standard deviation (SD). After confirming the normal distribution of the data, a repeated measure analysis of variance (ANOVA) was conducted to compare the external load of players among each microcycle and each training session and match play. In addition, one-way ANOVA was used to analyze the external load differences among playing positions (i.e., CB, FB, CM, and FW) in each training session and on each match day. When significant differences were obtained, Bonferroni post hoc tests were used. The coefficient of variation (CV) was quantified to assess the variation within the microcycle, training sessions, and match day. Statistical analysis was conducted using SPSS version 25.0 and the significance level was set at p < 0.05.

Results

The external loads imposed on professional female soccer players during four consecutive microcycles are shown in Table 1. M1 showed significantly (p < 0.05) lower ACC and DCC distances compared to the other three microcycles, whereas during M3, significantly fewer meters of HID (p < 0.05) were observed than in M2. No significant differences in TD, SPD (meters and number), and PL were observed among microcycles. The CVs for each microcycle were 9.4%, 11.8%, 11.1%, and 7.7% for RD; 17.6%, 30.5%, 21.81%, and 18.9% for HID; 4.2%, 6.4%, 6.4%, and 4.8% for ACC; and 4.2%, 6.9%, 7.2%, and 4.8% for DCC in M1, M2, M3, and M4, respectively.

Table 1

Mean external load of four consecutive microcycles.

	TD (m)	RD (m·min-1)	HID (m)	HID (m·min-1)	SPD (m)	SPD (m·min-1)	SPD (n°)	Maximal Velocity (km·h-1)	ACC (m·min-1)	DCC (m·min-1)	PL (m·min-1)
M1	21942±4488	67.5±7.4	498.1±390.2	6.0±4.5	305.2±181.1	3.7±1.4 *†	17.8±11.5	23.2±1.4	36.7±1.9	36.8±1.5 †	0.8±0.1
M2	24139±6044	71.5±8.8	545.4±338.6	6.3±3.7	454.4±247.8	5.5±2.7	23.2±15.0	24.8±1.0	35.5±2.2	35.15±1.8	0.8±0.2
M3	22414±4774	67.1±8.2	504.2±353.8	5.8±4.0	325.2±122.7	3.4±2.6 *†	16.0±6.6	24.0±2.0	36.4±1.7	36.8±1.3†	0.9±0.1
M4	24251±5027	65.1±5.0	445.4±402.2	5.1±4.4	426.3±217.5	4.9±2.4	20.1±10.4	23.7±1.0	35.9±1.5	35.5±1.5	0.8±0.1

Data are presented according to microcycle: M1 = Microcicle 1; M2 = Microcicle 2; M3 = Microcicle 3; M4 = Microcicle 4; TD = total distance; HID = high intensity distance; SPD = sprint; ACC = accelerations; DCC = decelerations; PL = player Load.

* = denotes difference from M4

† = denotes difference from M2.

Analysis of external load of the training sessions and matches demonstrated that training session MD-3 presented a significantly higher load (p < 0.05) for all external variables (Table 2). All training sessions showed significantly (p < 0.05) less external load than MD except ACC and DCC, which were significantly higher (p < 0.05) compared to MD. The CV for each training session is reported in Table 2.

Table 2

Mean external load of training sessions and match day of four consecutive microcycles.

	TD (m)	RD (m·min-1)	HID (m)	HID (m·min-1)	SPD (m)	SPD (m·min-1)	SPD (n°)	Maximal velocity (km·h-1)	ACC (m·min-1)	DCC (m·min-1)	PL (AU·min-1)
MD-4	4817 ± 407*†^	57.3 ± 4.7*†	288.1 ± 139.9	3.3 ± 1.6 *†	52.3 ± 6.2*†^	0.6 ± 0.4*†^	2.6 ± 1.2*†	23.4 ± 0.3*†^	38.1 ± 1.5*†‡^	38.1 ± 0.4*†^	0.8 ± 0.1*†^
CV (%)	5.8	7.1	47.6	48.0	107.2	83.7	39.9	12.3	7.1	7.1	6.5
MD-3	5952 ± 727†	75.4 ± 8.5†	699.4 ± 290.1	8.7 ± 3.3 †	151.7 ± 20.3†	1.7 ± 0.8	7.3 ± 3.7†	25.0 ± 0.3†	35.7 ± 2.2†	35.2 ± 0.5†	0.9 ± 0.2†
CV (%)	24.1	10.9	41.5	38.8	31.5	59.9	14.9	3.6	8.3	8.6	15.2
MD-2	4682 ± 221*†	54.3 ± 3.4*†	420.6 ± 199.3	4.7 ± 2.2*†	57.0 ± 9.5*†	0.6 ± 0.2	3.4 ± 1.9*†	23.9 ± 0.5*†	39.2 ± 1.3*†	39.2 ± 0.4*†	0.7 ± 0.1*†
CV (%)	15.3	8.1	47.4	47.0	28.8	17.8	23.2	2.6	8.1	8.1	10.2
MD-1	4083 ± 414*†‡	55.3 ± 4.7*†	215.6 ± 194.9	2.9 ± 2.9 *†	24.8 ± 4.2*†‡	0.3 ± 0.3 *†	1.9 ± 1.2*†	21.9 ± 0.3*†‡	37.0 ± 1.5†‡	37.0 ± 0.4*†‡	0.8 ± 0.1*†‡
CV (%)	31.9	15.5	90.4	99.8	89.8	59.1	88.2	7.3	24.7	24.7	27.1
MD	9347 ± 1013*	96.3 ± 8.8*	1110.5 ± 331.8	11.9 ± 3.6 *	235.1 ± 20.6*	2.6 ± 1.8	13.4 ± 4*	25.3 ± 0.3*	31.7 ± 1.6*	31.7 ± 0.4*	1.3 ± 0.2*
CV (%)	3.7	5.5	30.8	9.9	6.5	41.9	9.1	2.5	4.0	4.1	3.2

Data are presented according to days to match: TD = total distance; HID = High intensity distance; SPD = sprint; ACC = accelerations; DCC = decelerations; PL = player Load.

* = denotes difference from MD-3

† = denotes difference from MD

‡ denotes difference from MD-2

^ denotes difference from MD-1.

The analysis of external load in the microcycles according to playing position showed that FW covered significantly (p<0.05) more distance sprinting and performed more sprints than CB in M4 (Table 3).

Table 3

External load in microcycles according to playing position.

		TD (m)	RD (m·min-1)	HID (m)	HID (m·min-1)	SPD (m)	SPD (m·min-1)	SPD (n°)	Maximal Velocity (km·h-1)	ACC (m·min-1)	DCC (m·min-1)	PL (AU·min-1)
M1	CB	22524±4696	62.9±8.4	385.7±325.7	4.6±3.5	254.0±221.0	2.8±1.9	16.0±14.5	22.7±1.4	38.6±1.5	38.6±1.1	0.7±0.1
	FB	22496±8047	65.7±4.1	508.5±365.2	6.2±4.3	465.8±67.0	5.2±0.4	21.0±18.4	24.2±0.7	37.0±0.2	37.8±0.8	0.8±0.1
	CM	23555±4695	68.0±6.0	471.9±421.0	5.7±4.7	198.5±117.1	2.2±1.0	11.7±6.1	22.4±1.0	36.2±2.0	36.3±1.3	0.9±0.2
	FW	19112±2306	70.2±9.7	618.7±388.8	7.5±5.4	420.9±183.1	4.7±1.8	26.0±9.7	24.1±1.6	36.2±2.0	36.1±1.2	0.9±0.1
M2	CB	24108±5980	64.0±12.1	408.3±243.9	4.7±2.6	379.8±87.8	4.2±17	22.0±8.0	24.4±1.5	36.5±3.7	35.0±2.9	0.7±0.1
	FB	23725±8414	65.4±2.0	521.8±295.9	5.8±2.7	504.0±351.9	5.6±3.1	24.5±20.5	25.8±0.2	35.9±1.2	35.4±0.8	0.7±0.1
	CM	22510±6778	73.3±7.8	526.5±328.7	6.1±3.7	336.1±115.4	3.7±2.3	17.6±5.5	24.5±0.8	34.9±2.6	35.5±1.8	0.9±0.2
	FW	28250±3456	77.0±5.8	720.9±405.8	8.3±4.5	772.0±330.5	8.6±4.2	33.2±26.0	25.2±1.0	35.7±0.9	33.4±3.1	0.9±0.2
M3	CB	21847±5530	66.3±7.9	474.5±379.9	5.2±4.1	272.6±96.7	3.0±1.0	15.3±4.7	25.5±3.4	36.8±0.6	37.7±1.3	0.7±0.0
	FB	19499±1001	64.4±2.0	489.1±430.7	5.5±4.7	348.0±33.5	3.0±0.6	18.5±2.1	23.2±0.5	36.5±1.3	36.9±2.1	0.8±0.0
	CM	23137±5252	66.6±3.8	499.6±376.2	5.8±4.2	281.1±111.5	3.1±0.9	12.3±7.2	22.6±0.6	36.9±1.5	36.7±1.3	0.9±0.1
	FW	22414±4774	69.2±13.9	532.9±303.4	6.3±3.8	400.5±153.8	4.4±1.6	21.7±3.6	25.0±2.0	35.7±2.4	36.3±1.3	0.9±0.2
M4	CB	22491±7605	60.9±3.8	273.5±217.3	3.3±2.3	165.7±117.2*	1.8±0.9*	8.6±5.5*	23.7±1.3	37.4±1.2	37.2±0.8	0.7±0.1
	FB	23146±4389	60.8±0.1	495.6±395.4	5.6±4.3	583.2±234.7	6.6±2.7	27.0±11.3	24.7±0.5	36.9±0.95	36.5±0.1	0.8±0.1
	CM	2423±4555	67.0±3.6	451.0±434.7	5.2±4.8	380.3±155.0	4.2±1.2	17.7±7.0	23.3±0.9	35.3±1.15	35.2±1.3	0.9±0.1
	FW	26143±5027	66.8±6.7	530.1±438.1	6.2±4.9	624.0±140.5	6.9±1.1	29.25±9.7	24.2±0.7	35.2±1.6	34.7±1.6	0.9±0.1

Data are presented according to microcycle and positions: M1 = microcycle 1; M2 = microcycle 2; M3 = microcycle 3; M4 = microcycle 4; TD = total distance; CB = Central defender; FB = fullback; CM = central midfielder; FW = forwards; RD = relative distance; HID = High intensity distance; SPD = sprint; ACC = accelerations; DCC = decelerations; PL = player Load.

*Denote differences from FW.

Table 4 presents the training load in training sessions and match days according to playing position. FWs performed significantly more sprints (in number and meters; p < 0.05) than CMs and CBs in MD-2 and MD, and covered significantly more sprint distance (meters; p < 0.05) than CBs in MD-2. Comparing the external training load versus MD, FBs, CMs, and FWs in MD-3 exceeded 50% of match play values in sprint distance (Fig 1). In addition, FWs and FBs in MD-3 reached match maximal velocity. Significantly higher peak velocity (p < 0.05) was obtained in MD-3 compared to MD-1 for FBs, CMs, and FWs.

Table 4

Mean external training load variables according to days to match and playing position.

	Position	TD (m)	RD (m·min-1)	HID (m)	HID (m·min-1)	SPD (m)	SPD (m·min-1)	SPD (n°)	Maximal velocity (km·h-1)	ACC (m·min-1)	DCC (m·min-1)	PL (AU·min-1)
MD-4	CB	4729 ± 454	55.4 ± 5.3	226.3±72.4*	2.6±0.8*	40.2 ± 19.1	0.4 ± 0.2	1.8 ± 0.7	23.2 ± 1.5	39.3 ± 0.1	39.3 ± 0.1	0.68 ± 0.1
	FB	4748 ± 509	54.9 ± 5.8	239.1±111.9	2.8±1.3	69.2 ± 14.3	0.8 ± 0.2	3.4 ± 0.9	24.3 ± 0.7	38.8 ± 0.1	38.8 ± 0.1	0.71 ± 0.1
	CM	4984 ± 318	58 ± 3.7	262.5±117.7*	3.0±1.3*	48.3 ±16.6	0.5 ± 0.2	2.1 ± 0.7	23.3 ± 0.5	37.2 ± 1.6	37.2 ± 1.6	0.74 ± 0.1
	FW	4768 ± 862	59.7 ± 5.1	387.5±168.6	4.5±1.9	61.1 ± 33.1	0.7 ± 0.3	3.3 ± 1.5	23.9 ± 1.7	37.7 ± 1.8	37.7 ± 1.8	0.86 ± 0.1
MD-3	CB	5691 ± 921	68.6 ± 9.5	491.4±170.2*	5.9±2.0*	91.4 ± 81.5	1.0 ± 0.7	5.2 ± 5.2	24.1 ± 1.9	37.2 ± 1.5	36.3 ± 2.2	0.72 ± 0.1
	FB	6241 ± 24	75 ± 3.1	719.7±234.6	8.9±3.0	216.6 ± 74.7	2.4 ± 1.0	8.9 ± 0.8	26.1 ± 1.3	34.3 ± 0.3	34.3 ± 0.4	0.83 ± 0.1
	CM	6492 ± 969	79.8 ± 9.8	696.1±284.8	8.6±3.3	114.3 ± 54.1	1.3 ± 0.6	5.5 ± 1.8	24.2 ± 1.1	34.8 ± 3.2	34.3 ± 2.8	0.92 ± 0.2
	FW	6172 ± 545	76.4 ± 4.7	820.2±328.3	10.2±3.4	194.8 ± 66.7	2.2 ± 0.9	9.9 ± 3.4	25.6 ± 1.3	35.4 ± 1.5	34.9 ± 1.7	0.95 ± 0.2
MD-2	CB	4908 ± 653	55.1 ± 7.1	389.9±359.8	4.3±3.9	40.6 ± 6.4	0.5 ±0.1	2.1 ± 0.7*	24.5 ± 3.7	39.2 ± 1.9	39.2 ± 1.9	0.54 ± 0.1
	FB	4671 ± 113	51.7 ± 1.2	475.5±110.0	5.3±0.8	67.2 ± 5.3	0.7 ± 0.1	4.6 ± 0.9	24.3 ± 0.0	39.7 ± 0.5	39.7 ± 0.4	0.65 ± 0.0
	CM	4880 ± 334	55.7 ± 2.1	377.9±132.4	4.3±1.5	37.9 ± 29.8*	0.4 ± 0.4 *	2.4 ± 1.4*	23.1 ± 0.9	38.9 ± 1.4	38.9 ± 1.4	0.68 ± 0.1
	FW	4753 ± 312	54 ± 2.3	492.4±145.9	5.6±1.8	89.7 ± 36.2	1.0 ±0.5	5.7 ± 2.1	24.5 ± 0.9	38.9 ± 1.6	38.6 ± 1.7	0.73 ± 0.1
MD-1	CB	3933 ± 231	54.4 ± 2.9	150.0±143.2	2.2±2.4	17.6 ± 7.1	0.2 ± 0.3	1.5 ± 0.7	22.3 ± 0.3	37.9 ± 0.4	37.9 ± 0.4	0.71 ± 0.1
	FB	3978 ± 364	52.8 ± 2.7	227.9±173.1	2.9±1.9	27.1 ± 15.5	0.3 ± 0 .2	1.8 ± 0.8	22.1 ± 0.6	37.7 ± 0.3	37.7 ± 0.3	0.69 ± 0.0
	CM	4181 ± 461	57.8 ± 5.9	221.4±206.3	3.1±3.2	16.7 ± 12.7	0.2 ± 0.2	1.2 ± 0.9	21.4 ± 0.8	36.4 ± 1.9	36.8 ± 1.9	0.77 ± 0.1
	FW	4113 ± 675	55.2 ± 4.3	254.9±225.2	3.3±3.2	36.7 ± 25.7	0.4 ± 0.3	2.6 ± 1.8	21.9 ± 1.7	36.1 ± 1.6	36.1 ± 1.6	0.76 ± 0.1
MD	CB	8025 ± 1241	87.7 ± 11	717.5±231.4*†‡	7.5±2.3*†‡	168.8 ± 78.4	1.9 ± 0.7	10.3 ± 5.2*	25.8 ± 2.0	33.3 ± 2.2	33.2 ± 2.2	1.06 ± 0.1†
	FB	9198 ± 675	91.2 ± 0.5	1178.4±139.1	12.3±1.7	272.9 ± 34.3	3.0 ± 0.5	15.2 ± 1.2	26.1 ± 1.0	31.7 ± 1.1	31.7 ± 1.2	1.16 ± 0.1
	CM	9895 ± 527	102.5 ± 3.8	1303.7±284.7	13.8±3.2	206.9 ± 28.6	2.3 ± 0.4	10.8 ± 0.9*	24.6 ± 0.9	30.9 ± 1.0	30.9 ± 1.0	1.41± 0.2
	FW	9597 ± 1121	97.4 ± 8.9	1205.4±215.9	11.9±3.7	282.4 ± 78.5	3.1 ± 1.0	17.5 ± 1.6	25.7 ± 1.1	31.6 ± 1.4	31.6 ± 1.4	1.27 ± 0.1

Data are presented according to days to match and positions. CB = Central defender; FB = fullback; CM = central midfielder; FW = forwards. TD = total distance; HID = high intensity distance; SPD = sprint; ACC = accelerations; DCC = decelerations; PL = player Load.

* denote differences from FW

† denote differences from CM

‡ denote differences from FB.

Fig 1

Sprint distance and maximal velocity for professional players relative to match play in training sessions.

* = denote differences from MD- 1. CB = central defender; FB = fullbacks; CM = central midfielder; FW = forwards.

Discussion

The aim of this study was to analyze the inter- and intra-differences in external load across microcycles and compare the external load among playing positions and microcycles and between training sessions and match days in female professional soccer players. The novel findings revealed a similar inter-microcycle external training load. In addition, according to playing position, FWs covered significantly (p < 0.05) more sprint distance and performed a greater number of sprints than CBs in M4. Intra-microcycle analysis showed significant (p < 0.05) differences in external load between training sessions, with central sessions of the microcycle demonstrating the highest external load, thus confirming our hypothesis. In addition, during training sessions in MD-3, only FWs and FBs reached maximal velocity comparable to peak match velocity. Our results may aid researchers to understand periodization models and taper strategies, through demonstrating limited training-load-relevant variations across microcycles and that differences between positions only exist in the sprint distance and numbers of sprints.

Quantifying training and match load could facilitate the establishment of specific demand profiles in female soccer players in order to periodize the training sessions as well as the recovery strategies in this specific population. As such, the current study revealed no general inter-microcycle differences in external training loads across the mesocycle, since only M3 and M2 showed a significantly (p<0.05) lower SPD covered in comparison to M4 and M1 (~3.5 m·min-1 vs ~5 m·min-1). Similarly, the study performed by Owen et al. [22] reported no significant differences in external load across microcycles in male professional soccer players. These findings suggest that external load remains constant in female professional soccer players, in order to maintain their physical capacities to accommodate match demands during the competitive season and reduce injury risk [26]. To prevent injuries, fitness and conditioning staff can manage some external load to determine the correct load for future training sessions while helping to mitigate injuries due to overuse during a long competitive season [26,27].

Another major finding of this study was that external training loads were significantly greatest in the MD-3 sessions compared with the rest of the training sessions, whereas all training sessions showed significantly less external load than observed on match day according to previous studies [28]. The central sessions of the microcycle (i.e., MD-3) produced the greatest loads in terms of RD, ACC, HID, and SPD, which is supported by the types of training tasks included in those sessions in which the main objective, from a conditional perspective, is the overstimulation of strength and endurance capacities [17]. The TD and HID variables also differed in training sessions (4883 vs. 5437 m and 350 vs. 1027 m, respectively) from those reported for elite [16] and collegiate (TD = 2950 m) female soccer players [29]. This is probably because of variations in the competitive standards of the players [20], the training methodologies used [15], and the different high-intensity distance definition (16.0 vs 12.1 km·h-1), which may have overestimated the training load because professional female players reach peak velocity > 24 km·h-1 [30]. In addition, significant differences for TD, SPD, ACC, DCC, and PL were observed between MD-1 and the rest of the training sessions, confirming our hypothesis concerning the use of the tapering strategy within the microcycle and the existence of intra-microcycle differences.

Managing training loads may be facilitated if they are expressed as a percentage of official match-related loads, since this makes interpreting, communicating, and deciding the training prescription easier [31]. According to previous studies [15,28], our results showed that average team sprint distances in training sessions are lower compared to match days (23.5%, 64.4%, 24.7%, and 10.4% in MD-4, MD-3, MD-2, and MD-1, respectively). Therefore, matches constitute the main load of a training microcycle in female professional soccer players. In contrast to our results, Martín García et al. [15] showed that the highest sprint and peak velocities are reached in the MD-4 training session. These differences could be due to the number of training sessions that composed the microcycle (five vs. four). In all sessions, except MD-1, players reached velocities near the maximum velocity expressed in a match, but only FBs and FWs reached match velocity in MD-3. The exposure to HID in training sessions has been proposed as an injury-prevention strategy [32-34], so it is important for staff members to ensure that they design tasks to reach this intensity. On MD and MD-2, FWs showed many more sprints and longer sprint distances than CMs and CDs, because players in this position are expected to run into open space and break into the box to create goal-scoring opportunities, so it is necessary for them to make maximal sprint efforts [35].

In line with previous research [15,36], the SPD variable demonstrated the most variability in training sessions (107.1%, 31.5%, 28.8%, and 89.8% on MD-4, MD-3, MD-2, and MD-1, respectively), and on MD all variables showed lower variability (5.5%, 30.8%, and 6.5% for RD, HID, and SPD, respectively). These results could be explained by a combination of the inherent unpredictable nature of game-based training and the strategies coaches use to vary the stimulus for players to create training adaptations [15]. However, because the analysis of the variability in external load reported relevant values, the results should be interpreted with caution. In our study, the MD-4 and MD-1 training sessions presented the greatest variability (47.6% and 90.4% for HID and 107.1% and 89.8% for SPD), and MD had the least variability (30.8% and 6.5% for HID and SPD, respectively). Previous studies have reported greater variability (>80%) in HID and SPD values in the microcycle structure [15], or in training tasks (60–140%) [37] when compared to competitive matches (20–30%) [38,39]. Castillo et al., [17] obtained high between-session CVs (range = 10–100%) for distance covered at different intensities and short-term high-intensity actions across acquisition sessions in a Spanish professional team, with similar CV values (115%) obtained in English Premier League soccer players for high-intensity running during the in-season competitive phase [40]. Likewise, our results showed greater CV values for RD (7.1%), HID (38.2%), and SPD (107.1%), which coincides with previous literature [15,41]. This could be explained by contextual factors such as training task characteristics, physical fitness level, outcome, level of opposition, competitive level, and/or tactical requirements [14,17], which can influence the players’ external loads.

Despite only significant differences between microcycles in SPRD (m·min-1) (M1 and M2 lower than M4) and HID (M3 lower than M2), M2 shows a ~ 30% greater than M3 and M4 and a ~ 28% and ~ 30% greater than M3 and M1 in HID and SPRD respectively. Previous studies have shown differences in microcycle load according to the time of the season [42] or the training objective [22]. A comprehensive analysis focused on playing positions could provide useful information for coaches to individualize the distribution of external training loads. During M4, FWs performed significantly more sprints (29.25±9.7 vs. 8.6±5.5, ~ 67%) and sprinted longer distances (624.0±140.5 vs. 165.7±117.2 m, ~75%) than CBs. This may be because the type of tasks implemented that week may have caused greater physical demands from FWs. In this sense, our results showed that FWs and FBs performed significantly more sprints than CDs and CMs on MD and MD-2 and FWs sprinted significantly longer distances than CMs on MD-2 without differences in the rest of the external load. These results are in line with those reported by Mohr et al. [9], who showed that during MD the attackers sprinted a greater distance (0.52±0.03 km vs. 0.33±0.05 km) but covered a similar (~10.2 km) total distance to defenders. The results further concur with previous findings whereby FWs covered the greatest distance at high intensity (consisting of HID and sprinting) [25]. However, other studies did not show differences between playing positions in TD and sprint distance [43]. Olivera et al. [28] These differences may be due to the different speed thresholds, as Vescovi and Favero [25] considered sprint distance covered to be at >20.0 km·h-1 and Datson et al. [43] considered distance covered to be at >25.0 km·h-1. Therefore, to provide references to make comparisons between studies, a methodological standardization of velocity thresholds is necessary to quantify external loads in female soccer players.

This study is not exempt from limitations, the main one being that all of the female players belonged to the same team, so external training load cannot be generalized to all clubs. In addition, the small sample size for each position and the playing formation this team used prevent generalizing to other female soccer players. A strength/speed session can cause increases in accelerations, but also decelerations and alter the load of the session. Therefore, quantifying these changes to make them uniform among players may be necessary. As the same external load can originate a different internal response, future studies that analyze these aspects together (internal and external load) may be of interest to understand the dose-response during the training process. However, the main strength of this study is the analysis of the inter- and intra-microcycle external loads across four consecutive weeks, reporting relevant data for coaches.

Quantifying external loads across training and matches could help coaches understand the dose-response across microcycles and, consequently, enhance the training periodization in female soccer. Because MD is the most demanding session of the week, adequate strategies for recovery in subsequent sessions are necessary in order for players to face the next game under optimal conditions. Likewise, considering the aforementioned differences found related to playing positions, special attention is required to periodize better training processes to allow players to prepare for match demands and reduce the risk of injury. In this sense, implementing soccer-specific speed drills is necessary for each playing position to increase external training load and prevent injuries.

Conclusion

In summary, this study demonstrated that external load is similar for female professional soccer players during the inter-microcycle; however, the intra-microcycle revealed higher external loads in MD-3 in comparison to the rest of the training sessions. Likewise, MD was the most demanding session across the microcycle. In addition, considering the playing positions of female players, FWs sprinted greater distances and performed a greater number of sprints than CBs in M4. Finally, differences were found in maximal velocity reached by FWs and FBs in comparison to CBs and CMs during the MD-2 training session and MD and between FWs and CMs in sprint distance during the MD-2 training session.

(XLSX)

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20 Oct 2021

19 Nov 2021

Response to Reviewers

Response to reviewer 1:

First of all, we would like to express our gratitude to Reviewer 1 for the time in reviewing our paper and for providing us comments/suggestions helpful to improve this paper quality. We are very proud of your comments. We think that your observations have improved the manuscript. We have answered point-to-point in yellow in this document and in the new version of the manuscript.

Reviewer #1: Abstract

Ok

Introduction

Line 44: Include what is sprint speed

Response: Dear reviewer, we have included values of sprint speed.

At a general level, a more exhaustive review of the importance of load control in football and its relationship with different performance parameters would be interesting.

Response: Dear reviewer, we have modified the introduction section including a more exhaustive review of the importance of load control. You can see in introduction section“ Inappropriately training loads can cause overuse injuries [18] and increased injury risk is associated with spikes in workload (i.e., overloading) and low chronic workloads (i.e., underloading) [19]. Given that quantification of the workload has become an essential aspect in soccer performance [11].”

[11] Malone J, di Michele R, Morgans R, et al. Seasonal training-load quantification in elite English Premier League soccer players. International Journal of Sports Physiology and Performance 2015; 10: 489–497.

[18] Drew MK, Finch CF. The Relationship Between Training Load and Injury, Illness and Soreness: A Systematic and Literature Review. Sports medicine (Auckland, NZ) 2016; 46: 861–883.

[19] Hulin BT, Gabbett TJ, Lawson DW, et al. The acute: Chronic workload ratio predicts injury: High chronic workload may decrease injury risk in elite rugby league players. British Journal of Sports Medicine 2016; 50: 231–236.

Material and Methods

The previous acute / chronic burden accumulated before the study period was taken into account.

Response: Dear reviewer, we have considered previous workload. In this sense the previous microcycle to the experimental design was a recovery microcycle and all the following microcycles were performance typology in season (after preseason finished). See the next response.

If competitive microcycle 1 is taken, the preseason phase previously existed. Did the players start with a similar load or was it different from the start?

Response: Thanks for your appreciation. We include in methods section an explication about your concern: “Microcycle 1 was performed in the middle of the first part of the season, 4-weeks after the end of the pre-season with a similar workload in all players”

The level of the rivals, were they similar, higher or lower than the level of the team studied?

Response: Dear reviewer, we know the importance of the team level as a contextual factor in the match demands. It is difficult to predict the level of an opponentin early phases of the season, but in this case the four microcycles were placed against opponents with similar level according to their final classification during the previous season.

What order was the session in? In the Strength, Endurance, Speed sessions, what kind of general work was done?

Response: In Procedures section, we agree more exhaustive explanation: “The usual distribution of the microcycle was as follows: MD-4: recovery session and general resistance; MD-3: resistance and endurance session (i.e., plyometric drills, strength stations and game simulation); MD-2: speed and tactical approximation (i.e., sprint running and large small sided games); and MD-1: activation session (reaction speed and small sided games), targeting the three main physical capacities and similar to that shown by previous studies with male soccer players (Buchheit et al., 2018; Castillo et al., 2019). In MD-3 tactical drills (i.e., medium and large small games with tactical constrains) was performed bay female soccer players”.

Buchheit, M., Lacome, M., Cholley, Y., & Simpson, B. M. (2018). Neuromuscular responses to conditioned soccer sessions assessed via GPS-Embedded accelerometers: Insights into tactical periodization. International Journal of Sports Physiology and Performance, 13(5), 577–583. https://doi.org/10.1123/ijspp.2017-0045

Castillo, D., Raya-González, J., Weston, M., & Yanci, J. (2019). Distribution of External Load During Acquisition Training Sessions and Match Play of a Professional Soccer Team. Journal of Strength and Conditioning Research. https://doi.org/10.1519/jsc.0000000000003363

What kind of tactical tasks did they consist of? What% of time corresponds to each task in the session?

Response: We agree with the reviewer, so a better explanation of the characteristics of the sessions have been included in the procedures section: “Tactical task (i.e., conditioned games in medium and large spaces simulating competition situations, superiorities and inferiorities) represents 20%, 40% and 40% in MD-4, MD-3 and MD-2 respectively”

A Strength / Speed session can alter the parameters of decelerations or high intensity actions. Was it quantified in some way to make homogeneous efforts?

Response: thank you for your comment. In this sense we no quantified the decelerations or high intensity actions in aim to make homogeneous efforts. We include how possible limitation: Line 302: A strength / speed session can cause increases in accelerations, but also decelerations and alter the load of the session. Therefore, quantifying these changes to make them uniform among players may be necessary.

In games, how many minutes did the players play? Was it a homogeneous time? Were the exposure times in training sessions / matches relativized?

Response: Dear reviewer, only player who that completed at least 60 min were analyzed. We have included it on procedures section. “The external load of the microcycle was analyzed only in those players who played ≥ 60 min in MD”

What were they based on to establish 15 or 20 min of warm-up? Was there a 17-minute warm-up? Those 5 minutes of margin that was included?

Response: To determine warm up time we used usual time in female soccer players (Isla et al., 2021, Pardos et al., 2019). In addition, it is the usual time that the coach used in the warm-up routines in this team and in order not to limit him there was a margin of 5 minutes. Following references support this concern:.

Isla, E., Romero-Moraleda, B., Moya, J. M., Esparza-Ros, F., & Mallo, J. (2021). Effects of a Neuromuscular Warm-Up Program in Youth Female Soccer Players. Journal of human kinetics, 79, 29–40. https://doi.org/10.2478/hukin-2021-0080

Pardos-Mainer, E., Casajús, J. A., & Gonzalo-Skok, O. (2019). Adolescent female soccer players' soccer-specific warm-up effects on performance and inter-limb asymmetries. Biology of sport, 36(3), 199–207. https://doi.org/10.5114/biolsport.2019.85453

Statical

Ok

Results

Ok

Response: Thanks for the consideration. However, we have added one column in each table showing the absolute value of high intensity distance covered HID (m) by female soccer player, so the HID and distance to sprint (SPD) covered are shown in absolute values (m) and relative to time (m·min-1) in each table.

Discussion

Were there any injuries during the study period either in training or in the game? Was the accumulated load on the players taken into account to regulate their intervention in training sessions?

Response: Thank you for your comment. In this sense, no injuries were occurred during the analysis period (4 microcycles). Acute:Chronic load was not taken into account since the authors were not part of the team staff. Today women's soccer, despite analyzing a first division team (i.e., Primera Iberdrola League), does not have the same resources as men's soccer.

It would be interesting to talk in the discussion about the% change in load with respect to the microcycles and also observe, the% load that each training session represents with respect to the previous match. It may be a future line of research.

Response: Dear reviewer, we agree that It would be interesting to talk about the % change in load in relation to the microcycles and also to observe the % load that each training session represents with respect to the previous match. Although, it is not directly related to the objectives of our study, we include values in the discussion section. Line 291-295 Thanks for the contribution, it is an interesting future line of research.

high SPD values at -1 to be tapering phase

Response: we agree but in MD-1 CV is 89.8%, 59.1% and 88.2% to SPD in m, m·min-1 and nº respectively.

Since there are no standardized thresholds, why do the authors use <21 km? Is this speed based on men's soccer data? Has the speeds been relativized based on the individualization of each player? It may be that the players have their sprint level at 17-18-19 km and not at 21. Was it taken into account?

Dear reviewer, indeed different speed thresholds have been proposed for female soccer players, some of them related to male values or proposing some lower ones. In our case we have taken into account: Physical Analysis of the FIFA Women’s World Cup France 2019TM (https://digitalhub.fifa.com/m/4f40a98140d305e2/original/zijqly4oednqa5gffgaz-pdf.pdf)

Reviewer #2: Inter- and intra-microcycle external load analysis in female professional soccer players:

a playing position approach

First of all, the reviewer would like to thank the authors for their work and efforts in trying to improve sports science knowledge.

General comments to the authors

Overall, this is a nice study that the study could have important practical information integrated with inter-and intra-microcycle external load according to playing position in female professional soccer players. The authors are commended on their efforts thus far. The study is well designed and well-written, with a great original article. However, I suggest only small corrections and the authors should update the recent references about inter-and intra-microcycle external load according to playing position in professional soccer players. These corrections and studies will allow improving the manuscript.

Response: First of all, we would like to express our gratitude to Reviewer 2 for the time in reviewing our paper and for providing us comments/suggestions helpful to improve this paper quality. We are very proud for your comments which help us to improve the manuscript substantially. We have answered point-to-point in highlight (yellow) in this document and in the new version of the manuscript.

Abstract

Line 28: I think that we do not need this information (i.e., Primera Iberdrola League).

Instead of this, … who played to the same team in a regional league or something like that

Response: We agree with you. Corrected: “… who belonged to the same team in first national division”

Line 29: I think that we do not need this information in abstract (WIMU PRO, RealTrack Systems, Almería, Spain)

Response: We agree. Deleted.

Line 35: Both fitness and conditioning experts ….

Response: Dear reviewer, corrected.

Introduction section

Line 47: As such, fitness and conditioning staff …

Response: Corrected.

Line 62: the authors should add this article for professional male

Clemente, F., Silva, R., Arslan, E., Aquino, R., Castillo, D., & Mendes, B. The effects of congested fixture periods on distance-based workload indices: A full-season study in professional soccer players. Biology of Sport, 37(1), 37-44.

Line 62: the authors should add this article for professional female

Strauss, A., Sparks, M., & Pienaar, C. (2019). The use of GPS analysis to quantify the internal and external match demands of semi-elite level female soccer players during a tournament. Journal of sports science & medicine, 18(1), 73.

Response: Dear reviewer, thanks for the specific reference proposed: Include

Materials and Methods section

This section is well designed and well-written.

Participants

Line 105: As the same as in abstract

Response: corrected.

Results section

This section is well designed and well-written.

Response: Thanks for the consideration. However, we have added one column in each table, showing the absolute value of high intensity distance covered HID (m) by female soccer player, so the HID and distance to sprint (SPD) covered are shown in absolute values (m) and relative to time (m·min-1) in each table.

Discussion section

Overall the discussion is well-written and incorporates relevant literature. However, the authors could use these recent articles in discussion, if you want

Oliveira, R., Martins, A., Nobari, H., Nalha, M., Mendes, B., Clemente, F. M., & Brito, J. P. (2021). In-season monotony, strain and acute/chronic workload of perceived exertion, global positioning system running based variables between player positions of a top elite soccer team. BMC Sports Science, Medicine and Rehabilitation, 13(1), 1-10.

Oliveira, R., Brito, J. P., Martins, A., Mendes, B., Marinho, D. A., Ferraz, R., & Marques, M. C. (2019). In-season internal and external training load quantification of an elite European soccer team. PloS one, 14(4), e0209393.

Clemente, F. M., Silva, R., Ramirez-Campillo, R., Afonso, J., Mendes, B., & Chen, Y. S. (2020). Accelerometry-based variables in professional soccer players: comparisons between periods of the season and playing positions. Biology of Sport, 37(4), 389.

Hasan, U. C., Silva, R., & Clemente, F. (2021). Weekly variations of biomechanical load variables in professional soccer players: Comparisons between playing positions. Human Movement, 22(1), 19-34.

Silva, R., Ceylan, H. I., Badicu, G., Nobari, H., Carvalho, S. A., Sant’Ana, T., ... & Clemente, F. M. (2021). Match-to-match variations in external load measures during congested weeks in professional male soccer players. J. Men’s Health, 1-11.

Stevens, T. G., de Ruiter, C. J., Twisk, J. W., Savelsbergh, G. J., & Beek, P. J. (2017). Quantification of in-season training load relative to match load in professional Dutch Eredivisie football players. Science and Medicine in Football, 1(2), 117-125.

Response: Dear reviewer, thanks for the specific and actual reference suggestion. We have included those related to the sections discussed in the discussion section.

Figure and Tables

This section is well designed and well-written.

Response: Thanks for the consideration.

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Inter- and intra-microcycle external load analysis in female professional soccer players: a playing position approach.

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Inter- and intra-microcycle external load analysis in female professional soccer players: a playing position approach.

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