Sage Journals: Discover world-class research

Abstract

The objective of this study was to describe and compare the running demands and performances in women's elite football in different types of training sessions and matches, considering two professional categories (First Division and Second Division) during two consecutive seasons. A total of 32 players were analyzed in the Spanish Women's First Division (C1) and Second Division (C2). In addition to the match-day (MD), four types of training sessions were analyzed: four, three and one days before the MD, MD-4, MD-3 and MD-1 respectively, and one day after, MD + 1. The recorded variables, were: effective minutes (EM), total distance (TD), high-speed running (HSR), sprint (SPR) and distance covered per minute (TDmin). The results were: 1) for both categories: no training session replicated the demands of competition, except for MD + 1 in C2 which accumulated higher values in two variables (HSR and SPR). MD-1 was the session with the lowest load and intensity; 2) C1 only presented higher demands than C2 in two (TD, 9533 m vs 9255 m and TDmin, 98,8 m/min vs 96 m/min) of the four variables in the MD. We can conclude that there was an inverted U-shaped distribution in running performance within the competition microcycle in both categories, despite that most of the training sessions were not more demanding than the competition, and that there were only differences between categories in competition running performance. The practical applications of this study could improve intervention strategies in both the training process and competition.

Keywords

Competition microcycle high-speed running soccer time-motion training

Introduction

Throughout history, women's football has experienced exponential growth, however it was not until the late in the twentieth century that significant interest in studies on women's football aroused,^1–4 as a result of the social impact generated by the final of the FIFA Women's World Cup ‘99.^5,6 To establish reference values for competition, the researchers aimed to determine whether different competition levels are associated with particular demands in competition.⁷ One of the most current studies concludes that, for example, the values of total distance covered by the players in a competition match were lower in national competitions compared to international ones, 8700 vs 9400 m. Moreover, in accumulated distance at high intensity and sprint, international matches compared to national ones were more demanding according to Griffin et al.⁸ with 766 vs 608 m values at high intensity, and 363 vs 306 m at sprint.

It also seems that competition itself appears to be the most demanding stimulus of competition microcycle¹ therefore, training sessions are planned according to competition. Using the match as a reference point, a weekly distribution of training plans are usually proposed considering the availability of days between two consecutive matches.^1,4,9 This approach aims to maintain a balance between load (or stimulus) and recovery (or rest), to optimize performance in competition and reduce the chances of overloading players or suffering injury.^10–12 Thus, in order to achieve effective periodization, elite football teams have adopted different planning strategies, with tactical periodization and structured microcycle currently being the most widespread.¹⁰ In the microcycles of a single competition, both strategies align by scheduling the acquisition sessions in the central days of the microcycle, and conditionally less demanding sessions in the final part of the microcycle, focusing on the objective of tuning or tapering.^13,14 Both types of sessions, those with higher and lower conditional demand, give rise to an inverted U-shaped in the distribution of conditional demands during the microcycle.^11,15–17

Comparisons between competition levels in women's football are challenging to develop due to two main factors, on the one hand, the volume of matches analysed by companies and/or leagues is still not widespread enough, and on the other, the local and competition context (e.g., competition format) are particular as recently Harkness-Armstrong et al.¹⁸ described it in the English regional teams. Consequently, it appears that physical performance will most likely be greater in volume and intensity in relation to the competition level, as is proposed in men's football, both in training process and in competition. In this sense, even though some authors in the state of the art have described the conditional demand in training and competition in a single team and category,^1,4 no references have been found in women's football that simultaneously include the conditional demand of training process and competition, in the two highest elite categories of Spanish women's football.

Based on the reasons outlined above, this study aims to innovatively describe and compare running demands and performances in training sessions and competition matches of the same team participating in two consecutive seasons in the two top tiers in the Spanish Womeńs football (Spanish Women's First and Second Divisions). As a basis, three hypotheses are proposed: 1) running demands follow an inverted U-shaped distribution within the competition microcycle sessions¹⁰; 2) no training session fully replicates the running demands of competition¹; and 3) both training sessions and competition exhibit higher running performance demands in the top-tier category.⁸ This work, in addition to describing the reference values of running performances at two competition levels, will provide insights into the type of weekly planning of running demands that is proposed in Spanish women's elite football.

Methods

Sample

A total of 32 women football players took part in the study for two consecutive seasons. In the first season the players played in Reto Iberdrola (C2), considering semi-professional players (n = 20; age: 24.6 ± 4.0 years; height: 163.9 ± 5.0 cm; weight: 58.5 ± 4.2 kg). In the second season they played in the Liga Iberdrola (C1), considering them professionals (n = 22; age: 24.3 ± 7.1 years; height: 165.2 ± 6.2 cm; weight: 58.8 ± 5.3 kg). Ten players were the same in both seasons. A total of 46 weeks were analysed, distributed as follows: 17 weeks in C2, during the 2020–21 season, and 29 weeks in C1, during the 2021–22 season. The Ethics Committee of research with humans (CEISH) of the University of the Basque Country (UPV/EHU) gave its institutional approval of the study (code M10-2019-099).

Physical variables

The duration of the session was recorded considering only the effective minutes (EM), that is, the time in which the players were doing any task. As in other studies,¹⁸ running performance involved the monitoring of the following variables: total distance covered (TD, in m), distance covered at >19 km/h or high-speed running (HSR, in m), distance covered at >23 km/h or sprint (SPR, in m) and distance covered per minute (TDmin, in m/min).

Matches

A total of 34 matches (MD) were registered, distributed in C2 (n = 12) and C1 (n = 22). For a better contextualization of results, regarding the play style of both teams, it should be noted that there were differences between both categories. When the team played in C2, it was a dominant team throughout the season, characterized by a possession play style (higher % possession than its opponents). This team was the champion of the league and promoted to C1. On the other hand, when the team played in the C1, it played a game that was not very dominating, based fundamentally on fast transitions. The team was classified in eleventh place, which allowed it to maintain the category.

Type of training sessions

A total of 1542 records were included in the study divided between the C2 (n = 516) and the C1 (n = 1026). The distribution of the sessions throughout the microcycle was based on the previous days (4, 3 and 1 days prior to MD; MD-4, MD-3 and MD-1 respectively) and one after (one day after the match, MD + 1) the MD, following the proposal of previous studies.^10,11 Session MD-4 was the session four days before the MD and was oriented towards strength work. The MD-3 session was held three days before the MD and was focused on endurance work and slight velocity stimuli. The MD-1 session was held the day before the MD, and it was oriented to work on activation stimuli prior to the competition. Finally, the MD + 1 session was held the day after the competition and was aimed at developing all the conditional objectives (strength, endurance and velocity), trying to replicate the running demands of players with little or no participation in competition. The characteristics of the tasks that were scheduled for each type of session are included in Table 1. The training pitch measured 103 × 65 meters and featured an artificial surface in both categories. Training sessions were consistently held in the morning, beginning at 11:30 AM. Usually, training was held on Mondays, Wednesdays, Thursdays, and Saturdays, with rest days scheduled on Tuesdays and Fridays.

Table 1.

Description of four training sessions and match day.

	Characteristics of the session
Type of session	Conditional work	Number of players per team	Relative space per player	Orientation of the field
MD + 1	Velocity	1–3	<100 m²	Oriented
	Endurance	4–6	100–250 m²
	Strength	>6	>250 m²
MD-4	Strength	1–3	<100 m²	Not oriented
MD-4	Strength	4–6	<100 m²	Oriented
MD-3	Endurance	4–6	>250 m²	Oriented
MD-3	Endurance	>6	>250 m²	Oriented
MD-1	Activation	1–3	<100 m²
		4–6	100–250 m²	Oriented
		>6	>250 m²
MD	Velocity	11:11	>250 m²	Oriented
	Endurance
	Strength

Note: MD-4, MD-3, and MD-1 sessions were pre-match-day (MD) session 4^th, 3^rd, and 1^st, respectively, and MD + 1 was post-MD session. Number of players (1–3; 4–6; > 6 per team), relative space (it is computed dividing the total space by number of field-players). Velocity is velocity work, endurance is endurance work and strength is strength work. Not oriented is when the task does not have goals; oriented is when the task has goals and goalkeepers.

Procedures

The data collection was carried out with Global Positioning System (GPS) technology as follows: 1) C2 data set, from October 2020 to March 2021 with WIMU GPS devices (Real Track Systems, Almería, Spain); 2) C1 data set, from October 2021 to May 2022 with S5 GPS devices (Catapult Sports, Melbourne, Australia).

Reliability and validity of WIMU devices, whose sampling frequency is 10 Hz, have been described in a previous study.¹⁹ S5 GPS device also has a sampling frequency of 10 Hz, and its reliability and validity are optimal.²⁰ The players were familiar with the devices. In both seasons, each device was placed on the surface between the scapulae, in a pocket that carried the adjustable harness. The devices were activated 10–15 min before the start of warming up. Only records from participants completing either or both parts were included in the analysis. To avoid possible differences between devices, during the entire registration period each player used the same device.^21,22

The download of the records obtained with the WIMU devices was carried out with the software sPRO v.973 (RealTrack Systems, Murcia, Spain), while for the S5 the Openfield software was used^TM v.3.7.3 (Catapult Sports, Melbourne, Australia). Once the data was filtered through the software, it was imported into a Microsoft Excel spreadsheet (Microsoft Corporation, Washington, USA) in order to configure a matrix that would later be used to carry out the analyses.

Statistical analysis

Descriptive statistics data from variables were presented using mean and standard deviation with 95% confidence intervals. Differences between categories in the different training sessions and match day were determined using a T-test for independent samples. Differences between sessions and matches for each category were analyzed across multiple groups using the Welch ANOVA test, considering sample size, non-normality and heteroscedasticity in certain variables. Significant results were then analysed using post hoc Bonferronís test. The effect size was calculated using Cohen's d (d). A Cohen's d effect size of d = 0.2 was considered a small effect size; an effect size of d = 0.5 was considered a medium effect size; and, an effect size of d = 0.8 was considered a large effect size.²³ The level of significance was set at p < 0.05. The statistical analysis was conducted using the software JASP 0.14.1 (University of Amsterdam, Amsterdam, Kingdom of the Netherlands) and a customized Microsoft Excel spreadsheet (Microsoft Corporation, Washington, USA) for Windows.

Results

The values of the variables EM, TD, HSR, SPR and TDmin are represented in Figure 1 considering the different training sessions and matches in both leagues.

Figure 1.

Mean and standard deviation of the effective minutes and running performances in different training and competition sessions in Reto Iberdrola (C2) and Liga Iberdrola (C1). Note: MD-4, MD-3, and MD-1 sessions were pre-match-day (MD) session 4th, 3rd, and 1st, respectively, and MD + 1 was post-MD session. EM is the effective minutes of the session (in min), TD is the total distance (in m), HSR is the high intensity running distance (in m), SPR is the sprint running distance (in m), and TDmin is the distance per min (in m/min⁻¹). C1 is Liga Iberdrola and C2 is Reto Iberdrola. Significant differences (p < 0.05) are represented: 1 >MD-1, 2 >MD-4, 3 >MD-3, 4 >MD + 1, 5 >MD, a > C2 and b > C1.

Intra-category and inter-session comparison

EM variable presented significantly higher values in MD than in the other sessions in both categories, with a large magnitude (2.0–7.0). On the contrary, MD-1 was the session with the lowest volume in EM with significant differences compared to the rest of the sessions in both categories. In both C1 and C2, the MD + 1 session was significantly longer than the rest of the training sessions. The duration of MD-4 and MD-3 sessions did not present significant differences between them in C1. However, in C2, MD-3 session was longer than MD-4 session (Table 2).

Table 2.

Intra-category/inter-session effect sizes (ES) and 95% confidence intervals (95% CI) for the variables effective minutes (EM) total distance (TD), total distance per minute (TDmin), high-speed running (HSR) and sprint (SPR).

CATEGORY	DAYS	EM			TD			TDmin			HSR			SPR
			95% CI			95% CI			95% CI			95% CI			95% CI
		ES	Lower	Upper	ES	Lower	Upper	ES	Lower	Upper	ES	Lower	Upper	ES	Lower	Upper
Liga Iberdrola	MD vs MD + 1	2.0	1.7	2.4	4.0	3.5	4.5	3.0	2.6	3.4	0.5	0.2	0.8
	MD vs MD-1	3.7	3.1	3.7	8.1	7.6	8.7	4.6	4.3	5.0	2.9	2.6	3.2	2.0	1.8	2.3
	MD vs MD-3	3.8	3.4	4.2	5.7	5.2	6.1	2.3	2.0	2.5	1.2	0.9	1.4	1.0	0.7	1.2
	MD vs MD-4	3.5	3.2	3.9	5.6	5.2	6.1	2.6	2.3	2.9	2.0	1.7	2.2	1.5	1.2	1.8
	MD + 1 vs MD-1	1.2	0.9	1.4	3.1	2.8	3.4	2.3	2.0	2.6	2.6	2.3	2.9	2.3	2.0	2.6
	MD + 1 vs MD-3	1.0	0.7	1.2	0.7	0.5	1.0	−0.3	−0.6	−0.1	0.7	0.5	1.0	1.1	0.9	1.4
	MD + 1 vs MD-4	1.0	0.8	1.3	1.2	1.0	1.5	0.4	0.1	0.6	1.6	1.3	1.9	1.7	1.4	2.0
	MD-1 vs MD-3	−0.3	−0.4	−0.1	−2.6	−2.8	−2.4	−2.5	−2.7	−2.3	−1.1	−1.2	−0.9	−0.9	−1.1	−0.7
	MD-1 vs MD-4	−0.2	−0.3	0.0	−1.7	−1.9	−1.5	−1.7	−1.9	−1.5
	MD-3 vs MD-4				0.7	0.5	0.9	0.6	0.4	0.8	0.7	0.5	0.9	0.6	0.4	0.8
Reto Iberdrola	MD vs MD + 1	5.0	4.1	5.9	5.3	4.3	6.2	2.6	2.0	3.2	−0.5	−0.9	0.0	−1.5	−2.0	−1.0
	MD vs MD-1	3.4	3.0	3.9	6.0	5.5	6.6	2.6	2.3	3.0	2.1	1.8	2.5	3.0	2.6	3.3
	MD vs MD-3	7.0	6.1	7.8	5.1	4.4	5.7	2.0	1.6	2.4	1.0	0.6	1.3	1.0	0.6	1.3
	MD vs MD-4	3.8	3.3	4.3	4.5	4.0	5.1	1.3	1.0	1.6	1.6	1.2	1.9	2.5	2.1	2.9
	MD + 1 vs MD-1	1.1	0.7	1.5	2.2	1.7	2.6	1.4	0.9	1.8	3.5	3.0	4.1	3.7	3.2	4.3
	MD + 1 vs MD-3	0.4	0.0	0.9							1.5	1.0	2.0	1.6	1.1	2.1
	MD + 1 vs MD-4	0.5	0.1	1.0	0.6	0.1	1.0				2.4	1.9	2.9	3.1	2.5	3.6
	MD-1 vs MD-3	−1.0	−1.3	−0.7	−1.8	−2.1	−1.5	−1.2	−1.5	−0.9	−0.7	−0.9	−0.4	−0.4	−0.7	−0.2
	MD-1 vs MD-4	−0.7	−1.0	−0.5	−1.5	−1.8	−1.3	−1.1	−1.4	−0.9
	MD-3 vs MD-4	0.3	0.0	0.6							0.5	0.2	0.8	0.4	0.1	0.7

Note: MD-4, MD-3, and MD-1 sessions were pre-match-day (MD) session 4^th, 3^rd, and 1^st, respectively, and MD + 1 was post-MD session. EM is the effective minutes of the session (in min), TD is the total distance (in m), HSR is the high intensity running distance (in m), SPR is the sprint running distance (in m), and TDmin is the distance per min (in m/min⁻¹). C1 is Liga Iberdrola and C2 is Reto Iberdrola. Significant differences (p < 0.05) are represented: 1 >MD-1, 2 >MD-4, 3 >MD-3, 4 >MD + 1, 5 >MD, a > C2 and b > C1.

Regarding locomotor demand, MD presented a significantly higher load (TD) and intensity (TDmin) compared to the rest of the training sessions in both categories, with a large magnitude (1.3–8.1). In C1, HSR and SPR variables were higher compared to the rest of the sessions, with the exception of SPR for MD + 1 session. Also, in C2, both the HSR and the SPR were higher than the rest of the sessions, except for the MD + 1 session, which presented higher values than MD in both variables. In addition, the size of the effect in these two variables with respect to day MD-1 was large (2.0–3.0) and regarding MD-4, also large (2.0–2.5) for both categories.

In MD + 1 session, significantly higher values were described in HSR and SPR with respect to the rest of the training sessions in both categories. Both in C1 and C2 the size of the effect with respect to MD-1 was large (2.3–2.6 in C1 and 3.5–3.7 in C2) as with MD-4 day in C2 (2.4–3.1). TD presented higher values than the days MD-4 and MD-1 in C2 and with respect to the rest of the training sessions in C1, highlighting the size of the effect with respect to the day MD-1, from d = 2.2 to d = 3.1. The TDmin was higher compared to MD-1 in C2 and, MD-4 and MD-1, in C1, with a difference ranging from d = 0.4 to d = 2.3 with respect to day MD-1. MD-3 session presented significantly higher differences in the HSR and SPR variables compared to MD-4 and MD-1 sessions in both categories. In both C2 and C1, greater TD was accumulated with respect to the MD-1 session and greater with respect to MD-4 session in C1. The TDmin average, as with TD, was higher compared to MD-1 session in both categories and higher compared to MD-4 and MD + 1 session in C1. The size of the effect in the variables of TD and TDmin with respect to day MD-1 was large in both categories. Finally, the MD-4 session presented higher values in TD and TDmin compared to MD-1 day in both categories.

Intra-session and inter-category comparison

MD presented significant differences between categories in TD and TDmin variables, being higher in C1 (Figure 1). Session MD-1 described significant differences between categories for all the variables studied. Specifically, EM and TD variables were higher in C1, while the HSR, SPR and TDmin variables were higher in C2. In MD + 1 session, significant differences were found in all the variables, except in TD. The variables of HSR, SPR and TDmin were higher in C2, on the contrary, the duration was higher in C1. The effect size of HSR variable was large. The MD-3 session, unlike the rest of the sessions, did not present significant differences between categories. Finally, the MD-4 session was longer in C1 and the TDmin presented higher values in C2 (Table 3).

Table 3.

Intra-session/inter-category effect sizes (ES) and 95% confidence intervals (95% CI) for the variables effective minutes (EM) total distance (TD), total distance per minute (TDmin), high-speed running (HSR) and sprint (SPR).

DAYS	MD-4			MD-3			MD-1			MD			MD + 1
Variables		95% CI			95% CI			95%CI			95% CI			95%CI
Variables	ES	Lower	Upper	ES	Lower	Upper	ES	Lower	Upper	ES	Lower	Upper	ES	Lower	Upper
EM	0.4	0.2	0.6				1.0	0.8	1.2				0.8	0.3	1.2
TD							0.2	0.0	0.3	0.4	0.1	0.7
TDmin	−0.6	−0.8	−0.4				−0.8	−0.9	−0.6	0.4	0.0	0.7	−0.9	−1.3	−0.4
HSR							−0.5	−0.7	−0.3				−1.6	−2.1	−1.1
SPR							−0.5	−0.6	−0.3				−0.8	−1.3	−0.4

Note: MD-4, MD-3, and MD-1 sessions were pre-match-day (MD) sessions, 4, 3, and 1, respectively, and MD + 1 was post-MD session. EM is the effective minutes of the session (in min), TD is the total distance (in m), HSR is the high intensity running distance (in m), SPR is the sprint running distance (in m), and TDmin is the distance per min (in m/min⁻¹). C1 is Liga Iberdrola and C2 is Reto Iberdrola. Significant differences (p < 0.05) are represented: 1 >MD-1, 2 >MD-4, 3 >MD-3, 4 >MD + 1, 5 >MD, a > C2 and b > C1.

Discussion

The aim of this study was to describe and compare running demands and performances in women's elite football across different training sessions and matches considering the league category. To the best of the authors’ knowledge and based on existing references, this is the first work that compares the two highest categories of professional football in the Spanish league, with the unique aspect that the same team participated in consecutive years in both the Reto Iberdrola and the Liga Iberdrola. The results confirm the first of the hypotheses, describing a distribution of running demands based on an inverted U-shaped during the competition microcycle sessions. The second of the hypotheses was confirmed in the TD and TDmin variables, since none of the training sessions replicated running performances of the matches, unlike HSR and SPR that presented higher values in MD + 1. Finally, the third of the hypotheses was also partially supported, as the training sessions in the higher category (C1) were not more demanding than those in the lower category (C2). in competition, However, in competition, C1 showed greater demands compared to C2 in two of the four variables (TD and TDmin).

Regarding the duration of the training sessions, consistent with the findings of previous studies,^1,4 no session (from 57 to 79 min) lasted longer than the matches. It seems that an unwritten rule is still being respected in which it is difficult to find any training session that lasts longer than the matches.

Regarding the conditional demand of the training sessions, the results of this study showed that MD + 1 session had the longest duration, in addition to accumulating the highest values in the distances at high intensity and sprint, even in relative values (%) compared to competition matches (HSR = 127% in C2; SPR = 111% in C1; 180% in C2), This contrasts with the findings of Romero-Moraleda et al.⁴ where MD + 1 was one of the less demanding sessions. This strategy is commonly used in the professional field with the aim of compensating those players who did not participate or played a minimal role in the previous match.²⁴ The acquisition sessions (MD-4 and MD-3) were longer and had a greater load on TD and TDmin variables compared to the pre-match session (MD-1) for both categories, with similar values in TD (MD-4, 5096 ± 790 m in C1 and 5246 ± 992 m in C2; MD-3, 5584 ± 659 m in C1 and 5456 ± 846 m in C2) to those reported by Romero-Moraleda et al.⁴ (MD-4, 4831 ± 860 m; MD-3, 4975 ± 1318 m) and Diaz-Seradilla et al.¹ (MD-4, 4817 ± 407 m; MD-3, 5952 ± 727 m). MD-3 session also presented higher values of HSR and SPR compared to the MD-1 session. These findings align with previous research, accumulating higher loads on the central days of the week.^1,4,9,15,16 However, careful consideration is needed when comparing if we intend to consider the accumulated distance in absolute terms, because the threshold for considering HSR proposed by Diaz-Seradilla et al.¹ and Romero-Moraleda et al.⁴ was 16 and 15 km/h, respectively, far from 19 km/h of the present study. Therefore, to provide references to make comparisons among these case studies, a methodological standardization of velocity thresholds is necessary to quantify external loads in women football players.

Between the two acquisition sessions, session MD-3 presented significant differences in C1 in TD and TDmin variables with respect to day MD-4, coinciding with the results obtained by Diaz-Seradilla et al.¹ and Romero-Moraleda et al.⁴ These differences between sessions could be explained by the type of tasks that are proposed in those days. There are proposals in the field of professional training to alternate the conditional objective in the sessions: strength and endurance for sessions MD-4 and MD-3, respectively.^1,4,9 This implies that in the MD-4 session the staff tries to propose tasks with a reduced number of players and dimensions of the space per player, thus increasing neuromuscular demands and reducing locomotives.²⁵

Finally, in the MD-1 session, both in C1 and C2 the lowest values were described in most of the variables, which would represent a phase of tapering in the training load in the day before the competition in order to promote recovery and therefore ensure greater freshness and readiness to compete.^1,4,9,10,16

The values of the variables TD and TDmin were higher in C1 compared to the lower category in MD. These results coincide with previous studies carried out on women's football,^8,26 where a higher competition level (international level compared to national level) also described a higher running performance. However, the HSR and SPR variables did not reflect significant differences between categories, unlike what was reported by Griffin et al.⁸ and Andersson et al.,²⁶ where the international level presented significantly higher values compared to the national level. One of the explanations that could justify these differences, as indicated by the literature, could be the playing style used by the teams in both categories: in C2, the team displayed a more dominant style, with superior ball possession, while in C1, possession was lower, resulting in higher values of TD and TDmin, as previously described.²⁷

Regarding the comparison between categories in the training sessions, MD-1 session lasted longer in C1, and accumulated higher values in TD variable. However, the intensity (TDmin) and the cumulative distances of HSR and SPR were higher in C2. These results cannot be compared with other works because they do not exist. For the present work, this could be due to the fact that when the team competed in C1, not being dominant in the matches, unlike when it competed in C2, it saw the need to give priority to a type of set piece tasks (i.e., corners, lateral fouls, frontal fouls, etc., where there is practically no movement of the players) with the aim of maximizing this type of play in competition. This implied a higher EM and TD, and, consequently, a lower intensity (TDmin) of the session. The MD + 1 session was longer in C1, while in C2 greater distances of HSR and SPR were accumulated, in addition to having a higher intensity (TDmin). This could be due to the number of players that conditioned the format of the commonly used tasks. The number of players in C2 was greater than in C1, which made it possible to perform larger tasks, increasing the interaction space per player and, consequently, the distances covered at high intensity and sprint.²⁵

This work has some limitations. Firstly, the sample size (a single team), the sample size is limited to a single team, and expanding the sample will not be possible until a company provides competition analysis on a larger scale, similar to what is proposed Mediacoach^® for the two professional men's football leagues. In addition, it would have been interesting to have differentiated player positions,⁴ in order to analyse whether there were differences between categories for the same demarcation. Thirdly, having neuromuscular variables would have allowed a better understanding of the training and competition process (e.g., accelerations and decelerations), as well as the internal response of the players (e.g., questionnaire on the response to perceived exertion (RPE), which could offer insights into other dimensions of player performance and response. Given these limitations, more case studies are required, similar to the present one, with a larger and more varied sample of teams, where a wide spectrum of particularities of the training and competition process are described. This would allow for a broader description of the particularities of the training and competition processes, leading to the collection of a wider range of planning strategies and profiles of running demand and performance in both training and competition.

The conclusions of the study could be summarized as follows: 1) an inverted U-shaped was described in the distribution of running demands in the competition microcycle; 2) the team in both categories did not reach the match values in TD and TDmin in all the training sessions, unlike the HSR and SPR that in some session (e.g., MD + 1) presented higher values; 3) in the competition matches, differences were described in TD and TDmin variables, being greater in the highest level category.

The practical applications derived from this study, which coaching staff in women's football could consider when designing their intervention strategies, are as follows: 1) Propose a distribution of running demands in horizontal alternation throughout the competition microcycle, following an inverted U-shape, with an increase in the load in the central days of the week and a reduction in the days prior to the competition, with the triple objective of optimizing fitness (maintaining a chronic load high), not compromising performance in competition (maintain a low acute load), and reducing the chances of injury (adequately manage the habit of loading and freshness of the players); 2) consider the conditional performance during the competition based on the players’ level with the aim of replicating and/or compensating (for the players with less participation in competition) the conditional demand during the training process.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Spanish government PID2023-147577NB-I00 , “Knowledge Generation Projects”, in the framework of the State Program to Promote Scientific-Technical Research and its Transfer, of the State Plan for Scientific, Technical and Innovation Research of the Ministry of Science, Innovation and Universities (MCIU), the Basque Goverment and the University of the Basque Country, IT1489-22, EUSK22/17, COLAB22/15, PES22/30, MCIU-NO23/P22, COLAB22/1).

ORCID iDs

Aratz Olaizola

Ibai Errekagorri

References

Diaz-Seradilla

Rodríguez-Fernández

Rodríguez-Marroyo

, et al. Inter- and intra-microcycle external load analysis in female professional soccer players: a playing position approach. PLoS ONE 2022; 17: e0264908.

Malina

Martinho

Valente-dos-Santos

, et al. Growth and maturity status of female soccer players: a narrative review. Int J Environ Res Public Health 2021; 18: 1448.

Okholm Kryger

Wang

Mehta

, et al. Research on women’s football: a scoping review. Sci Med Football 2022; 6: 549–558.

Romero-Moraleda

Nedergaard

Morencos

, et al. External and internal loads during the competitive season in professional female soccer players according to their playing position: differences between training and competition. Res Sports Med 2021; 29: 449–461.

Castellano

Olaizola

Guerrero

, et al. Análisis del Tiempo de Juego Efectivo y de la Posesión de Balón en el Fútbol Femenino Profesional. Cuad Psicol Deporte 2024; 24: 242–256.

Kirkendall

. Evolution of soccer as a research topic. Prog Cardiovasc Dis 2020; 63: 723–729.

Pons

Ponce-Bordón

Díaz-García

, et al. A longitudinal exploration of match running performance during a football match in the Spanish La Liga: a four-season study. Int J Environ Res Public Health 2021; 18: 1133.

Griffin

Newans

Horan

, et al. Acceleration and high-speed running profiles of women’s international and domestic football matches. Front Sports Act Living 2021; 3: 604605.

Doyle

Browne

Horan

. Quantification of internal and external training load during a training camp in senior international female footballers. Sci Med Football 2022; 6: 7–14.

10.

Guridi

Castellano

Echeazarra

. Physical demands and internal response in football sessions according to tactical periodization. Int J Sports Physiol Perform 2021; 16: 858–864.

11.

Martín-García

Gómez Díaz

Bradley

, et al. Quantification of a professional football team’s external load using a microcycle structure. J Strength Cond Res 2018; 32: 3511–3518.

12.

Weston

. Training load monitoring in elite English soccer: a comparison of practices and perceptions between coaches and practitioners. Sci Med Football 2018; 2: 216–224.

13.

Fessi

Zarrouk

Di Salvo

, et al. Effects of tapering on physical match activities in professional soccer players. J Sports Sci 2016; 34: 2189–2194.

14.

Owen

Djaoui

Newton

, et al. A contemporary multi-modal mechanical approach to training monitoring in elite professional soccer. Sci Med Football 2017; 1: 216–221.

15.

Akenhead

Harley

Tweddle

. Examining the external training load of an English premier league football team with special reference to acceleration. J Strength Cond Res 2016; 30: 2424–2432.

16.

Hannon

Coleman

Parker

LJF

, et al. Seasonal training and match load and micro-cycle periodization in male premier league academy soccer players. J Sports Sci 2021; 39: 1838–1849.

17.

Malone

Di Michele

Morgans

, et al. Seasonal training-load quantification in elite English premier league soccer players. Int J Sports Physiol Perform 2015; 10: 489–497.

18.

Harkness-Armstrong

Till

Datson

, et al. Whole and peak physical characteristics of elite youth female soccer match-play. J Sports Sci 2021; 39: 1320–1329.

19.

BastidaCastillo

Carmona

CDG

Belmonte

, et al. Validez y fiabilidad de un dispositivo inercial (WIMU PROTM) para el análisis del posicionamiento en balonmano. J Sports Sci 2018; 14: 9–16.

20.

Castellano

Blanco-Villaseñor

Álvarez

. Contextual variables and time-motion analysis in soccer. Int J Sports Med 2011; 32: 415–421.

21.

Bastida Castillo

Gómez Carmona

De la cruz sánchez

, et al. Accuracy, intra- and inter-unit reliability, and comparison between GPS and UWB-based position-tracking systems used for time–motion analyses in soccer. Eur J Sport Sci 2018; 18: 450–457.

22.

Bastida-Castillo

Gómez-Carmona

De la Cruz-Sánchez

, et al. Accuracy and inter-unit reliability of ultra-wide-band tracking system in indoor exercise. Appl Sci 2019; 9: 939.

23.

Cohen

. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, N.J: L. Erlbaum Associates, 1988, 567 p.

24.

M. Oliva-Lozano

Gómez-Carmona

Fortes

, et al. Effect of training day, match, and length of the microcycle on workload periodization in professional soccer players: a full-season study. Biol Sport 2022; 39: 397–406.

25.

De Dios-Álvarez

Lorenzo-Martínez

Padrón-Cabo

, et al. Small-sided games in female soccer players: a systematic review. J Sports Med Phys Fitness 2022; 62: 1474–1480.

26.

Andersson

HÅ

Randers

Heiner-Møller

, et al. Elite female soccer players perform more high-intensity running when playing in international games compared with domestic league games. J Strength Cond Res 2010; 24: 912–919.

27.

Castellano

Errekagorri

Los Arcos

, et al. Tell me how and where you play football and I’ll tell you how much you have to run. Biol Sport 2022; 39: 607–614.

Analysis of running performance in the two main Spanish Women's football leagues: A case study

Abstract

Keywords

Introduction

Methods

Sample

Physical variables

Matches

Type of training sessions

Procedures

Statistical analysis

Results

Intra-category and inter-session comparison

Intra-session and inter-category comparison

Discussion

Footnotes

Declaration of conflicting interests

Funding

ORCID iDs

References