Interpreting Weekly External Load in Professional Soccer: A Position-Based and Context-Driven Approach for the “Real World” Setting

doi:10.21203/rs.3.rs-4831352/v1

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Research Article

Interpreting Weekly External Load in Professional Soccer: A Position-Based and Context-Driven Approach for the “Real World” Setting

https://doi.org/10.21203/rs.3.rs-4831352/v1

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Purpose

This study analyzed the weekly external load of professional soccer players with two main aims: 1) to describe the external load based on match-contextual difficulty and playing position; 2) to compare the external load in contexts of low and high match-contextual difficulty.

Methods

Eighteen professional soccer players were monitored over 13 weeks using GPS units and accelerometers. Players participating for at least 60 minutes in non-congested weeks were analyzed for total distance, distances covered at various speeds and acceleration levels, and Player Load. Match difficulties were categorized as "high" (score > 10) or "low" (score ≤ 10) and determined using match location and quality of opposition.

Results

The results revealed that the highest external loads occurred mid-week, decreasing towards the week's end, with external defenders and midfielders facing higher demands than central defenders and forwards. In low-difficulty scenarios (p < 0.001–0.030), external loads were higher than in high-difficulty scenarios, particularly on days preceding a match (MD-4 to MD-2). Conversely, high-difficulty matches increased distance and mechanical work on specific days (MD-3 and MD-1) (p < 0.001–0.020).

Conclusion

The findings suggest that external load varies significantly with match context, offering valuable insights for tailoring training loads according to position and upcoming match difficulty.

Match demands

Load monitoring

Association football

Team Sports

Sport Science

In soccer, the practice of load monitoring involves continuous and systematic analysis of data to aid coaches in monitoring both the externally designated training load, which includes metrics like distance and accelerometry-based data, and the internal responses of players throughout the season, such as their perceived exertion and heart rate [1]. Both internal and external training loads serve as metrics to gauge each player’s overall exposure to training and competitive activities [2]. However, skillfully integrating scientific recommendations into the design of daily external prescribed loads is a constantly evolving, intricate, and demanding task for sports scientists and technical staff [3]. Factors such as individual characteristics (e.g., playing position) and contextual elements (e.g., match location and the quality of the opposition) significantly influence the external load during training and match-play [4–6]. Therefore, enhancing soccer performance requires an optimized process for designing training regimens and monitoring external load, which must be tailored to individual and contextual factors.

A previous study proposed a practical approach for soccer coaches on how to use external load data obtained using global positioning system (GPS) for training load monitoring at both team and individual level [7]. This includes reliable and relevant GPS and accelerometry-based parameters across three distinct levels of analysis [8]: i) typical distances covered in different velocity zones (e.g., total distance covered above 19.8 km·h^− 1); ii) all events related to changes in velocity (e.g., number and distances in high accelerations [> 2 m·s²] and high decelerations [< -2 m·s²]); iii) all events derived from inertial sensors/accelerometers (e.g., PlayerLoad). Therefore, individual players' specific external load profiles during matches can be used to plan monthly, weekly, and daily training loads [7]. For instance, drawing from published data in professional soccer primarily from Europe, one approach to external load planning involves gradually increasing the chronic external load on a monthly scale, adjusting the match reference weekly. This could include multiplying the total distance by 2.8 in week 1, 3.2 in week 2, 3.4 in week 3, and 2.6 in week 4 [7]. Additionally, the authors suggested a weekly factor based on playing positions (i.e., center back, midfielder, wide midfielder, and attacks). This proposal is helpful and can notably assist coaches and sports scientists in prescribing external load in professional soccer.

Previous studies have reported that contextual factors also influence the external load parameters in training sessions [4] and match-play during soccer practice (e.g., [5]). For example, home matches played against strong opponents have shown higher values of total distance covered and high-intensity actions compared to away matches [9]. Furthermore, increased distance-based volume metrics and mechanical work have been observed during the midweek training session (e.g., three days before the match, MD-3) when facing lower-ranking teams as compared to medium-ranking opponents [4]. Hence, it seems reasonable to consider incorporating the match-contextual difficulty, including factors such as match location and the quality of opponents, when planning the weekly external load.

Therefore, the aims of this study were twofold: i) to describe the weekly external load according to match-contextual difficulty (based on match location and quality of opposition) and playing position (i.e., central/external defenders, central/external midfielders, forwards) over the course of the competition; ii) to compare the external load between low and high match-contextual difficulty in professional soccer players. These results can aid coaches and sports scientists in prescribing the external load throughout the season, considering individual and contextual factors.

Study design

This observational, longitudinal, and retrospective study analyzed a professional soccer team’s performance during 2021 season in the Brazilian National 3rd Division League, from May 29 to November 06. The focus was on a team that achieved promotion to the Brazilian National 2nd Division League at the season's end. Distance- and accelerometry-based measures were recorded using GPS devices (Playertek) throughout the competition. To minimize confounding factors and more accurately understand the effects of match-contextual difficulty on weekly load responses, only athletes who played ≥ 60 min[6] during non-congested weeks were considered for data analysis (i.e., weeks when the team had only one match [10, 11]). The days leading up to each match were analyzed to assess weekly load distribution according to match-contextual difficulty: four days before the match (MD-4), three days before the match (MD-3), two days before the match (MD-2), and one day before the match (MD-1) [4]. The season comprised 52 training sessions and 13 matches, resulting in six wins, four draws, and three losses. Match-contextual difficulty was calculated using a score included match location and quality of opposition, with two clusters identified using k-means method: low and high.

Participants

Eighteen professional male outfield soccer players (age: 25.6 ± 4.2 years; height: 179.9 ± 6.0 cm; body mass: 79.8 ± 6.9 kg) from the team in the Brazilian National 3rd Division League participated in this study. Players were assigned to one playing position by the head coach after each match: external defenders (n = 4), central defenders (n = 2), external midfielders (n = 3), central midfielders (n = 6), and forwards (n = 3). Goalkeepers were excluded due to their specific roles during match play [12]. Inclusion required participation in ≥ 60 min of play. Participants were required to have played in at least 60 minutes of play to be included. All players provided written consent. The study was approved by the Human Research Ethics Committee of the Federal University of Espírito Santo (CEFD: 10954/2021) and conducted according to the ethical guidelines of the Declaration of Helsinki for studies involving humans.

Dependent Variables

Players’ activities in training sessions and matches were monitored with Playertek GPS devices (Playertek by Catapult, Melbourne, Australia), featuring a 10 Hz model with a triaxial accelerometer, gyroscope, and magnetometer, each with a 100 Hz sampling rate. Previous studies have demonstrated theses devices’ high accuracy, validity, and inter-unit reliability [13–15].

Before each session or match, players were fitted with belts positioned at the center of their upper back. The devices were checked for functionality, and after each session or match, they were collected and placed on a docking station. To avoid inter-unit errors, players used the same device throughout the season [16]. Analyzed variables included: i) total distance covered (TD; meters); ii) total distance covered in high-speed running (HSR: 19.8–25.1 km·h^− 1; meters); iii) total distance covered in sprint running (SR: ≥ 25.2 km·h^− 1; meters); iv) total distance covered in high-acceleration (ACC: > 2 m·s2; meters); vi) total distance covered in high-deceleration (DEC < -2 m·s2; meters); vi) Player Load (PL; a.u.), which sums the accelerations across all axes of the internal tri-axial accelerometer, accounting for the instantaneous rate of change of acceleration and divided by a scaling factor (100). The speed thresholds are consistent with those reported in a previous systematic review [17].

Independent Variables

To quantify each week’s match-contextual difficulty, the total score included two factors: (i) match location (away with travel = 3; away = 2; home = 1); (ii) quality of opposition (top 4 teams = 12 − 9; middle 3 teams = 8 − 6; bottom 3 teams = 5 − 3) [18]. After calculation, the total score was classified into two levels of match-contextual difficulty: high (n = 255 individual observations) and low (n = 320 individual observations). The cutoff value for “high” or “low” classification was determined based on the values obtained throughout the season. With maximum score of 15, a weekly context above 50% (i.e., > 10) was classified as “high”, and a score of 50% or less (i.e., ≤ 10 total score) as “low”. Table 1 illustrates the scores for each factor and the total score representing match-contextual difficulty, calculated week-by-week.

Table 1

Scores for each factor and total score match-contextual difficulty for each week of the year are included in this study.
Week of the year	Match location	Quality of opposition	Total score	Match-contextual difficulty
26	1	10	11	High
27	1	2	3	Low
29	2	4	6	Low
30	1	6	7	Low
34	1	1	2	Low
36	3	2	5	Low
37	1	4	5	Low
38	1	3	4	Low
40	1	11	12	High
42	1	12	13	High
43	3	12	15	High
44	1	14	15	High
45	3	11	14	High

Insert Table 1 near here

Statistical analysis

The data distribution was checked and confirmed using the Shapiro-Wilk test. Results were reported as mean and minimum–maximum values. To account for the non-independence of data sampled from the same individuals across multiple matches, separate linear mixed models were performed. These models compared match-contextual difficulty (high vs. low) as fixed effects, with "player ID" included as a random effect. Additionally, the effect size was reported, calculated using the Hopkins threshold [19] as follows: <0.2 = trivial, 0.2 to 0.6 = small, > 0.6 to 1.2 = medium, > 1.2 to 2.0 = large, > 2.0 to 4.0 = very large, and > 4.0, almost perfect. The results were analyzed using SPSS Statistics for Windows, version 22.0. The significance level was set at p < 0.05.

Tables 2 and 3 provide an overall view of TD, HSR, SPR, ACC, DEC, and PL across the weekly, match day, training days (MD-4, MD-3, MD-2, and MD-1), and game across season. These measures are broken down by weekly, match day, training days (MD-4, MD-3, MD-2, and MD-1), and game reference for each position. Overall, all positions presented the highest running output on MD-3, while the lowest running output was observed on MD-1 for all positions. The data from MD-4 and MD-3 indicated higher ACC/DEC and HRS/SR, respectively. The dynamics of the two days before a match (MD-2 and MD-1) showed a moderate training load, followed by a low training load for the team. External defenders and external/central midfielder presented a high weekly load during the competition. Specifically, external defenders and midfielders exhibited the highest HSR and SR, whereas central defenders and forwards had the lowest running output.

Game reference is calculated as the mean values of GPS parameters during official matches. For each training day, the sum of loads per week for each distance and accelerometry-based measure is calculated and weighted arbitrarily by a factor of match reference for all positions. Generally, all positions showed a similar distribution of game reference to the absolute values of external load. In addition, it appears that the mechanical load (ACC, DEC) accumulated during the week presented higher values than the distance-based volume measures (HSR, SR) accumulated over the same period.,

Table 2

Overview of the high match-contextual difficulty in the weekly, match day, training days, and game reference of the distance and accelerometry-based measures for each position over the season.
Positions	MD-4	MD-3	MD-2	MD-1	MD	wTL
Positions	TD (m)	TD (m)	TD (m)	TD (m)	TD (m)	TD (m)
External defenders	0.43 4169.1 (2508.0–7792.0)	0.56 5459.0 (4259.0–6435.0)	0.35 3431.2 (2456.0–4113.0)	0.27 2599.1 (2027.0–3265.0)	1.00 9704.5 (7139.0–10875.0)	2.52 24487.5 (18789–31370.0)
Central defenders	0.44 4257.5 (2516.0–6334.0)	0.50 4830.3 (2681–5980.0)	0.32 3099.1 (2151.0–4188.0)	0.26 2489.6 (1857–3415.0)	1.00 9633.4 (9075.0–10256.0)	2.50 24113.3 (20883.0–27549.0)
Central midfilders	0.46 4548.9 (2409.0–7124.0)	0.59 5805.6 (3716.0–7426.0)	0.37 3618.7 (2307.0–4343.0)	0.30 2994.1 (2302.0–3915.0)	1.00 9872.9 (8250.0–12336.0)	2.70 26690.4 (22159.0–31873.0)
External midfilders	0.40 3981.3 (3328.0–5262.0)	0.50 4948.3 (3660.0–6563.0)	0.42 4116.0 (3582.0–4555.0)	0.26 2608.0 (2039.0–3376.0)	1.00 9914.8 (8641.0–11323.0)	2.58 25568.5 (23175.0–26826.0)
Forwards	0.59 4517.0 (3933.0–5518.0)	0.68 5211.0 (4721.0–5701.0)	0.33 2548.0 (2548.0–2548.0)	0.32 2470.0 (1978–2962.0)	1.00 7644.3 (6559.0–9361.0)	2.59 19804.0 (17841.0–21340.0)
	HSR (m)	HSR (m)	HSR (m)	HSR (m)	HSR (m)	HSR (m)
External defenders	0.25 192.7 (30.0–384.0)	0.56 434.5 (264.0–556.0)	0.27 213.1 (48.0–499.0)	0.10 80.6 (38.0–119.0)	1.00 781.5 (385.0–985.0)	2.11 1645.5 (1218.0–2275.0)
Central defenders	0.14 61.0 (10.0–193.0)	0.40 181.9 (27.0–246.0)	0.21 93.4 (6.0–229.0)	0.07 29.9 (1.0–85.0)	1.00 450.9 (280.0–652.0)	1.82 819.8 (567.0–1248.0)
Central midfilders	0.17 129.4 (6.0–418.0)	0.45 353.8 (159.0–605.0)	0.22 175.3 (0.0–424.0)	0.11 86.3 (12.0–164.0)	1.00 780.4 (383.0–1213.0)	1.99 1550.7 (950.0–2193.0)
External midfilders	0.20 181.5 (58.0–346.0)	0.39 351.2 (242.0–542.0)	0.26 234.8 (83.0–337.0)	0.08 74.2 (0.0–163.0)	1.00 899.0 (438.0–1624.0)	1.94 1740.7 (1046.0–2629.0)
Forwards	0.13 78.7 (53.0–99.0)	0.58 350.0 (187.0–513.0)	0.03 21.0 (21.0–21.0)	0.06 34.0 (5.0–63.0)	1.00 603.0 (439.0–913.0)	1.60 963.0 (765.0–1095.0)
	SPR (m)	SPR (m)	SPR (m)	SPR (m)	SPR (m)	SPR (m)
External defenders	0.16 30.0 (1.0–53.0)	0.57 105.1 (0.0–223.0)	0.29 53.2 (4.0–120.0)	0.05 9.1 (1.0–18.0)	1.00 182.9 (88.0–309.0)	2.01 368.0 (242.0–588.0)
Central defenders	0.09 8.4 (0.0–49.0)	0.39 37.3 (0.0–102.0)	0.15 14.2 (0.0–47.0)	0.00 0.2 (0.0–2.0)	1.00 95.6 (24.0–150.0)	1.63 156.2 (36.0–313.0)
Central midfilders	0.10 16.3 (0.0–81.0)	0.31 49.2 (0.0–134.0)	0.13 20.3 (0.0–83.0)	0.06 9.9 (0.0–33.0)	1.00 160.1 (56.0–317.0)	1.69 270.2 (89.0–524.0)
External midfilders	0.07 7.7 (0.0–49.0)	0.25 67.5 (22.0–148.0)	0.13 35.8 (3.0–78.0)	0.05 13.8 (0.0–78.0)	1.00 271.3 (63.0–549.0)	1.50 406.2 (158.0–808.0)
Forwards	0.02 2.0 (1.0–4.0)	0.58 73.0 (18.0–128.0)	0.01 1.0 (1.0–1.0)	0.01 0.7 (0.0–1.0)	1.00 125.7 (82.0–199.0)	1.41 177.7 (117.0–212.0)
	ACC (m)	ACC (m)	ACC (m)	ACC (m)	ACC (m)	ACC (m)
External defenders	0.59 180.4 (118.0–372.0)	0.72 221.0 (158.0–291.0)	0.46 141.2 (94.0–207.0)	0.36 109.3 (84.0–128.0)	1.00 306.5 (227.0–387.0)	3.01 921.9 (646.0–1245.0)
Central defenders	0.59 154.2 (85.0–207.0)	0.53 136.7 (80.0–225.0)	0.40 104.2 (62.0–154.0)	0.32 82.7 (46.0–120.0)	1.00 259.5 (186.0–322.0)	2.83 733.1 (500.0–1006.0)
Central midfilders	0.48 170.2 (112.0–247.0)	0.56 199.0 (135.0–273.0)	0.43 152.2 (119.0–209.0)	0.26 91.2 (65.0–161.0)	1.00 353.2 (220.0–514.0)	2.56 904.4 (770.0–1189.0)
External midfilders	0.48 170.2 (112.0–247.0)	0.56 199.0 (135.0–273.0)	0.43 152.2 (119.0–209.0)	0.26 91.2 (65.0–161.0)	1.00 353.2 (220.0–514.0)	2.73 965.7 (684.0–1296.0)
Forwards	0.76 198.0 (188.0–204.0)	0.80 209.5 (188.0–231.0)	0.53 139.0 (139.0–139.0)	0.38 98.0 (75.0–121.0)	1.00 261.0 (208.0–364.0)	3.02 789.3 (689.0–841.0)
	DEC (m)	DEC (m)	DEC (m)	DEC (m)	DEC (m)	DEC (m)
External defenders	0.49 193.6 (112.0–441.0)	0.66 260.6 (177.0–378.0)	0.41 161.2 (118.0–207.0)	0.29 115.2 (85.0–146.0)	1.00 391.9 (299.0–482.0)	2.76 1081.2 (750.0–1518.0)
Central defenders	0.56 177.1 (67.0–270.0)	0.53 167.6 (88–287.0)	0.39 123.2 (74.0–179.0)	0.30 93.8 (53.0–144.0)	1.00 315.8 (206.0–416.0)	2.76 872.8 (578.0–1139.0)
Central midfilders	0.53 221.4 (98.0–404.0)	0.65 270.6 (181.0–414.0)	0.37 152.3 (62.0–255.0)	0.29 118.8 (63.0–182.0)	1.00 414.3 (292.0–541.0)	2.83 1171.3 (901.0–1572.0)
External midfilders	0.46 202.7 (126.0–337.0)	0.51 226.8 (148.0–322.0)	0.40 178.8 (126.0–268.0)	0.22 95.8 (60.0–198.0)	1.00 442.0 (242.0–694.0)	2.58 1141.2 (761.0–1649.0)
Forwards	0.77 287.3 (271.0–306.0)	0.77 287.0 (251.0–323.0)	0.50 185.0 (185.0–185.0)	0.36 136.0 (97.0–175.0)	1.00 373.3 (230.0–549.0)	2.98 1111.3 (1030.0–1231.0)
	PL (a.u.)	PL (a.u.)	PL (a.u.)	PL (a.u.)	PL (a.u.)	PL (AU)
External defenders	0.51 218.2 (146.0–392.0)	0.64 273.1 (219.0–322.0)	0.45 190.4 (135.0–233.0)	0.35 148.9 (128.0–184.0)	1.00 424.8 (317.0–508.0)	2.85 1210.7 (902.0–1551.0)
Central defenders	0.53 218.8 (123.0–325.0)	0.57 235.9 (140.0–301.0)	0.40 162.9 (116.0–205.0)	0.33 136.3 (112.0–179.0)	1.00 410.7 (390.0–432.0)	2.82 1159.9 (969.0–1334.0)
Central midfilders	0.54 221.1 (133.0–375.0)	0.65 264.9 (186.0–342.0)	0.45 183.8 (120.0–243.0)	0.36 148.3 (119.0–216.0)	1.00 406.8 (314.0–519.0)	2.99 1217.5 (943.0–1588.0)
External midfilders	0.48 204.2 (175.0–262.0)	0.57 241.0 (178.0–327.0)	0.50 211.7 (194–252.0)	0.33 142.3 (132–171.0)	1.00 425.2 (365.0–491.0)	2.88 1224.3 (1137.0–1305.0)
Forwards	0.71 225.3 (196.0–276.0)	0.78 247.0 (233.0–261.0)	0.47 148.0 (148.0–148.0)	0.42 133.0 (119.0–147.0)	1.00 315.3 (270.0–393.0)	2.97 937.0 (816.0–1015.0)
Note: TD: total distance (meters); HSR: high speed running (19.8–25.1 km.h^− 1; meters); SR: sprint running (≥ 25.2 km.h^− 1; meters); ACC: distance covered in high-acceleration (> 2 m.s^− 2; meters); DEC: distance covered in high-deceleration (< -2 m.s^− 2; meters); PL: Player Load (arbitrary units). Italic: game reference. The data are described by the mean (minimum – maximum).

Table 3

Overview of the low match-contextual difficulty in the weekly, match day, training days, and match reference of the distance and accelerometry-based measures for each position over the season.
Positions	MD-4	MD-3	MD-2	MD-1	MD	wTL
Positions	TD (m)	TD (m)	TD (m)	TD (m)	TD (m)	TD (m)
External defenders	0.42 4342.3 (2507.0–6721.0)	0.55 5705.8 (2654.0–7440.0)	0.45 4660.5 (3007.0–6529.0)	0.27 2778.7 (2340.0–3131.0)	1.00 10396.7 (9109.0–11456.0)	2.65 27537.2 (20697.0–32835.0)
Central defenders	0.46 4307.0 (2748.0–5909.0)	0.53 4925.6 (2428.0–6654.0)	0.48 4487.9 (3307.0–5621.0)	0.26 2399.9 (1794.0–2642.0)	1.00 9317.8 (8686.0–9760.0)	2.73 25438.1 (20565.0–28568.0)
Central midfilders	0.46 4734.1 (2455.0–7952.0)	0.61 6182.7 (2778.0–8656.0)	0.45 4604.7 (2755.0–6577.0)	0.28 2888.3 (2220.0–4248.0)	1.00 10189.0 (6717.0–12129.0)	2.72 27685.3 (15859.0–34264.0)
External midfilders	0.63 5196.1 (2462.0–6722.0)	0.67 5513.0 (3106–7321.0)	0.65 5338.1 (4421.0–6453.0)	0.35 2893.4 (2474.0–3129.0)	1.00 8235.1 (7126.0 – 9976.0)	3.22 26526.3 (22418.0–31004.0)
Forwards	0.64 4860.1 (2599.0–6892.0)	0.73 5623.6 (3353.0–7149.0)	0.64 4918.1 (3445.0–6874.0)	0.33 2553.1 (2432.0–2727.0)	1.00 7653.6 (6605.0–8431.0)	3.35 25608.6 (21457.0–29341.0)
	HSR (m)	HSR (m)	HSR (m)	HSR (m)	HSR (m)	HSR (m)
External defenders	0.14 121.3 (17.0–308.0)	0.36 321.0 (41.0–538.0)	0.23 204.2 (65.0–332.0)	0.07 64.8 (29.0–107.0)	1.00 894.1 (432.0–1368.0)	1.78 1595.9 (1015.0–2336.0)
Central defenders	0.25 101.6 (5.0–251.0)	0.41 163.6 (11.0–347.0)	0.17 68.6 (3.0–144.0)	0.13 50.6 (14.0–106.0)	1.00 399.8 (183.0–562.0)	1.89 756.9 (507.0–1222.0)
Central midfilders	0.21 151.1 (9.0–273.0)	0.31 219.1 (5.0–563.0)	0.30 213.9 (28.0–514.0)	0.09 66.1 (0.0–197.0)	1.00 716.4 (338.0–1096.0)	1.87 1341.0 (481.0–1886.0)
External midfilders	0.33 274.6 (63.0–567.0)	0.32 274.3 (14.0–572.0)	0.40 334.6 (157.0–617.0)	0.10 87.6 (22.0–155.0)	1.00 844.3 (522.0–1244.0)	2.11 1781.0 (1926.0–2654.0)
Forwards	0.26 165.7 (7.0–259.0)	0.36 229.4 (21.0–511.0)	0.32 207.3 (104.0–378.0)	0.05 31.0 (14.0–62.0)	1.00 645.3 (393.0–832.0)	1.98 1278.7 (970.0–1559.0)
	SPR (m)	SPR (m)	SPR (m)	SPR (m)	SPR (m)	SPR (m)
External defenders	0.06 14.8 (0.0–62.0)	0.17 42.6 (0.0–120.0)	0.17 42.4 (1.0–95.0)	0.02 4.1 (0.0–16.0)	1.00 247.2 (118.0–457.0)	1.42 350.0 (187.0–569.0)
Central defenders	0.20 19.6 (0.0–61.0)	0.20 19.6 (0.0–62.0)	0.16 15.5 (0.0–45.0)	0.07 7.1 (0.0–27.0)	1.00 96.9 (16.0–146.0)	1.64 158.8 (69.0–247.0)
Central midfilders	0.22 24.3 (0.0–69.0)	0.11 12.2 (0.0–95.0)	0.30 33.3 (0.0–169.0)	0.04 4.9 (0.0–19.0)	1.00 110.1 (34.0–210.0)	1.72 189.1 (48.0–351.0)
External midfilders	0.18 44.7 (4.0–125.0)	0.21 53.6 (0.0–139.0)	0.33 82.9 (32.0–259.0)	0.05 11.6 (0.0–29.0)	1.00 253.4 (124.0–469.0)	1.74 440.6 (233.0–796.0)
Forwards	0.21 25.3 (0.0–62.0)	0.17 20.0 (0.0–85.0)	0.32 38.3 (0.0–116.0)	0.03 3.0 (0.0–9.0)	1.00 119.7 (69.0–185.0)	1.72 206.3 (95.0–323.0)
	ACC (m)	ACC (m)	ACC (m)	ACC (m)	ACC (m)	ACC (m)
External defenders	0.56 192.7 (115.0–295.0)	0.66 224.3 (92.0–323.0)	0.50 172.5 (89.0–256.0)	0.29 99.6 (79.0–129.0)	1.00 341.8 (280.0–419.0)	2.97 1016.1 (610.0–1261.0)
Central defenders	0.63 154.8 (93.0–217.0)	0.69 169.4 (87.0–264.0)	0.59 144.4 (95.0–206.0)	0.31 76.0 (30.0–101.0)	1.00 245.0 (1558.0–318.0)	3.22 789.5 (603.0–997.0)
Central midfilders	0.59 182.1 (96.0–310.0)	0.71 220.0 (82.0–341.0)	0.49 152.6 (65.0–237.0)	0.30 91.8 (2.0–137.0)	1.00 308.8 (177.0–439.0)	3.01 928.3 (557.0–1261.0)
External midfilders	0.79 231.6 (109.0–394.0)	0.72 213.8 (134.0–341.0)	0.73 216.0 (121.0–297.0)	0.33 98.1 (70.0–154.0)	1.00 294.9 (224.0–390.0)	3.48 1025.4 (701.0–1410.0)
Forwards	0.81 197.0 (101.0–287.0)	0.93 225.4 (167.0–281.0)	0.84 205.0 (142.0–315.0)	0.35 85.6 (50.0–120.0)	1.00 242.9 (198.0–307.0)	3.94 955.9 (830.0–1100.0)
	DEC (m)	DEC (m)	DEC (m)	DEC (m)	DEC (m)	DEC (m)
External defenders	0.53 231.3 (155.0–314.0)	0.62 271.0 (123.0–367.0)	0.43 189.0 (101.0–316.0)	0.25 110.2 (72.0–153.0)	1.00 437.2 (380.0–497.0)	2.79 1220.9 (777.0–1425.0)
Central defenders	0.61 190.2 (129.0–277.0)	0.66 206.7 (109.0 – 320.0)	0.51 158.0 (94.0–252.0)	0.29 91.1 (42.0–132.0)	1.00 312.2 (218.0–438.0)	3.07 958.2 (707.0–1199.0)
Central midfilders	0.50 222.2 (117.0–373.0)	0.66 290.0 (95.0–458.0)	0.42 186.1 (82.0–305.0)	0.25 112.3 (0.0–151.0)	1.00 441.3 (303.0–585.0)	2.76 1217.1 (737.0–1635.0)
External midfilders	0.70 273.7 (117.0–519.0)	0.64 252.3 (196.0–488.0)	0.64 252.1 (147.0–398.0)	0.26 102.4 (65.0–174.0)	1.00 391.4 (290.0–567.0)	3.16 1237.6 (779.0–1908.0)
Forwards	0.73 277.7 (138.0–449.0)	0.81 306.0 (203.0–440.0)	0.68 258.4 (173.0–385.0)	0.29 108.7 (54.0–156.0)	1.00 378.7 (296.0–492.0)	3.51 1329.6 (1166.0–1517.0)
	PL (a.u.)	PL (a.u.)	PL (a.u.)	PL (a.u.)	PL (a.u.)	PL (AU)
External defenders	0.52 242.8 (157.0–359.0)	0.64 296.8 (179.0–360.0)	0.55 254.9 (192.0–350.0)	0.32 146.8 (120.0–195.0)	1.00 465.9 (389.0–519.0)	2.98 1388.5 (1018.0–1658.0)
Central defenders	0.59 235.0 (165.0–307.0)	0.65 257.3 (163.0–319.0)	0.59 234.6 (179.0–289.0)	0.32 128.9 (88.0–188.0)	1.00 398.8 (371.0–412.0)	3.15 1254.6 (1094.0–1401.0)
Central midfilders	0.58 248.6 (161.0–444.0)	0.70 298.3 (191.0–388.0)	0.56 237.7 (177.0–343.0)	0.33 141.3 (108.0–206.0)	1.00 425.6 (340.0–541.0)	3.09 1314.5 (843.0–1731.0)
External midfilders	0.76 269.1 (166.0–339.0)	0.78 278.8 (201.0–352.0)	0.77 272.5 (225.0–315.0)	0.39 139.3 (118.0– 153.0)	1.00 355.4 (305.0–432.0)	3.61 1281.4 (1054.0–1465.0)
Forwards	0.80 254.1 (160.0–325.0)	0.88 279.1 (204.0–354.0)	0.80 254.0 (193.0–352.0)	0.43 136.0 (109.0–186.0)	1.00 317.0 (278.0–357.0)	3.91 1240.3 (1093.0–1420.0)
TD: total distance (meters); HSR: high speed running (19.8–25.1 km.h^− 1; meters); SR: sprint running (≥ 25.2 km.h^− 1; meters); ACC: distance covered in high-acceleration (> 2 m.s^− 2; meters); DEC: distance covered in high-deceleration (< -2 m.s^− 2; meters); PL: Player Load (arbitrary units). Italic: game reference. The data are described by the mean (minimum – maximum).

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The comparison of the match-contextual difficulty in the weekly load, as well as specific days leading up to the match (MD-4, MD-3, MD-2, MD-1), and MD for distance and accelerometry based-measures across all positions in the Brazilian National 3rd Division League are displayed in Tables 4–9. Low match-contextual difficulty showed an increase than the high match-contextual difficulty in wTD, wACC, wDEC, and wPL (p < 0.001–0.030; ES = small – medium; Table 4). No significant changes were observed in wHSR and wSR between high and low match-contextual difficulty (p = 0.338–0.420; ES = trivial; Table 4). When examining changes on MD-4 and MD-3, low match-contextual difficulty demonstrated significant improvements in PL (p = 0.004–0.014; ES = small; Tables 5 and 6). Conversely, high match-contextual difficulty in noted higher values of HSR and SR than low match-contextual difficulty on MD-3 (p < 0.001–0.005; ES = medium; Table 6). No significant differences were observed for other GPS-derived variables when comparing both groups (p > 0.05, ES = trivial – small; Tables 5 and 6). Significantly greater TD, ACC, DEC, and PL were reported on MD-2 for low match-contextual difficulty compared to high match-contextual difficulty (p < 0.001; ES = medium – large; Table 7). However, no significant differences were found for HSR and SR on MD-2 (p = 0.095–0.112; ES = small; Table 7). On MD-1, soccer players exhibited significantly higher in ACC in a high match-contextual difficulty than low match-contextual difficulty (p = 0.020; ES = small; Table 8). No significant differences in other GPS-derived variables were observed between high and low match-contextual difficulty on MD-1 (p > 0.05; ES = trivial – small; Table 8). No significant differences in any distance and accelerometry based-measures was found between high and low match-contextual difficulty on the MD (p > 0.05; ES = trivial; Table 9).

Table 4

Differences between high and low match-contextual difficulty in the weekly for distance and accelerometry based-measures for all positions over the season.
Variables	Match-contextual difficulty		Δ%	p value	ES (inference)
Variables	High (n = 52)	Low (n = 65)	Δ%	p value	ES (inference)
wTD (m)	25126.0 (17841.0–31873.0)	26805.4 (15859–34264.0) ^*	6.7	0.006	0.481 (small)
wHSR (m)	1390.1 (567.0–2629.0)	1313.6 (481.0–2654.0)	5.5	0.420	0.158 (trivial)
wSR (m)	274.9 (36.0–808.0)	247.6 (48.0–796.0)	9.9	0.338	0.183 (trivial)
wACC (m)	869.0 (500.0–1296.0)	930.9 (557.0–1410.0) ^*	7.1	0.018	0.342 (small)
wDEC (m)	1076.4 (578.0–1649.0)	1176.8 (707.0–1908.0) ^*	9.3	0.030	0.417 (small)
wPL (a.u.)	1187.4 (816.0–1588.0)	1304.4 (843.0–1731.0) ^*	9.9	< 0.001	0.757 (medium)
wTD: weekly total distance (meters); wHSR: weekly high-speed running (19.8–25.1 km.h^− 1; meters); wSR: weekly sprint running (≥ 25.2 km.h^− 1; meters); wACC: weekly distance covered in high-acceleration (> 2 m.s^− 2; meters); wDEC: weekly distance covered in high-deceleration (< -2 m.s^− 2; meters); wPLrel: weekly Player Load (arbitrary units). p-value at alpha level 0.05. ES: effect size. * High < Low. The data are described by the mean (minimum – maximum).

Table 5

Differences between high and low match-contextual difficulty in the MD-4 for distance and accelerometry based-measures for all positions over the season.
Variables	Match-contextual difficulty (MD-4)		Δ%	p value	ES (inference)
Variables	High (n = 50)	Low (n = 62)	Δ%	p value	ES (inference)
TD (m)	4338.8 (2409.0–7792.0)	4625.5 (2455.0–7952.0)	6.6	0.298	0.199 (trivial)
HSR (m)	130.2 (6.0–418.0)	149.7 (5.0–567.0)	15.0	0.289	0.192 (trivial)
SR (m)	16.6 (0.0–81.0)	23.8 (0.0–125.0)	43.4	0.129	0.315 (small)
ACC (m)	175.2 (58.0–372.0)	185.3 (93.0–394.0)	5.8	0.373	0.166 (trivial)
DEC (m)	207.8 (67.0–441.0)	228.9 (117.0–519.0)	9.3	0.193	0.319 (small)
PL (a.u.)	218.2 (123.0–392.0)	247.3 (157.0–444.0) ^*	13.3	0.014	0.473 (small)
TD: total distance (meters); HSR: high speed running (19.8–25.1 km.h^− 1; meters); SR: sprint running (≥ 25.2 km.h^− 1; meters); ACC: distance covered in high-acceleration (> 2 m.s^− 2; meters); DEC: distance covered in high-deceleration (< -2 m.s^− 2; meters); PL: Player Load (arbitrary units). p-value at alpha level 0.05. ES: effect size. * High < Low. The data are described by the mean (minimum – maximum).

Table 6

Differences between high and low match-contextual difficulty in the MD-3 for distance and accelerometry based-measures for all positions over the season.
Variables	Match-contextual difficulty (MD-3)		Δ%	p value	ES (inference)
Variables	High (n = 50)	Low (n = 63)	Δ%	p value	ES (inference)
TD (m)	5375.5 (2681.0–7429.0)	5657.8 (2428.0–8656.0)	5.3	0.279	0.195 (trivial)
HSR (m)	328.2 (27.0–605.0) ^§	229.9 (5.0–572.0)	-30.0	< 0.001	0.654 (medium)
SR (m)	60.7 (0.0–223.0) ^§	28.6 (0.0–139.0)	-52.9	0.005	0.744 (medium)
ACC (m)	188.9 (80.0–299.0)	209.5 (82.0–341.0)	11.0	0.057	0.325 (small)
DEC (m)	239.3 (88.0–414.0)	264.6 (95.0–488.0)	11.0	0.077	0.303 (small)
PL (a.u.)	256.0 (140.0–342.0)	284.3 (163.0–388.0) ^*	11.1	0.004	0.519 (small)
TD: total distance (meters); HSR: high speed running (19.8–25.1 km.h^− 1; meters); SR: sprint running (≥ 25.2 km.h^− 1; meters); ACC: distance covered in high-acceleration (> 2 m.s^− 2; meters); DEC: distance covered in high-deceleration (< -2 m.s^− 2; meters); PL: Player Load (arbitrary units). p-value at alpha level 0.05. ES: effect size. * High < Low. ^§ High > Low. The data are described by the mean (minimum – maximum).

Table 7

Differences between high and low match-contextual difficulty in the MD-2 for distance and accelerometry based-measures for all positions over the season.
Variables	Match-contextual difficulty (MD-2)		Δ%	p value	ES (inference)
Variables	High (n = 52)	Low (n = 65)	Δ%	p value	ES (inference)
TD (m)	3465.3 (2151.0–4555.0)	4714.8 (2755.0–6874.0) ^*	36.1	< 0.001	1.505 (large)
HSR (m)	163.7 (0.0–499.0)	194.8 (3.0–617.0)	19.0	0.095	0.256 (small)
SR (m)	26.8 (0.0–120.0)	37.9 (0.0–259.0)	41.4	0.112	0.283 (small)
ACC (m)	128.2 (56.0–209.0)	168.2 (65.0–315.0) ^*	31.2	< 0.001	0.873 (medium)
DEC (m)	150.6 (62.0–268.0)	196.5 (82.0–398.0) ^*	30.5	< 0.001	0.767 (medium)
PL (a.u.)	181.8 (116.0–252.0)	246.5 (177.0–352.0) ^*	35.6	< 0.001	1.681 (large)
TD: total distance (meters); HSR: high speed running (19.8–25.1 km.h^− 1; meters); SR: sprint running (≥ 25.2 km.h^− 1; meters); ACC: distance covered in high-acceleration (> 2 m.s^− 2; meters); DEC: distance covered in high-deceleration (< -2 m.s^− 2; meters); PL: Player Load (arbitrary units). p-value at alpha level 0.05. ES: effect size. * High < Low. The data are described by the mean (minimum – maximum).

Table 8

Differences between high and low match-contextual difficulty in the MD-1 for distance and accelerometry based-measures for all positions over the season.
Variables	Match-contextual difficulty (MD-1)		Δ%	p value	ES (inference)
Variables	High (n = 51)	Low (n = 65)	Δ%	p value	ES (inference)
TD (m)	2713.9 (1857.0–3915.0)	2725.7 (1794.0–4248.0)	0.4	0.924	0.028 (trivial)
HSR (m)	67.3 (0.0–164.0)	61.3 (0.0–197.0)	-9.0	0.336	0.144 (trivial)
SR (m)	7.4 (0.0–33.0)	5.8 (0.0–29.0)	-21.6	0.320	0.18 (trivial)
ACC (m)	97.5 (46.0–161.0) ^§	90.1 (2.0–154.0)	-7.6	0.020	0.292 (small)
DEC (m)	110.4 (53.0–198.0)	105.7 (0.0–174.0)	-4.2	0.153	0.147 (trivial)
PL (a.u.)	144.0 (112.0–216.0)	138.9 (88.0–206.0)	-3.5	0.114	0.251 (small)
TD: total distance (meters); HSR: high speed running (19.8–25.1 km.h^− 1; meters); SR: sprint running (≥ 25.2 km.h^− 1; meters); ACC: distance covered in high-acceleration (> 2 m.s^− 2; meters); DEC: distance covered in high-deceleration (< -2 m.s^− 2; meters); PL: Player Load (arbitrary units). p-value at alpha level 0.05. ES: effect size. ^§ High > Low. The data are described by the mean (minimum – maximum).

Table 9

Differences between high and low match-contextual difficulty in the MD for distance and accelerometry based-measures for all positions over the season.
Variables	Match-contextual difficulty (MD)		Δ%	p value	ES (inference)
Variables	High (n = 52)	Low (n = 65)	Δ%	p value	ES (inference)
TD (m)	9658.3 (6559.0–12336.0)	9469.2 (6605.0–12129.0)	-2.0	0.664	0.144 (trivial)
HSR (m)	708.0 (280.0–1624.0)	691.8 (183.0–1368.0)	-12.5	0.840	0.061 (trivial)
SR (m)	160.9 (24.0–549.0)	153.4 (16.0–469.0)	-4.6	0.320	0.08 (trivial)
ACC (m)	295.2 (186.0–514.0)	292.8 (158.0–439.0)	-0.8	0.980	0.035 (trivial)
DEC (m)	387.6 (206.0–694.0)	399.8 (218.0–585.0)	-3.1	0.484	0.129 (trivial)
PL (a.u.)	408.3 (270.0–519.0)	407.5 (278.0–541.0)	-0.2	0.942	0.014 (trivial)
TD: total distance (meters); HSR: high speed running (19.8–25.1 km.h^− 1; meters); SR: sprint running (≥ 25.2 km.h^− 1; meters); ACC: distance covered in high-acceleration (> 2 m.s^− 2; meters); DEC: distance covered in high-deceleration (< -2 m.s^− 2; meters); PL: Player Load (arbitrary units). p-value at alpha level 0.05. ES: effect size. The data are described by the mean (minimum–maximum).

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This study aimed to investigate the influence of match-contextual difficulty, specifically considering match location and the quality of opposition, on the weekly external load experienced by professional Brazilian soccer players over a competitive season. The main findings revealed that matches with less difficulty were associated with a significantly higher external load on MD-4, MD-3, and MD-2, compared to more difficult matches. However, higher mechanical work was observed during more difficult matches on MD-3 and MD-1.

A significant fluctuation in external load measures throughout the competitive period was reported, with the highest values observed during the middle weeks and the lowest values in the final weeks of the season. Previous studies have reported similar variations in weekly external load based on distance and accelerometry measures [20, 21]. These studies noted minimal external load variations during the first and last weeks of the season, while the greatest variations occurred during the in-season periods (i.e., middle weeks). This variation in external load could be attributed to several factors, including the accumulation of fatigue over the season [20], the intensity of the matches played during specific weeks [22], and the individualized recovery strategies employed [23]. Coaches and practitioners should take this weekly variation into account when programming training sessions and managing training load to optimize performance and minimize injury risk.

The position-specific analysis highlighted significant differences in the physical demands experienced by players in different on-field roles. External defenders and central midfielders exhibited higher weekly physical demands during the competition, while central defenders and forwards demonstrated the lowest running demands. A recent study underscored significant differences in external load demands based on players' positions during both training and official matches [24]. In the mentioned study [24], the wingers showed the highest external load demands during matches, while central backs and midfielders present the lowest demands. Another study on 18 professional soccer players found that the wing-backs achieved only 64% of match sprint peaks during microcycles, while other positions either matched or exceeded match values (107% for center-backs, 100% for center midfielders, and 107% for center forwards) [25]. These findings emphasize the importance of tailoring training regimens and load management strategies to the specific requirements of each position, encouraging coaches to develop position-specific training programs to enhance player performance.

Notable differences in external load measures based on match-contextual difficulty were reported in the present study. Specifically, matches characterized by low match-contextual difficulty were associated with significantly higher external load in certain weeks (MD-4, MD-3, and MD-2) compared to matches with high match-contextual difficulty. In contrast, higher mechanical work was observed during matches of higher contextual difficulty on MD-3 and MD-1. This suggests that players may engage in additional high-intensity activities, such as sprints and accelerations, when facing stronger opposition or more demanding playing conditions. These findings align with a recent study conducted on 22 professional soccer players [26], which found that players covered greater distances in sprints during matches against weaker opponents compared to matches against intermediate and strong opponents [26]. Players tend to exert more physical effort in matches perceived as less challenging, perhaps due to increased offensive opportunities or reduced defensive pressure.

Multiple studies consistently demonstrate that competing at one's home venue offers several advantages to soccer teams, including heightened goal-scoring prowess, improved passing proficiency, and enhanced disciplinary behavior [27]. The consequential home advantage effect profoundly influences soccer strategies, compelling teams to tailor their playing styles accordingly [27]. In fact, significant interactions have been identified between match location and the demands on TD, HSR, and SR distances [28], indicating that the match location (e.g., home or away) notably impacts external load demands. In this context, our findings underscore the importance of considering the location of matches and the quality of opposition when planning training loads. Coaches should adopt a nuanced approach, adjusting training intensity and volume based on the contextual factors surrounding each match.

The current study has certain limitations that warrant discussion. First, the study was limited a relatively small team sample size. Second, it did not incorporate internal load measurements, such as the rate of perceived exertion-based training load, heart rate-based metrics, and variations in well-being, which could have provided a more comprehensive understanding. Future research should consider including additional variables related to the contextual difficulty of matches, such as the number of training days leading up to the match. Additionally, it's important to note that this study exclusively focused on starting players who participated for most of the match (i.e., over 60 minutes). Future investigations should extend their scope to include substitute players and consider the effects of congested match schedules.

Notwithstanding the above-mentioned limitations, the present study highlights some potential practical implications. The observed variations in external load across different weeks and positions highlight the need for individualized training programs that consider the specific demands faced by each player. Furthermore, our findings emphasize the importance of incorporating match-contextual difficulty into load management strategies, as it significantly impacts the physical demands placed on players. Coaches should leverage this knowledge to optimize player performance, minimize injury risk, and enhance overall team success.

The present study highlights the significant impact of match-contextual difficulty on the weekly external load experienced by professional soccer players. Matches that were less challenging matches led to higher external loads, while more difficult matches resulted in increased mechanical work during specific periods. These findings underscore the need for individualized training programs that consider positional differences and adjust the weekly training load according to the match difficulty within the same microcycle.

Acknowledgments

The authors would like to thank Criciúma Sport Club (Criciúma, Brazil).

Author contributions

Each author contributed to both the conceptualization and execution of the research project. L.G.G., R.M.S., M.V.M.N., and D.A. processed the methodological assessment, performed analysis, and wrote and revised the original manuscript. B.P., A. P., R.A.A.L., F.V.,and F.V. wrote and revised the original manuscript. R.A. was involved in supervising the work. All authors have read and agreed to the published final version of the manuscript.

Funding

This study was funded, in part, by the Secretaria Nacional de Futebol e Defesa dos Direitos do Torcedor, Ministério do Esporte (Programa Academia e Futebol – edital número 1 de 2020), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (financial code: 001).

Data availability

The datasets generated during and analyzed during the current study are available from the corresponding author upon reasonable request.

Conflicts of interest

The authors declare no potential conflicts of interest.

Ethical approval

The ethical approval of the study was approved by the Human Research Ethics Committee (Centre of Physical Education and Sports, Federal University of Espírito Santo: 10954/2021) and was by ethical principles stated in the Declaration of Helsinki.

Consent for publication

Before the study began, all participants received informational sheets outlining the intention to publish, along with the option to receive copies of the submitted manuscripts.

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No competing interests reported.

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Interpreting Weekly External Load in Professional Soccer: A Position-Based and Context-Driven Approach for the “Real World” Setting

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Interpreting Weekly External Load in Professional Soccer: A Position-Based and Context-Driven Approach for the “Real World” Setting

Status:

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Abstract

Purpose

Methods

Results

Conclusion

Introduction

Methods

Study design

Participants

Dependent Variables

Independent Variables

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Statistical analysis

Results

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***Insert Table 4 near here***

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