Win, Draw, or Lose? Global Positioning System-Based Variables’ Effect on the Match Outcome: A Full-Season Study on an Iranian Professional Soccer Team

Abstract

The aim of the study was to determine the between-match and between-halves match variability of various Global Positioning System (GPS) variables and metabolic power average (MPA) in competitions, based on the match results obtained by professional soccer players over a full season. Observations on individual match performance measures were undertaken on thirteen outfield players competing in the Iranian Premier League. The measures selected for analysis included total duration, accelerations in zones (AccZ1, 2, and 3), decelerations in zones (DecZ1, 2, and 3), and MPA collected by the Wearable Inertial Measurement Unit (WIMU). The GPS manufacturer set the thresholds for the variables analyzed as follows: AccZ1 (<2 m.s−2); AccZ2 (2 to 4 m.s−2); AccZ3 (>4 m.s−2); DecZ1 (<−2 m.s−2); DecZ2 (−2 to −4 m.s−2); DecZ3 (>−4 m.s−2). The results revealed significant differences between wins and draws for the duration of the match and draws compared to wins for the first- half duration (p ≤ 0.05; ES = 0.36 [−0.43,1.12]), (p ≤ 0.05; ES = −7.0 [−8.78, −4.78], respectively. There were significant differences on AccZ1 during the first-half between draws and defeats (p ≤ 0.05; ES = −0.43 [−1.32,0.46]), for AccZ3 in the second-half between draws and defeats (p ≤ 0.05; ES = 1.37 [0.48,2.25]). In addition, there were significant differences between wins and draws (p ≤ 0.05; ES = 0.22 [−0.62,1.10]), and wins and defeats for MPA in the first- half (p ≤ 0.05; ES = 0.34 [−0.65,1.22]). MPA showed further differences between draws and defeats in the second- half (p ≤ 0.05; ES = 0.57 [−0.22,1.35]). Descriptive analysis revealed differences between the first and second half for wins in AccZ2 (p = 0.005), DecZ2 (p = 0.029), and MPA (p = 0.048). In addition, draws showed significant differences between the first and second half in duration, AccZ1, AccZ2, and DecZ2 (p = 0.008), (p = 0.017), (p = 0.040), and (p = 0.037) respectively. Defeats showed differences between the first and second half in AccZ1, AccZ3, and MPA (p = 0.001), (p = 0.018), and (p = 0.003) respectively. In summary, the study reveals large variations between the match duration, accelerometer variables, and MPA both within and between matches. Regardless of the match outcome, the first half seems to produce greater outputs. The results should be considered when performing a half-time re-warm-up, as this may be an additional factor influencing the drop in the intensity markers in the second half in conjunction with factors such as fatigue, pacing strategies, and other contextual variables that may influence the results.

Are acute:chronic workload ratios of perceived exertion and running based variables sensible to detect variations between player positions over the season? A soccer team study

“…Another limitation is the lack of potentially important time-motion characteristics such as decelerations and accelerations covered during training and match play across the different periods of the season. Finally, there were some possible contextual factors, such as the match result [ 23 , 44 , 45 ] and location [ 24 , 45 ] that could influence the results and should be considered for future studies. The final limitation of this study was the lack of internal and external load monitoring in resistance training and competitions sessions which should be considered in future studies.…”

Comparison of Measurements of External Load between Professional Soccer Players

“…The unscaled BL (USBL) was then calculated using the formula USBLC = NV + (NV3) [ 19 ]. Next, the accelerometer recording speed (100 Hz) and load factor (EF) (SBLC = USBLC/100/EF) were used to calculate the scaled BL (SBLC) [ 34 ]. Finally, the final BL (BL = BL + SBLC) was determined.…”

Wearable Inertial Measurement Unit to Measure External Load: A Full-Season Study in Professional Soccer Players

“…The following stages were performed in the BL calculation for each acceleration level: initialize the BL count to 0; calculate the magnitude of the acceleration vector (V) for the current acceleration (V = ax2 + ay2 + az2); and normalize the magnitude vector (NV) by subtracting a national 1 G (NV = V − 1.0 G). Following that, the unscaled BL (USBL) was calculated using the formula USBLC = NV + [NV3] [51]; after that, the scaled BL (SBLC) was computed using the accelerometer logging rate (100 HZ) and exercise factor (EF) (SBLC = USBLC/100/EF); finally, the final BL (BL = BL + SBLC) was determined [52]. BL had replaced the original GPSports.…”