“Seasonal changes and variability of physical match demands in a highly trained female soccer team”

Author: João Barreira et al
Journal: Biology of Sport (2025)

AI written summary

This study investigated how physical match demands vary across matches, seasons, positions, and individual players in a highly trained professional women’s soccer team competing in the Italian Serie A over two seasons (2021–22 and 2022–23). Using 344 full-match GPS observations from 27 players, the researchers quantified seasonal trends, sources of variability, and minimum detectable changes (MDC) for common GPS metrics.


Key Aims
  1. Describe match external loads across two seasons.
  2. Quantify how much match physical performance varies (between matches, players, positions, seasons, and within players).
  3. Establish thresholds for meaningful individual changes across matches.

Main Findings
1. Overall Match Demands

Typical match values (averaged across both seasons):

  • Total Distance: ~9,290 m
  • m/min: ~103
  • High-Speed Running (HSRD): ~289–309 m
  • High Metabolic Load Distance (HMLD): ~1,982 m
  • Max Speed: ~26.3 km/h
  • Acceleration & Deceleration Distances: Highly variable

These values align with elite-level women’s football benchmarks (e.g., FIFA Women’s World Cup)


2. Between-Season Difference

Only HSRD increased significantly in Season 2 (+36.9 m; large effect) — suggesting more distance performed at >19.8 km/h despite similar total distances. Other metrics showed no meaningful differences between seasons


3. Variability of Match Demands

The study decomposed variability into:

  • Between-match
  • Between-player
  • Between-position
  • Between-season
  • Within-player
High-intensity metrics = most variable
  • HSRD CV: 11.6%–33.7%
  • Accelerations & Decelerations CV: 22%–30%
  • HMLD CV: up to 12.2%
Lower-intensity metrics = very stable
  • Total Distance CV: ~4–5%
  • m/min CV: ~4–5%
  • Max Speed: only 3–5% variability

This confirms that high-intensity outputs fluctuate heavily due to tactical and contextual match factors, while global running load is more stable. Coaches should avoid overinterpreting single-match HSRD changes


4. Minimum Detectable Changes (MDC)

Based on match-to-match variability and smallest worthwhile change, the study established thresholds for meaningful individual changes:

Stable (low-intensity) metrics → meaningful change ≈ ±12–15%
  • Total Distance
  • m/min
  • Max Speed
Highly variable metrics → meaningful change extremely high
  • HSRD: +83% to +104%
  • Accelerations: +84% to +106%
  • Decelerations: +65% to +82%
  • HMLD: +32% to +40%

In practice, a normal week-to-week fluctuation in HSRD could be ±30–40%, so a “big drop” or “big spike” is not automatically meaningful


5. Seasonal Trends

Figures on page 5 show mostly flat seasonal trends across both seasons:

  • No clear increase/decrease in most metrics over time.
  • Exception: Season 2 showed increasing max speed and increasing deceleration distance across weeks (possibly linked to tactical evolution or player roster changes)

Practical Implications for Practitioners
1. Use stable metrics (TD, m/min, max speed) to monitor changes.

These metrics are reliable indicators of within-player deviation across matches.

2. Be cautious with high-intensity data.

HSRD and acceleration/deceleration distances are too variable to interpret without context (scoreline, opposition, playing style, player role, fatigue) BS_Art_57114-10.

3. Contextual factors must be integrated.

Opposition level, team tactics, match status, and ball possession heavily influence high-intensity actions.

4. Training prescription should remain varied.

Because match demands fluctuate widely, simply targeting match loads (e.g., replicating 600 m HSRD) is insufficient.


Conclusion

Seasonal changes in physical performance in this professional women’s football team were minimal. Low-intensity metrics were stable, while high-intensity metrics showed very high variability, requiring large changes before they become meaningful. Coaches and performance staff should interpret high-intensity outputs cautiously and rely on broader context when making training or recovery decisions.

Niels de Vries
Niels de Vries
Articles: 174