Monitoring mood state to improve performance in soccer players: A brief review

Introduction

Psychological aspects of sport are key in maintaining athlete motivation and make a difference in competitive outcomes. Adjustments to training may be necessary according to athletes' emotional state. Therefore, it is important to assess and quantify mood states throughout the season in team sports, including among soccer players. The Profile of Mood States (POMS) is a widely used questionnaire that assesses emotional states characterized by positive or negative feelings and can be administered repeatedly to assess changes in mood state. This review aims to assess and summarize the current literature on mood state variation in soccer players with a specific focus on training loads, training modalities, and competitive performance.

Methods

A literature search was systematically conducted and resulted in 156 records. After removing duplicates, items with irrelevant titles and abstracts were screened out, and full texts were then screened for relevance and compared with inclusion and exclusion criteria. The remaining 37 articles were included in the final qualitative synthesis.

Results

POMS scores were related to variability in training load, intensity of the training period, modality of training exercises, competitive performance and time of day in soccer players. Common recommendations include monitoring the mood state of soccer players during training sessions, matches, and throughout training periods to detect early signs of psychological disturbance and aid in optimizing high-level training performance.

Conclusion

The POMS allows for monitoring of players' psychological state, providing coaches with data to aid in adjusting acute program variables according to players' psychological states and improve performance. Results offer practical support for the use of a simple POMS measurement as part of an overall program to monitor the players' psychological states. Results also highlight how training choices (i.e., load and exercise modality) and competitive performance are related to mood states (i.e., tension, anger, confusion, depression, fatigue, and vigor).

Psychological and Physiological Changes in Response to the Cumulative Demands of a Women's Division I Collegiate Soccer Season

ABSTRACT

McFadden, BA, Walker, AJ, Bozzini, BN, Hofacker, M, Russell, M, and Arent, SM. Psychological and physiological changes in response to the cumulative demands of a women's division I collegiate soccer season. J Strength Cond Res 36(5): 1373-1382, 2022-This study sought to determine the effects of a women's collegiate soccer season on psychological markers, biomarkers, sleep, and performance. Athletes participated in maximal countermovement vertical jump height (CMJ) assessments and biomarker monitoring in conjunction with subjective measures of psychological wellness and sleep questionnaires before preseason (S1) and every 4 weeks following (S2, S3, and S4). Training was monitored during practices and games using global positioning satellite systems and heart rate technology. Total training load was highest from S1 to S2, decreased from S2 to S3 (effect size [ES] = -2.5; p < 0.001), and remained stable from S3 to S4. CMJ declined at S2 (ES1-2 = -0.51; p = 0.001) and returned to baseline at S3. Increases from S1 to S2 were seen for creatine kinase (ES1-2 = 1.74), free testosterone (ES1-2 = 1.27), total testosterone (ES1-2 = 3.5), and free cortisol (ES1-2 = 0.88) (p < 0.03) before returning to baseline by S3 and S4 (free cortisol). Total cortisol was elevated throughout the season before declining at S4 (ES1-4 = -0.41; p = 0.03). Iron declined from S1 to S2 (ES1-2 = -0.73; p = 0.01) and returned to baseline values at S4, whereas growth hormone declined at S2 (ES1-2 = -0.50; p = 0.01) and remained depressed. Interleukin-6 increased at S4 (ES1-4 = 0.71; p = 0.02). Total training distress decreased from S1 to S2 (ES1-2 = -0.38; p = 0.02), returned to baseline by S3, and increased by S4 (ES1-4 = 0.57; p = 0.01). No changes were observed in markers of sleep (p > 0.05). Biomarkers showed notable changes after the highest workload period (S1-S2), which coincided with CMJ decrements. Biomarker perturbations preceded declines in subjective psychological wellness (S4) which occurred in the latter half of the season, indicating an accumulation of fatigue as the season progressed.