Mental fatigue is defined as a psychobiological state resulting from prolonged and intense cognitive demands (Boksem and Tops, 2008). It is characterised by subjective sensations of “fatigue” and “lack of energy” (Rozand and Lepers, 2017). This condition is prevalent in team sports that require significant cognitive engagement and operate within unpredictable environments (Yuan et al., 2023). Research indicates that mental fatigue adversely affects both physical and tactical performance in soccer players (Coutinho et al., 2017). The cognitive challenges inherent in team sports such as soccer are particularly formidable (Faubert and Sidebottom, 2012). For example, during matches, the movements of both teammates and opponents are unpredictable, and the trajectory of the ball cannot be anticipated; distractions may necessitate changes in direction, while the movements of others can obstruct the path of the incoming ball (Smith et al., 2018). These overwhelming streams of information hinder decision-making capabilities and ultimately impact athletic performance (Skala and Zemková, 2022). Consequently, athletes must sustain a high level of cognitive flexibility throughout the duration of the match (Sun et al., 2021).

The essence of football resides in the intense confrontations and counterattacks between opposing teams and their players, as both sides endeavour to outmanoeuvre one another. Beyond the physical demands inherent to the sport, players consistently encounter the challenge of being marked by opponents. In such high-pressure scenarios, they must make decisions that benefit their team (Trecroci et al., 2020). Given the multifaceted performance requirements in modern football, cognition may be the pivotal factor in achieving and sustaining peak performance (Knöbel and Lautenbach, 2023). With the evolution of modern football, advanced tactical concepts such as high pressing and structured defence have emerged, imposing extreme demands on players’ physical endurance (Sally, 2014). Consequently, the time and space available to players on the field have significantly diminished (Vestberg et al., 2020). In this context, executive functions—namely inhibition, cognitive flexibility, and working memory—are regarded as essential for effective and goal-oriented behaviour (Diamond, 2013).

Recent studies have highlighted an increasing interest in the relationship between mental fatigue and football performance, particularly its effects on physical conditioning (Smith et al., 2015; Coutinho et al., 2018; Filipas et al., 2020), technical skills (Smith et al., 2016), tactical execution (Kunrath et al., 2020), cognitive functions (Hans-Erik and Daniel, 2019), and training methodologies (Bian et al., 2022). For example, mental fatigue significantly influences players’ offensive and defensive techniques, notably diminishing both the frequency and success rate of tackles (Sun et al., 2022). Another investigation revealed that, although mental fatigue does not compromise athletes’ maximal strength, explosive power, or anaerobic capacity (Van Cutsem et al., 2017), its interaction with motivation during endurance training can affect performance (Dantzer et al., 2014). Moreover, mental fatigue exacerbates the sensation of “I cannot do it” by activating inhibitory neural systems in the brain. Cognitive research concerning football players has largely concentrated on developing assessment tools (Kane et al., 2007) and analysing athletes’ inhibitory contro (Soylu et al., 2022), decision-making abilities (Fortes et al., 2020), working memory (Zhou, 2021), and visual skills (Knöllner et al., 2022). However, further investigation is warranted to understand how mental fatigue impacts cognitive flexibility. Cognitive flexibility refers to the ability to consciously adjust cognitive strategies in response to environmental changes, enabling individuals to adapt to new situations and solve novel problems. Essentially, it involves switching between different cognitive rules, reflecting an individual’s capacity for mental transformation and inhibitory control (Zühlsdorff et al., 2023).

The Wisconsin Card Sorting Test (WCST) and the task-switching paradigm are currently prevalent methods for assessing cognitive flexibility (Schmitter-Edgecombe and Langill, 2006; Nyhus and Barceló, 2009). Nevertheless, these approaches predominantly concentrate on behavioural data from athletes, with limited investigation into the underlying neural mechanisms. Prior research has demonstrated a correlation between working memory, cognitive flexibility, and goal-scoring performance throughout a player’s season. This relationship remains significant even when controlling for intelligence, height, and age in partial correlation analyses (Wallace and Norton, 2014). Studies suggest that high executive function can serve as a predictor of football success among young players. While earlier investigations have explored the influence of cognitive functions in elite versus novice athletes and across various age groups through EEG mapping, no research has yet validated the mechanisms by which mental fatigue impacts cognitive flexibility in football players, particularly from the perspective of the More-odd shifting task (Dong et al., 2022). EEG spectral measurements offer a comprehensive overview of rhythmic brain activity, whereas event-related potentials (ERP) are temporally confined to specific events or stimuli, enabling a more precise examination of the neural processes that underpin cognitive functions (Sokhadze et al., 2017).

Classical event-related potential (ERP) components encompass P1, N1, P2, N2, and P3. The early ERP components, namely P1, N1, and P2, are regarded as exogenous factors predominantly influenced by the physical properties of stimuli (Luck and Kappenman, 2012). In contrast, the later-emerging components, such as N2 and P3, are considered endogenous factors closely linked to individual cognitive processes, including attention, decision-making, and memory updating (Folstein and Van Petten, 2008). The N2 component, which appears prior to P3, is characterised by a negative wave occurring approximately 200 milliseconds after stimulus onset, reflecting the brain’s initial processing of stimuli (Fan et al., 2023). Research suggests that goal-directed behaviour relies on control mechanisms associated with the prefrontal cortex, and task-switching processes can be employed to investigate cognitive flexibility mechanisms (Rozand and Lepers, 2017). In the context of EEG methodologies, switching mechanisms are represented by the N2 and P3 ERP components; during task switching, the N2 ERP component indicates mechanisms involved in resolving conflicts between simultaneously active stimulus–response mappings (Gehring et al., 2003). Other studies have reported increased N2 amplitudes following prolonged tasks (Boksem et al., 2005; Möckel et al., 2015). Additionally, research focusing on elderly individuals and patients has demonstrated that heightened N2 amplitudes signify increased energy costs associated with cognitive control, suggesting that patients utilise more resources in response selection (Pinal et al., 2015).

Building upon existing ERP literature concerning cognitive control and task switching (Trecroci et al., 2020), this study selected four electrode sites—Fz, Cz, Pz, and F3—for analysis. Firstly, Fz and Cz are situated in the precentral scalp region, representing the most prominent areas for conflict-related N2 components, which effectively reflect conflict monitoring activity in the anterior cingulate cortex (ACC) (Folstein and Van Petten, 2008). Secondly, the F3 site is located above the dorsal anterior frontal lobe (DLPFC), a region closely linked to task set reconfiguration and executive control, thereby facilitating a deeper exploration of the specific neural mechanisms underlying cognitive flexibility (Thönes et al., 2018). Finally, the Pz site records activity from the parietal cortex, serving dual purposes: confirming the anterior distribution characteristics of N2 components and preparing for subsequent stimulus evaluation analysis (Kieffaber and Hetrick, 2005). In this study, we not only focused on the N2 components associated with conflict monitoring recorded by midline electrodes (Fz, Cz, Pz), but also specifically established the F3 electrode in the left prefrontal cortex. The F3 electrode, located at the standard position of the international 10–20 system, is widely recognised for its ability to effectively reflect the neural activity of the underlying left dorsolateral prefrontal cortex (Ota et al., 2019).

Mental fatigue, as a critical factor influencing cognitive flexibility, necessitates a thorough examination of its relationship with cognitive performance. Comprehending this connection is vital for devising targeted interventions aimed at enhancing athletes’ capacity to manage complex situations and improve their cognitive adaptability. Consequently, this study synthesises existing evidence regarding the impact of mental fatigue on cognitive flexibility in soccer players, while also investigating the neural mechanisms that underpin this relationship.

This study provides robust evidence that a 30-min Stroop task effectively induces mental fatigue in soccer players, as demonstrated by significant subjective reports, prolonged reaction times, and decreased accuracy. Notably, our neurophysiological data reveal that this behavioural impairment is underpinned by a specific neural mechanism: a marked reduction in N2 amplitude and an increased latency during the More-odd shifting task (Liu et al., 2025), particularly observable at the Cz electrode site. The synthesis of these behavioural and electrophysiological findings allows us to propose a coherent model: mental fatigue compromises athletic cognitive performance primarily by depleting the neural resources essential for early conflict monitoring and cognitive control (Norman and Bobrow, 1975), as indicated by the diminished N2 component, which directly leads to slower and less accurate responses.

A Coherent Neuro-Behavioural Model of Fatigue-Induced Impairment The observed decline in behavioural performance aligns with the well-established concept of finite attentional resources (Hancock and Desmond, 2001). Our study extends this principle by identifying a plausible neural correlate. The N2 component, generated in the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC), is a well-established neural marker of conflict detection and cognitive control (Folstein and Van Petten, 2008; Nieuwenhuis et al., 2003). The significant reduction in N2 amplitude following fatigue indicates a less efficient neural response in these key prefrontal regions (Petruo et al., 2018). This means that the soccer players’ brains became less adept at rapidly detecting and signalling the cognitive conflict inherent in the task-switching paradigm. This “neural inefficiency” at the early stage of information processing (~200–300 ms) forces subsequent cognitive processes to operate on a degraded signal, ultimately manifesting as the delayed reaction times and increased errors we recorded. Therefore, the N2 attenuation is not merely an parallel observation; it is the mechanistic link that explains why behaviour deteriorates under fatigue—the core computational machinery for cognitive control is compromised (Sarter et al., 2006).

A critical analysis of the existing literature and the theoretical implications of our study reveal a significant discovery. We found a consistent reduction in N2 amplitude during both switch and non-switch trials, suggesting that mental fatigue impacts a broad cognitive control mechanism rather than just the switching process. This observation provides empirical backing for the Limited Cognitive Control Theory (Hockey, 2013; Baumeister et al., 1998), which posits that prolonged cognitive exertion depletes a central pool of cognitive resources (Ishii et al., 2014).

When placed in the wider context of existing literature, our findings demonstrate both similarities and differences that enrich the field. The discovery of compromised cognitive adaptability under fatigue corresponds with various studies in sports (Smith et al., 2018; Sokhadze et al., 2017). Nonetheless, the particular decrease in N2 amplitude we have identified offers a more intricate viewpoint. Previous research has indicated an increase in N2 among non-athletes or in different fatigue scenarios, suggesting heightened neural exertion (Lorist et al., 2005). In contrast, our distinct reduction in N2 may be elucidated by participant characteristics and task specificity. Elite footballers, accustomed to streamlined and automatic cognitive processes, may operate near their neural capacity thresholds. Consequently, when fatigue diminishes their resources, their capacity for neural compensation may be rapidly depleted, resulting in a reduced neural reaction rather than the heightened effort seen in other groups. This highlights that the neural effects of fatigue are not uniform but are shaped by individual diversities and task requirements (Tran et al., 2020).

It is crucial to translate these findings into practical applications to bridge the theory-practise gap. Our research suggests that cognitive performance, a key factor in soccer success, is vulnerable to mental fatigue (Smith et al., 2016). Therefore, practitioners should consider the following strategies: Firstly, coaches should manage cognitive load during training sessions similar to physical load periodization. Sessions with high tactical and cognitive demands should be followed by sufficient recovery or lighter cognitive activities to prevent cumulative fatigue that could impede learning and decision-making (Schmit and Brisswalter, 2018). Secondly, athletes should avoid mentally fatiguing activities (prolonged studying, intense video gaming, stressful work) in the 24 to 48 h before a competition to maintain the sharp cognitive control needed during the game. Additionally, athletes could benefit from “cognitive reset” techniques such as brief breathing exercises or temporarily shifting focus during halftime or breaks to replenish cognitive resources and potentially improve performance in the second half (Nédélec et al., 2015). Lastly, training programmes should include specific exercises to enhance cognitive endurance and efficiency under fatigue, strengthening compromised neural systems (as indicated by the N2) (Nédélec et al., 2013; Van der Linden et al., 2003).

This study illustrates that experimentally induced mental fatigue has a significant detrimental impact on the cognitive performance of football players, leading to slower reaction times and decreased neural electrophysiological indicators (specifically, a reduction in N2 wave amplitude), indicating a decline in conflict monitoring ability. An integrated examination of both behavioural and neurophysiological data indicates that the adverse effects of mental fatigue are likely due to the depletion of general cognitive control resources that rely on the prefrontal cortex, rather than targeting particular cognitive functions. These results offer initial insights into the cognitive and neurological alterations in fatigued athletes. While the study did not explore interventions, the findings lay the groundwork for the development of tailored cognitive training programmes and fatigue management strategies, along with potential evaluation criteria. Notably, the N2 wave amplitude serves as a key metric for assessing cognitive resource levels in football players.