Neurofeedback training (NFT) has emerged as a promising technique for enhancing sports performance by enabling individuals to self-regulate their neural activity. However, only 53% of the 13 included studies, which all published before 2021, in the latest meta-analyses of NFT and motor performance focused on motor performance outcome. Due to the rapid development of neurofeedback, 8 high-quality articles published in 2023 alone. Therefore, there is a need for a new meta-analysis to update the impact of NFT on sports performance. In this systematic review and meta-analysis, we have not only updated the knowledge of the effect of EEG neurofeedback in motor performance, but have also incorporated a standardized methodology, called CRED-nf checklist (Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies), for methodological evaluation of previous EEG neurofeedback studies. The study protocol was pre-registered, and the meta-analysis revealed a moderate positive effect of NFT on sports performance, with a standardized mean difference (SMD) of 0.71 (95% CI: 0.51-0.91, p < 0.001). Importantly, subgroup analyses showed that studies with higher methodological quality, as assessed by the checklist, had significantly larger effect sizes (SMD = 0.98) compared to lower-quality studies (SMD = 0.41). This finding highlights the importance of addressing key methodological gaps, such as reporting on participant strategies, data processing methods, and the relationship between regulation success and behavioral outcomes.

Self-efficacy (SE) is recognized as a main determinant of successful performance and may mediate the relationship between psychological performance enhancement techniques and sports performance. Identifying the cognitive–motor processes of superior performance can provide crucial information not only for accelerating the motor learning process but also for enhancing motor performance. The frontal midline theta power (Fmθ) reflects the level of top–down attention allocated to achieve a desired cognitive–motor behavior. Thus, this study investigated the effect of SE on the performance and Fmθ of golf players and explored the association between the objective measures of cortical dynamics and SE. Thirty-four skilled golfers were recruited (within-subject design) to perform 60 putts, and their electroencephalographic activity was recorded during the task. The SE score was measured using a visual analog scale ranging from 0 to 10 before each putt. Paired t test results revealed that trials with higher SE scores were associated with a higher putting success rate than trials with lower SE scores (53.3% vs 46.7%). Moreover, trials with higher SE scores were preceded by lower Fmθ than trials with lower SE scores (4.49 vs. 5.18). These findings suggested that higher SE was followed by less top–down attentional control, a characteristic of automatic processing, leading to better putting performance. Our findings support Bandura’s SE theory and elucidate the intermediate processes of SE by investigating the effect of the anticipation of outcomes on sports performance and attentional control before putting.