Talented athletes exhibit remarkable skills and performance in their respective sports, setting them apart from their peers. It has been observed that genetic polymorphisms can influence variations in sports performance, leading to numerous studies aimed at validating genetic markers for identifying sports talents. This study aims to evaluate the potential contribution of genetic factors associated with athletic performance predisposition in identifying sports talents. A systematic review was conducted following the PRISMA framework, utilizing the PICO methodology to develop the research question. The search was limited to case-control studies published between 2003 and June 2024, and databases such as Medline, LILACS, WPRIM, IBECS, CUMED, VETINDEX, Web of Science, Science Direct, Scopus and Scielo were utilized. The STREGA tool was employed to assess the quality of the selected studies. A total of 1,132 articles were initially identified, of which 119 studies were included in the review. Within these studies, 50 genes and 94 polymorphisms were identified, showing associations with sports talent characteristics such as endurance, strength, power, and speed. The most frequently mentioned genes were ACTN3 (27.0%) and ACE (11.3%). The ACE I/D and ACTN3 R577X polymorphisms are frequently discussed in the literature. Although athletic performance may be influenced by different genetic polymorphisms, limitations exist in associating them with athletic performance across certain genotypes and phenotypes. Future research is suggested to investigate the influence of polymorphisms in elite athletes from diverse backgrounds and sports disciplines.

Background: The influence of genetic polymorphisms on athletic performance has been widely explored. This study investigated the interactions between the polymorphisms ACTN3 (R577X), ACE (I/D), BDKRB2 (-9/+9), and AGT (M/T) and their association with endurance and strength phenotypes in Brazilian swimmers. Methods: 123 athletes (aged 20–30 years) and 718 controls participated in the study. The athletes were divided into elite and sub-elite (N = 19 and 104, respectively) and strength and endurance experts (N = 98 and 25, respectively). Hardy-Weinberg equilibrium was observed in all groups. Results: Considering the ACE polymorphism, it was observed a higher frequency of the DD genotype than expected in the strength experts of the elite group, whereas the strength experts sub-elite athletes had a higher frequency of the ID genotype (χ² = 8.17; p = 0.01). Subjects with XX genotypes of ACTN3 are more likely to belong to the athlete group when compared to the control group (OR = 1.79, p = 0.04). The DD homozygotes of the ACE are more likely to belong to the elite group with strength phenotypes than the group of sub-elite (OR = 7.96, p = 0.01) and elite strength experts compared to elite endurance (OR = 18.0, p = 0.03). However, no significant differences were observed in the allelic distribution of the polymorphisms evaluated when comparing Elite, sub-elite athletes and controls. Conclusion: ACE and ACTN3 allele frequencies should be considered with regard to performance influencing factors in Brazilian swimmers.

Context: Machine learning (ML) is a branch of artificial intelligence that centers on creating models derived from data, whereas artificial intelligence more broadly encompasses technologies that replicate human intelligence. The use of ML in sports science is transforming how athletes train, compete, and recover, leading to enhanced performance and a deeper understanding of the factors that contribute to success in sports. Objective: The aim of this study was to systematically identify original research that applied ML to sports performance. Design: A systematic review was conducted in January 2024 using PubMed, Web of Science, Science Direct, and Cochrane Library databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eligibility Criteria: Peer-reviewed articles addressing the use of ML models in the sports context were considered. Study Selection: Out of 510 initially identified studies, 36 were fully reviewed, and their outcome measures were extracted and analyzed. Main Outcome Measures: ML models used in sports performance were extracted. Results: The most commonly utilized ML models were random forest, Extreme Gradient Boosting, and logistic regression. The studies showed a significant concentration of research in Australia, with notable diversity in sports, such as soccer, swimming, and Australian football, suggesting that ML techniques can be adapted across various sports. Twenty-three studies reported on the accuracy of the ML models, which is crucial for their practical application; however, a relatively low number of studies (only 15) reported the training/test ratio. Omitting the training/test split reduces reproducibility and can lead to overfitting, thereby diminishing the reliability of a model’s reported performance. Conclusion: The advancement of technology and the resulting abundance of data has made ML a crucial strategy for assisting sports team staff in making decisions regarding performance by predicting dose–response relationships.

Team handball performance relies on physical and technical abilities, influenced by environmental and genetic factors. Variants in ACTN3 R577X (rs1815739), BDKRB2 −9/+9 (rs5810761), and AGT Met235Thr (rs699) genes are associated with athletic performance, but their relevance in handball remains unclear. Therefore, this study aimed to investigate the association of these polymorphisms with physical performance in Brazilian junior handball players. The study included 91 junior male handball players (16.4 ± 0.7 years) and 74 age-matched non-athletes. Genotypes for ACTN3 (R577X), BDKRB2 (−9/+9), and AGT (M235T) were identified using PCR-based techniques. Physical tests assessed upper limb strength (medicine ball throw) and lower limb strength (standing long jump). Genotypic and allelic frequencies were compared using Chi-square tests, while performance data were analyzed using ANOVA and t-tests (p ≤ 0.05). No significant differences were found in genotypic or allelic frequencies between athletes and controls for ACTN3 (R577X), BDKRB2 (−9/+9), and AGT (M235T) polymorphisms. Among athletes, ACTN3 RR carriers displayed significantly better upper limb strength (p = 0.049, d = 0.48). However, no genotype significantly influenced lower limb strength or anthropometric traits. Additionally, the study found no significant associations between BDKRB2 and AGT polymorphisms and physical performance parameters. This study demonstrates that specific genetic variants of the ACTN3 (R577X) gene may influence individual traits, such as upper-body strength, in Brazilian junior handball players. However, we found limited influence of BDKRB2 (−9/+9), and AGT (M235T) polymorphisms on overall performance. This lack of association may be attributed to the small sample size and the genetic heterogeneity of the studied population, encouraging further research with larger cohorts.

The ACTN3 gene encodes the protein alpha-actinin-3, which is crucial for fast-twitch muscle fibers, contributing to rapid and forceful contractions. The distribution of these genotypes and their impact on sports performance in Brazilian populations are not well-documented. This study aimed to determine the allelic and genotypic frequency of the ACTN3 R/X polymorphism in Brazil and its association with sports performance. A systematic review was conducted, including studies sourced from PubMed, Scielo, LILACS, LIPECS, Coleciona SUS, CUMED, BINACIS, IBECS, and MEDLINE databases, resulting in 42 studies included. The quality of these studies was assessed using the Strengthening the Reporting of Genetic Association (STREGA) guidelines. Among all the 8,746 participants, 35.2% had the RR genotype, 46.2% had the RX genotype, and 18.6% had the XX genotype. Regarding allelic frequency, 58.3% were R allele carriers, while 41.7% were X allele carriers. Meta-analysis showed that there was no consistent association between the ACTN3 genotypes and sports performance, although some data suggested potential benefits in athletic performance. This study revealed that the RX genotype of the ACTN3 R577X polymorphism is the most prevalent in Brazil, followed by the RR and XX genotypes. While the R allele was more frequent, the meta-analysis did not confirm a consistent association between ACTN3 genotypes and sports performance, suggesting that other genetic and environmental factors contribute to athletic success.