Can investigate the long-term effects of competitive
Research gap analysis derived from 5 computer_science papers in our local library.
The gap
Further studies can investigate the long-term effects of competitive complexity exercises on football skills. Research can explore the application of these exercises to different age groups and skill levels. Studies can examine the combinat
Evidence profile
Sourced from the future-work section and conclusions and future work of the source papers, classified as general, spanning 5 journals.
Research trend
Established — well-defined area with open sub-problems.
Supporting evidence — 6 representative gaps
- Strategic evaluation and development pathways of PFC Levski Youth Academy: A SWOT analysis (2026) · Turkish Journal of Kinesiology · doi
Further research could explore the development of youth football academies in other contexts. The study suggests that future research could investigate the impact of scouting networks on talent identification. Further research could also examine the role of sports science technologies in enhancing player development.
generalfuture-work sectionKeywords: further research explore development youth football academies other - Pathways to the senior national teams: experiences of playing-up and mixed-gender play among Swedish elite female footballers (2026) · Frontiers in Sports and Active Living · doi
Further research is required to clarify the hypothetical reasoning discussed and to obtain better data to improve understanding of the long-term implications of current player development strategies. This study has addressed a specific gap in the literature and provide important insights about the impact of playing-up and mixed-gender play within football.
generalconclusionsevidence 5/5Keywords: further required clarify hypothetical reasoning discussed obtain better improve understanding long term implications current player - Editorial: Football training and competition (2026) · Frontiers in Psychology · doi
Collectively, the 31 articles comprising this Research Topic reflect the remarkable breadth and depth of contemporary football science (see Figure 1). The contributions span a wide range of designs, from randomized training interventions and longitudinal monitoring studies to systematic reviews, machine learning applications, and qualitative inquiry, and include populations ranging from grassroots youth players to elite professionals, male and female, across multiple football formats including football and futsal.
generalfuture workevidence 5/5Keywords: football collectively articles comprising topic remarkable breadth depth contemporary science contributions span wide range designs - Editorial: Football training and competition (2026) · Frontiers in Psychology · doi
Future studies should prioritize external validation, model interpretability, and open datasets. Researchers should explore the use of technology in football practice and science. The integration of technology, wearables, artificial intelligence, VAR, and non-invasive brain stimulation should be examined further.
generalfuture-work sectionevidence 5/5Keywords: future studies prioritize external validation model interpretability open - أثر تمرينات التعقيد التنافسي المبنية على مواقف اللعب في تطوير الاستجابة الحركية والتهديف والتصرف الخططي لدى لاعبي كرة القدم دون (19) سنة (2026) · مجلة علوم الرياضة الدولية · doi
Further studies can investigate the long-term effects of competitive complexity exercises on football skills. Research can explore the application of these exercises to different age groups and skill levels. Studies can examine the combination of competitive complexity exercises with other training methods.
generalfuture-work sectionevidence 5/5Keywords: further studies investigate long-term effects competitive complexity exercises - Predicting athletic performance in track and field athletes based on wearable physiological and psychological indicators: an interpretable machine learning study (2026) · Frontiers in Physiology · doi
Future research should consider a more comprehensive analysis of the limitations of the approach. Studies should examine the generalizability of the findings to other sports and populations. Research should investigate the use of other machine learning models and techniques for predicting athletic performance.
generalfuture-work sectionevidence 5/5Keywords: future research consider comprehensive analysis limitations approach studies
Questions about this gap
Explore this gap further
Run this gap as a query across open scholarly engines for the latest related literature.
Working on this gap? Review it with us.
Science AI Journal reviews manuscripts in one pass with 8 specialised AI agents calibrated on 69,000+ real peer reviews.
Tools for your next paper
Related gaps in Computer Science
- Future studies can investigate the effects of trainingFuture studies can investigate the effects of training programs on sprint performance. Future studies can examine the relationship between s…
- The standard ΛCDM model has been successful in describingThe standard ΛCDM model has been successful in describing the large-scale structure of the universe, but recent measurements have shown pote…
- Adversarial attack methods for NIDS lack domain-specificAdversarial attack methods for NIDS lack domain-specific constraints that ensure realism in network traffic; most attacks are adapted from c…
- The study only examined the effect of chunking on workingThe study only examined the effect of chunking on working memory in a specific experimental setup. The sample size was limited to 23 partici…