Una revisión sistemática de la literatura sobre predicción del rendimiento en natación: métodos, datos, técnicas y tendencias
DOI:
https://doi.org/10.47197/retos.v67.112197Palabras clave:
Predicción, Red Neuronal Artificial, Desempeño en Natación, Método, TendenciaResumen
Introducción: Predecir el éxito en la natación en deportes competitivos, principalmente los resultados de las futuras competiciones olímpicas de natación.
Objetivo: Este artículo ofrece una revisión exhaustiva y sistemática de la investigación sobre la predicción del rendimiento en natación publicada entre 2014 y 2024.
Metodología: La investigación sobre la predicción del rendimiento en natación se realizó mediante una Revisión Sistemática de la Literatura (SLR). Además, para establecer los límites de los artículos según el tema de investigación, este estudio utilizó las directrices PRISMA para realizar la revisión sistemática. El resultado de la extracción de estudios seleccionados fue la identificación y análisis de 21 publicaciones científicas que describen los temas de investigación, conjuntos de datos, técnicas, métodos, evaluaciones y problemas en este campo. Resultados: El análisis proporciona una explicación detallada de los temas y tendencias que centran los estudios en la predicción del rendimiento en natación, ofrece referencias a conjuntos de datos públicos y explica las técnicas y métodos empleados por los investigadores.
Discusión: El modelo matemático predictivo es una técnica popular, ya que integra variables biológicas y biomecánicas complejas, proporcionando predicciones precisas. Además, para mejorar tanto la precisión como la interpretabilidad de las predicciones, es necesario el uso de enfoques híbridos que combinen modelos matemáticos con técnicas más avanzadas, como el aprendizaje automático y la inteligencia artificial explicable (XAI).
Conclusiones: La predicción del rendimiento en natación es fundamental para mejorar los programas de entrenamiento, orientar la selección de atletas y evaluar su progreso.
Citas
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