Distinguishing Important from Interesting: Informing Tactical, Physical, and Recovery Periodization with Load and Technical Performance Data

Abstract

In the modern era of soccer, the abundance of data available from sport science profiling, monitoring, and analytics can be overwhelming. However, it is the ability to contextualize and relate these data back to a game model and the needs of individual players and teams that truly leads to enhanced performance and development. This session will present a practical example of how data describing physical demands and technical performance can be used to distinguish important versus interesting and subsequently support what it takes to win and develop the team and individual players. This session addresses the contemporary challenge of data overload and “shiny object syndrome.” By focusing on the practical application and potential implications of data in the context of a game model or individual needs, analysis can bridge the gap between the raw data and actionable insights. This session will demonstrate the use of publicly available in-game technical performance data to inform potentially relevant training activities while an R Shiny tool with linear mixed models can be used estimate the subsequent physical demands of those training activities and overall sessions. Furthermore, the session will give a high-level overview of how physical performance data, both internal and external load and subjective feedback, can be used to inform individual recovery prescriptions based on the most up-to-date recovery science literature. The session will also highlight the importance of appropriately delivering this information to key stakeholders, coaches, practitioners, and athletes. The talk will emphasize being sensitive to how different individuals want to receive information and what from a given analysis they are interested in. This session is grounded in and builds upon existing research and practices in sport, recovery, and data science. However, the session is unique in that it will present tangible practical applications that can integrate data analysis and research findings into everyday practice to improve health and performance. While the session is not a deep dive tutorial on how to analyze a particular dataset, it will offer valuable insights and practical methodologies for leveraging data to support winning and player development whether the attendee is a coach, analyst, or sport scientist.

Emaly Vatne

Assistant Sport Scientist at The Ohio State University Department of Athletics and Human Performance Collaborative

My research interests include applied sport science, effects of recovery interventions, and data analysis, visualization, and engineering.