Researchers in the field of Sports Science describe performance analysis as a sub-discipline that uses ‘adaptative tools’ like human-machine instructiveness, visualization, evaluation, feedback, perspectives, generalization, and preparatory planning to study ‘variables’ and ‘fundamental indicators’ to build performance models and performance profiling. Such analysis is of critical importance to players, while coaches, performance analysts, technical staff, and managers use the data to draw insights and to manage performance in training and competition.
The key elements of Sports Performance analysis are:
Hence, performance analysis has the following benefits:
The primary use of sports performance analysis is to add Value to the sporting processes of players.
Value-adding qualities of Performance Analysis
Performance analysis adds value in:
The traditional approach to understanding and determining the performance in a given sport is static analysis, with a retrospective performance review. This was a very limited perspective that improved some of the fundamental factors of the performance of players. With the use of big data and artificial intelligence performance analysis has become dynamic and complex.
A very large body of research has established the scope of sports analytics and performance analysis. Sports analytics has helped in understanding complexity due to the non-linear nature of sports and multiple control factors used in understanding performance variability.
In performance analysis, the focus is on the measurement of technical indicators or ‘sport variables’ which influence performance are studied.
Spatiotemporal performance in hurdle athletes, race strategies, and longitudinal performance of gymnasts establishes the need for performance analysis.
The impact of environmental and psychological factors, like relative age, on track and field athletes, is reviewed, advanced analytics aid in improving postural skills, and anthropometric measurements to determine capabilities of players. The effect of the environment on performance due to factors like thermal conditions or extreme pressure conditions is reviewed.
A special study, Gomez-Ruano et.al., (2020) focused on gender in performance analysis
The sports analytics approach is scientific and hence uses
Using performance analysis, managers will be able to determine the strengths and weaknesses of athletes. Improve knowledge at technical and tactical levels to represent players at franchisees, or renew contracts.
Researchers Bateman and Jones show that the relationship between coach and performance analytics is very important. Coaches are able to determine the strengths and weaknesses of athletes and review performance in great depth
The psychological approach to performance analysis is based on multiple analysis factors in sports performance.
The language most preferred by sports scientists has been Python. The simple functionalities to solve complex issues in Python highlights the use of two libraries. Data visualization and analysis library is good for high levels of statistical plotting ensuring flexibility and simplicity. Sports performance analysis and data analytics is powerful and easy to use when using Python.
Performance analysts study the intra-behavior of athletes under different environments and task factors or ecological factors, tools study physiological and psychological, biomechanical, technical, tactical, positional as well as motor development, strength, and conditioning aspects of players during the training schedules and competition. These factors are evaluated using multiple techniques such as Logistic Regression, classification and Regression Tree, non-linear multidimensional scaling to understand at a deep level the performance of individuals or teams.
Advanced HD camcorder or a simple GoPro, camcorders, and videos collected from broadcasters for real-time data analysis become the input. Analysts use time-lapsed computerized video analysis software, notate key events and compare with database, create contextual information for individual action. Frequency of the data for manipulation, analysis software, data for tracking devices, generate an analysis for players, coaches.
This subfield of sports science continues to evolve, with new technology tools and databases being created using real-time recording and other data capturing and analysis technologies. Analysts find the market size for sports analytics expanding at 31.2% CAGR, and by 2025, expected to earn USD 4.6 billion in revenue. But the underpinning aspect of performance analysis remains data analytics. The capacity to identify and produce data for performance analysis is powered by changing technologies. Engaging professional data science and analytics experts will improve analysis and help in understanding competitive performance behavior.
As a coach or a player by reaching out to sports performance analysis, you will empower yourself and unlock targeted training, corrective techniques which will improve your game and let you win game after game!
