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Discrete time-series measurements collected at predefined timepoints are widely used in sport nutrition and exercise metabolism research, including tolerance tests, tracer studies, and physiological responses to experimental interventions. These data sets are commonly summarized using derived metrics such as area under the curve. The original Time Series Response Analyser, introduced in 2020 as a spreadsheet-based tool, aimed to standardize these calculations and reduced the risk of manual errors. However, spreadsheet implementations can be difficult to maintain, extend, and version control, and provide limited transparency regarding exactly how outputs are derived. Here, we present Time Series Response Analyser v2.0, a web-based successor designed to improve accessibility, usability, and long-term maintainability while preserving the analytical purpose of the original tool. The application runs in a standard web browser and guides users through a structured workflow consisting of data setup, file interpretation screening, interactive analysis, and export of results. It retains the core summary metrics of the original version while expanding visualization capabilities and export options. In summary, Time Series Response Analyser v2.0 is a free, open-source web-based application for researchers analyzing discrete time-series experiments across both repeated-measures and independent-groups designs, supporting transparent and reproducible analytical workflows while enabling future development through a code-based platform. Time-series data—measurements taken repeatedly over time—are widely used in sport nutrition and exercise science. For example, researchers may track blood glucose after carbohydrate ingestion, oxygen uptake during exercise, or metabolic responses to a meal. These data are often complex and are commonly simplified into summary measures such as the overall response over time or the peak value reached. This helps researchers to interpret results more clearly and compare different experimental conditions more easily. In 2020, we introduced the Time Series Response Analyser (TSRA), a spreadsheet-based tool designed to automate these calculations and reduce the risk of manual errors. Since then, the tool has been used by multiple research groups. However, spreadsheet-based tools can be difficult to maintain, update, and adapt over time, and may not clearly show exactly how results were generated. Here, we present the TSRA v2.0, a free, open-source web-based application that builds on the original tool. The new version runs directly in a web browser, meaning users do not need specialized software or specific system settings. This improves accessibility and ensures that the tool behaves consistently across different users and platforms. The TSRA v2.0 guides users through a structured workflow which is now more intuitive, from uploading data to checking their data, performing analyses, and exporting results. The application provides clear output files that document how results were calculated, improving transparency and reproducibility. Importantly, the TSRA v2.0 retains the core functionality of the original tool, including commonly used summary measures such as area under the curve, peak values, and time-to-peak. At the same time, the web-based design allows for ongoing updates, including additional features and bug fixes where necessary. Overall, the TSRA v2.0 is intended to support researchers working with time-series data by making analysis more efficient, transparent, and reproducible. By providing a free and openly-available tool, we aim to promote consistent analytical practices and improve confidence in reported findings across the field. [ABSTRACT FROM AUTHOR] |