It is well established that qualitative methods offer an in-depth understanding of complex phenomena, allowing researchers to understand the "how" and "why" behind behaviors, decisions, and events (Eakin & Gladstone, 2020; Lim, 2025). This contribution makes them very useful in the field of sports performance analysis (SPA), because the performance of an athlete or a team is a multifactorial and complex issue (Mujika et al., 2018; Yang et al., 2024; Zentgraf et al., 2024). However, their value is often underestimated.

Recently, the Journal of Sport Sciences published an editorial by Memmert (2025) that offers a valuable and timely reflection on the current and future directions of SPA. I fully agree with the author's emphasis on several key areas: the integration of big data and machine learning, the need for solid theoretical foundations in research design, the adoption of experimental approaches to strengthen causal inference, and the critical importance of contextualization and open science practices. These points form a strong and coherent framework that can guide SPA research in the years to come. Particularly noteworthy is the author's call for benchmarking, transparency, and reproducibility, which resonates with the broader movement towards open science in sports and exercise research.

However, despite these significant contributions, the editorial presents a vision of SPA that is quantitative mainly and technology-driven. While quantitative metrics, advanced tracking systems, and machine learning models are essential, performance analysis is both quantitative and qualitative. This omission is particularly striking given Memmert's own recognition of the importance of contextualization, which is best achieved through qualitative approaches (Lames, 2023).

This opinion paper was initially written in the form of a "comment" on Memmert's editorial and submitted to the Journal of Sports Sciences. However, the reviewer to whom it was assigned recommended rejection of its publication, even though, as they wrote in their comments, "I deem the efforts made in this comment valuable in general." One argument against the comment was that, even if we accept that qualitative analysis dominates the practical domain, "this would not suffice as an argument for why qualitative analysis should be more prevalent in the scientific field."

The question that arises from this reviewer's remark is: why then is research conducted in the scientific field at all? Is it merely to produce publications, or is it to provide insights that can ultimately assist practice? Therefore, the purpose of this paper is to emphasize the contribution that qualitative methods can offer to SPA, to invite authors to conduct such studies, and to invite journals to evaluate them objectively based on their contribution to applied, on-field practice.

Accordingly, this opinion paper adopts the position that advancing sports performance analysis requires a more balanced epistemological framework, in which qualitative and quantitative approaches are treated as complementary rather than hierarchical. In this view, qualitative analysis plays a central role in contextualizing data, interpreting behavior, and ensuring that research outcomes remain meaningful for applied practice.

Quantitative metrics, advanced technologies, and machine learning models have undoubtedly transformed the field of SPA; however, their dominance risks overshadowing the essential contribution of qualitative approaches. Qualitative methods capture the complexity, context, and meaning of player and team behaviors, elements that numbers alone cannot explain. By incorporating video-based evaluation, case studies, and narrative reconstructions, researchers can bridge the science–practice gap and ensure that scientific inquiry remains relevant to real-world coaching and athlete development.

Ultimately, SPA should not be framed as a competition between quantitative and qualitative methods, but as a complementary integration. A more balanced paradigm, in which qualitative insights stand alongside quantitative data, will enhance the validity, contextualization, and applicability of research. This opinion paper, therefore, calls for greater recognition of qualitative analysis as a central pillar of SPA and invites scholars to contribute to this evolving conversation.

The author acknowledges the use of ChatGPT (OpenAI) solely for improving the clarity and quality of the English language.

The author hereby declares that this research is free from conflicts of interest with any party