Abstract
This study represents one of the initial efforts to analyse a coach-athlete conversational dataset using freely available GPT tools and a pre-determined, context-specific, prompt-based analyses framework (i.e., R(2)-PIASS). One dialogue dataset was selected by means of two different freely available AI-based GPT tools: ChatGPT v4 and DeepSeek v3. The results illustrated that both ChatGPT v4 and DeepSeek v3 models could extract quantitative and qualitative conversational information from the source material using simple R(2)-PIASS prompt specifiers. Implications for how coaches can use this technology to support their own learning, practice designs, and performance analyses were the efficiencies both platforms provided in relation to cost, usability, accessibility and convenience. Despite the strengths, there were also associated risks and pitfalls when using this process such as the strength and robustness of the applicable statistical outcomes and tensions between keeping the input data within the context and ensuring that the context did not breach privacy issues. Further investigations that engage GPT platforms for coach-athlete dialogue analysis are therefore required to ascertain the true relevance and potential of using this type of technology to enhance coach learning and athlete development.