The answer is yes. But what was the question? Towards more useful theories in sport and exercise psychology

Debates about reform in sport and exercise psychology research largely center on the shortcomings of null hypothesis significance testing (NHST) and the binary conclusions it produces. We argue that significance testing is not the main culprit. NHST matches our theories, which typically use boxes and arrows to state that an effect exists and in which direction. So changing the statistical tool we use does not change much of what we learn, because it does not alter the questions we pursue or the specificity of the predictions we make: the answers we seek and settle for remain yes or no. The good news is that sport and exercise psychology is in a strong position to tackle more informative questions: We have established that many effects exist, collected a wealth of quantitatively rich data, and have sophisticated methods at hand. What is missing is a place in our theories to put these numbers. We outline three increasingly ambitious levers to transform this foundation into a more quantitative body of knowledge: (1) treating effect sizes and their precision as primary targets of study planning and inference, rather than as decorative statistics reported alongside the p-value; (2) synthesizing evidence cumulatively, so that established findings such as expected effect sizes constrain the next study; and (3) formulating theories themselves more quantitatively, for instance regarding the shape of a relationship or how quickly an effect unfolds, so that they make more precise predictions. Doing so benefits scientists and practitioners alike. Theories that make precise predictions can actually be wrong, which is what makes confirmations meaningful. A focus on cumulative effect size estimation also means that every well-conducted study teaches us something irrespective of its p-value, including the questions practitioners care about most: how much an intervention is likely to help, for whom, and when.