6 papers
Counterfactual Optimization of Baseball Pitch Sequences and Estimation of Its Impact on Season-Level Statistics
Ryota Takamido, Hiroki Nakamoto
Although pitch sequencing is a central topic in baseball analytics, previous studies have primarily focused on optimizing the final pitch within a single plate appearance, leaving…
Cross-individual generalizability of machine learning models for ball speed prediction in baseball pitching
Ryota Takamido, Chiharu Suzuki, Hiroki Nakamoto
Although machine learning (ML)-based performance outcome prediction is an important topic in contemporary sports science, one important issue is the limited understanding of the cr…
Personalized Motion Guidance Framework for Athlete-Centric Coaching
Ryota Takamido, Chiharu Suzuki, Hiroki Nakamoto
A critical challenge in contemporary sports science lies in filling the gap between group-level insights derived from controlled hypothesis-driven experiments and the real-world ne…
Data-driven modelling of low-dimensional dynamical structures underlying complex full-body human movement
Ryota Takamido, Chiharu Suzuki, Hiroki Nakamoto
One of the central challenges in the study of human motor control and learning is the degrees-of-freedom problem. Although the dynamical systems approach (DSA) has provided valuabl…
Experience-based Optimal Motion Planning Algorithm for Solving Difficult Planning Problems Using a Limited Dataset
Ryota Takamido, Jun Ota
This study aims to address the key challenge of obtaining a high-quality solution path within a short calculation time by generalizing a limited dataset. In the informed experience…
PassAI: explainable artificial intelligence algorithm for soccer pass analysis using multimodal information resources
Ryota Takamido, Jun Ota, Hiroki Nakamoto
This study developed a new explainable artificial intelligence algorithm called PassAI, which classifies successful or failed passes in a soccer game and explains its rationale usi…