For my master’s thesis at Oregon State University, sponsored by adidas, I developed a predictive model for outsole traction under conditions critical to basketball performance. The model successfully accounted for 87% of the variance in the coefficient of friction based on fundamental material properties, providing a valuable tool for selecting and tuning materials for high-performance footwear.

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The research began by analyzing the athlete's needs to define the pressures and relative velocities where traction is most critical. Using these parameters, I measured the coefficient of dynamic friction for a diverse matrix of outsole materials, each with varying ingredients, processing methods, and functional properties.

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To uncover the fundamental drivers of traction, I conducted extensive material testing, including:

• Dynamic Mechanical Analysis (DMA): To evaluate viscoelastic stiffness across a range of strain rates.

• Surface Roughness Profilometer: To measure surface geometry of both new and worn samples.

• Sessile Drop Test: To assess free surface energy.

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Through linear regression analysis, I identified three key material properties that best predicted dynamic friction. The resulting model enables informed material selection and optimization, contributing directly to the design of high-performance basketball outsoles. This project combined athlete-driven insights, rigorous experimentation, and advanced statistical modeling to achieve a practical and impactful result.