A prototype super shoe against three advanced running shoes: running economy in 15 trained runners (Journal of Sport and Health Science, 2026)
What we found
Fifteen trained runners, 11 men and 4 women, had their running economy measured in four advanced footwear technology shoes: a prototype PUMA Fast-R 3 (FR3) designed with a data-driven computational process, its traditionally developed predecessor the PUMA Fast-R 2 (FR2), the Nike Alphafly 3 and the Adidas Adios Pro Evo 1.
Running economy is the rate of metabolic energy consumption while running at a specified speed.
Running economy in the prototype FR3 was 3.15% (SD 1.24%) better than in the FR2, 3.62% (SD 1.25%) better than in the Nike Alphafly 3 and 3.54% (SD 1.16%) better than in the Adidas Adios Pro Evo 1, with p below 0.001 for all three comparisons.
Every one of the 15 runners had their best running economy in the FR3.
Step frequency was lower in the FR3 than in the Adidas shoe (p = 0.013), and contact time was longer in the FR3 than in the Nike and Adidas shoes (both p below 0.001); step parameters were similar between the FR3 and the FR2.
The authors conclude that shoes designed using computational design analysis of biomechanical data can improve running economy, and describe this as a promising frontier for performance running shoe design.
Who this applies to and what it does not show
The result comes from 15 trained runners in a laboratory running at one specified speed; the abstract does not state the speed, the runners' times, or the price of any shoe.
The FR3 is a prototype, not a shoe on sale, and one of the five authors is affiliated with PUMA SE, the maker of the prototype and of the FR2.
Running economy is not race time: the abstract reports no race performance and no conversion from a percentage better economy to seconds or minutes, so none is given here.
What we are unsure of
Whether the same differences hold at other speeds, for slower or older runners, or over a full race, and how the prototype compares with shoes the runners train in.
Source
Kuzmeski J, Bertschy M, Healey L, Barrons Z, Hoogkamer W. Data driven shoe design improves running economy beyond state-of-the-art Advanced Footwear Technology running shoes. J Sport Health Sci 2026;15:101133. doi:10.1016/j.jshs.2026.101133 (PubMed 41831565, PMC13262284). https://pubmed.ncbi.nlm.nih.gov/41831565/