Audet Jonathan, Benghanem Abdelghani, Lussier-Desbiens Alexis
Createk Design Lab, Université de Sherbrooke, 3000 bd de l'Université, Sherbrooke, QC J1K 2R1 Canada.
Sooth Ski, 1234 William St, Quebec City, QC G1S 4E9 Canada.
Sports Eng. 2025;28(2):35. doi: 10.1007/s12283-025-00511-w. Epub 2025 Aug 4.
Evaluating alpine skis on snow is pivotal for ski development and consumer decision-making, yet it is resource-intensive and hindered by subjective assessments. Leveraging recent extensive ski physical measurements and on-snow ski evaluation metrics, this study proposes an automated methodology that employs elastic net regression, bootstrap resampling, and intelligent feature selection to predict the on-snow performance using a minimal set of physical attributes. Results on 192 skis divided into 10 categories and 29 metrics indicate promising predictive capabilities, with models exhibiting an average Mean Absolute Error rank prediction of 15%. Importantly, the models utilize less than three physical attributes on average, underscoring their simplicity and effectiveness in identifying key performance-defining properties. These findings, to the authors' knowledge, represent the most comprehensive description of ski on-snow performance to date and hold implications for ski design and consumer guidance. Moreover, the automated methodology enables the easy integration of other evaluation sources, facilitating further refinement and validation, while promising to consider the diversity of opinions related to ski on-snow performance assessment.
The online version contains supplementary material available at 10.1007/s12283-025-00511-w.
在雪上评估高山滑雪板对于滑雪板的开发和消费者决策至关重要，但这需要大量资源，并且受到主观评估的阻碍。利用最近广泛的滑雪板物理测量数据和雪上滑雪评估指标，本研究提出了一种自动化方法，该方法采用弹性网络回归、自助重采样和智能特征选择，以使用最少的一组物理属性来预测雪上性能。对分为10类和29个指标的192块滑雪板的测试结果表明，该方法具有良好的预测能力，模型的平均平均绝对误差排名预测为15%。重要的是，这些模型平均使用不到三个物理属性，突出了它们在识别关键性能定义属性方面的简单性和有效性。据作者所知，这些发现代表了迄今为止对滑雪板雪上性能最全面的描述，对滑雪板设计和消费者指导具有启示意义。此外，这种自动化方法能够轻松整合其他评估来源，便于进一步完善和验证，同时有望考虑与滑雪板雪上性能评估相关的各种意见。
在线版本包含可在10.1007/s12283-025-00511-w获取的补充材料。
