In the new era of internet of things, big data collection and analysis based on widely distributed intelligent sensing technology is particularly important. Here, we report a flexible and durable wood-based triboelectric nanogenerator for self-powered sensing in athletic big data analytics. Based on a simple and effective strategy, natural wood can be converted into a high-performance triboelectric material with excellent mechanical properties, such as 7.5-fold enhancement in strength, superior flexibility, wear resistance and processability. The electrical output performance is also enhanced by more than 70% compared with natural wood. A self-powered falling point distribution statistical system and an edge ball judgement system are further developed to provide training guidance and real-time competition assistance for both athletes and referees. This work can not only expand the application area of the self-powered system to smart sport monitoring and assisting, but also promote the development of big data analytics in intelligent sports industry.

Combining traditional textiles with triboelectric nanogenerators (TENGs) gives birth to selfpowered electronic textiles (e-textiles). However, there are two bottlenecks in their widespread application, low power output and poor sensing capability. Herein, by means of the three-dimensional five-directional braided (3DB) structure, a TENG-based e-textile with the features of high flexibility, shape adaptability, structural integrity, cyclic washability, and superior mechanical stability, is designed for power and sensing. Due to the spatial framecolumn structure formed between the outer braided yarn and inner axial yarn, the 3DB-TENG is also endowed with high compression resilience, enhanced power output, improved pressure sensitivity, and vibrational energy harvesting ability, which can power miniature wearable electronics and respond to tiny weight variations. Furthermore, an intelligent shoe and an identity recognition carpet are demonstrated to verify its performance. This study hopes to provide a new design concept for high-performance textile-based TENGs and expand their application scope in human-machine interfacing.

In the new era of the Internet‐of‐Things, athletic big data collection and analysis based on widely distributed sensing networks are particularly important in the development of intelligent sports. Conventional sensors usually require an external power supply, with limitations such as limited lifetime and high maintenance cost. As a newly developed mechanical energy harvesting and self‐powered sensing technology, the triboelectric nanogenerator (TENG) shows great potential to overcome these limitations. Most importantly, TENGs can be fabricated using wood, paper, fibers, and polymers, which are the most frequently used materials for sports. Recent progress on the development of TENGs for the field of intelligent sports is summarized. First, the working mechanism of TENG and its association with athletic big data are introduced. Subsequently, the development of TENG‐based sports sensing systems, including smart sports facilities and wearable equipment is highlighted. At last, the remaining challenges and open opportunities are also discussed.