This study aimed to validate the use of a Global Positioning System with an accelerometer (GPS-Acc) unit to quantify canoeing kinematic variables. Eight canoe and kayak (200 and 500 m) sprint races were analysed. All the races were recorded sideways by a digital camera that followed the kayak or canoe bow and simultaneously using a GPS-Acc unit recorded the data concerning boat position, velocity, and acceleration. In 200 m races, 50 m splits were established over the entire race distance. In 500 m races, 100 m splits were used, excepting the race start and end, where the splits were divided into two sections of 50 m. The data of the GPS-Acc unit were analysed using a self-developed routine. The agreement between the video and the GPS-Acc analysis was measured regarding all the variables by a Bland-Altman analysis. No differences were found between both methodologies, except for time and velocity at the first 50 m, suggesting thus an agreement between the analysis methods. The GPS-Acc unit is valid for measuring quickly and accurately kinematic variables, mainly boat velocity and stroke rate. However, video analyses may be necessary when a more detailed analysis of the paddling technique is of interest.

Dynamic knee valgus is a biomechanical condition often linked to an increased risk of knee injuries, particularly in female athletes, due to greater hip adduction, internal rotation, and knee abduction during dynamic movements. This study aimed to assess the impact of neuromuscular fatigue on dynamic knee valgus in female basketball players during single-leg drop jumps (DJ-SL) and change of direction (COD) tests at 45° and 90°. Thirty-three athletes, divided into national and regional performance groups, performed these movements before and after a fatigue protocol. Fatigue was induced through a series of anaerobic exercises, and frontal plane projection angle (FPPA) was used to measure knee valgus. The results showed that dynamic knee valgus increased with the angle of directional change (from 24.77° ± 8.25 at 45° to 34.55° ± 10.40 at 95° pre-fatigue, and from 26.59° ± 12.30 at 45° to 35.87° ± 10.37 post-fatigue), but was not significantly affected by neuromuscular fatigue. The national group demonstrated lower valgus angles compared to the regional group, indicating potential performance differences based on competitive level. These findings suggest that while neuromuscular fatigue does not notably impact knee valgus, the higher valgus angles during directional changes warrant attention in injury prevention programs for female basketball players. Further research is needed to explore other factors influencing knee mechanics and injury risk.

Previous canoe sprint studies evaluated the best paddlers of their categories. This investigation aimed to identify the importance of biological maturation and athletes’ experience in kayaking performance and observe possible differences regarding anthropometry, years of practice, and performance. Eighty under 14 years of age (U14) and fifty under 16 years of age (U16) kayakers aged 13.40 ± 0.54 and 15.25 ± 0.61 years were evaluated. Kayakers were assessed for anthropometry (body mass (kg); stretch stature (cm); and sitting height (cm)), performance (time at 3000 m for U14 and 5000 m for U16 kayakers), and somatic maturation (predicted adult height (PAH) and maturity offset). In the U14 kayakers, years of practice, sitting height, and maturity offset showed significant differences (p < 0.05) between the Top10 and Middle, and Middle and Bottom10 performance times. Significantly higher (p < 0.05) sitting heights were identified between the Top10 and Middle U16 kayakers. Significant differences (p < 0.05) were observed for maturity offset and PAH% between the Top10 and Middle groups compared to the Bottom10 group. In conclusion, this research shows differences in the maturity status of young U14 and U16 kayakers, identifying that the more biologically mature individuals, with more years of specific practice, achieved better performances.

Like in other sports systems, in kayaking, young athletes are commonly grouped by their birth years. This study analyzed maturity status, relative age, and constituent age effects in young Under 14 (U14) and 16 (U16) Iberian male kayakers. One hundred and thirty (U14: n =80; U16: n = 50) young kayakers aged 14.10 ± 1.06 years were assessed for anthropometry, performance, maturity, and sport experience. The year was divided into four birth quarters (BQ). There were no significant differences in the kayaker’s distribution by BQ in both categories (U14, p = 0.348; U16, p = 0.709) or total sample (p = 0.783). Six of the ten best kayakers in the U14 category were born in the year’s first half, and eight were among the U16 kayakers. Talent detection and selection systems based solely on the young kayakers’ performances may imply some bias. One of the ways to get around this situation would be to adopt a grouping system similar to bio-banding, allowing the maximum number of practitioners to experience the possibility of obtaining competitive success.

This study aimed to produce predictive equations to determine the optimal paddle size for young Iberian kayakers competing in three categories: U14, U16, and U18. Data were collected in Portugal and Spain between 2005 and 2018, with a sample that includes 149 kayakers aged 14.42 ± 1.20 years. The kayakers were assessed for somatic maturation using the maturity offset and the percentage of the predicted adult height (%PAH). For anthropometry, assessing body mass (kg), stretch stature (cm), sitting height (cm), arm span (cm), arm length (cm), forearm length (cm), biacromial diameter (cm) and chest girth (cm), and for equipment setup, measuring paddle and blade length, blade maximum width, handgrip distance. A stepwise multiple linear regression analysis was performed to determine which anthropometric and maturity attributes could predict the paddle configuration for the total sample and each category analysed. Significant differences were found between the three categories for anthropometry, paddle setup, and maturity, except for PAH. Significant differences between U16 and U18 were only found in CA, maturity offset, %PAH, and paddle length. The predictive equation for the total sample explains the variance in paddle length by 75% and may be used as a more objective guide for paddle scaling.