PURPOSE: The purpose of the study was to examine the relationship between bat swing velocity and lower extremity strength and power in NCAA Division-I softball athletes. METHODS: Twenty-nine softball athletes (age = 19.8 ± 1.3 years, height = 167.9 ± 6.8 cm, mass = 76.4 ± 18.1 kg) participated in the study. Athletes were tested on unloaded and loaded (20kg) squat and countermovement jump peak force, peak power, and jump height performed on a force platform sampling at 1000Hz. During practice, athletes were tested on swing velocity using a timing gate system. Pearson-product moment zero-order correlations were calculated between bat swing velocity and lower extremity strength and power. Statistical significance was set at p≤0.05. RESULTS: Moderate to strong relationships were observed between swing velocity and peak force at all conditions: SJ 0kg (r= 0.51, p= 0.005), SJ 20kg (r= 0.50, p= 0.006), CMJ 0kg (r= 0.44, p= 0.016), CMJ 20kg (r= 0.43, p= 0.022). Additionally, relationships were observed between swing velocity and peak power at all conditions: SJ 0kg (r= 0.45, p= 0.015), SJ 20kg (r= 0.40, p= 0.031), CMJ 0kg (r= 0.53, p= 0.003), CMJ 20kg (r= 0.45, p= 0.015). No statistically significant relationships were observed between swing velocity and jump height. CONCLUSIONS: Swing velocity was related to lower extremity force and power variables. Considering the known effects of strength training on lower extremity strength and power production, these results provide background for inclusion of lower extremity strength training for the development of swing velocity in NCAA Division-I softball athletes.

The load-depended loss of vertical barbell velocity at the end of the acceleration phase limits the maximum weight that can be lifted. Thus, the purpose of this study was to analyze how increased barbell loads affect the vertical barbell velocity in the sub-phases of the acceleration phase during the snatch. It was hypothesized that the load-dependent velocity loss at the end of the acceleration phase is primarily associated with a velocity loss during the 1st pull. For this purpose, 14 male elite weightlifters lifted seven load-stages from 70–100% of their personal best in the snatch. The load–velocity relationship was calculated using linear regression analysis to determine the velocity loss at 1st pull, transition, and 2nd pull. A group mean data contrast analysis revealed the highest load-dependent velocity loss for the 1st pull (t = 1.85, p = 0.044, g = 0.49 [−0.05, 1.04]) which confirmed our study hypothesis. In contrast to the group mean data, the individual athlete showed a unique response to increased loads during the acceleration sub-phases of the snatch. With the proposed method, individualized training recommendations on exercise selection and loading schemes can be derived to specifically improve the sub-phases of the snatch acceleration phase. Furthermore, the results highlight the importance of single-subject assessment when working with elite athletes in Olympic weightlifting.

Driving with tyres not appropriate for the actual conditions can not only lead to accidents related to the tyres, but also cause detrimental effects on the environment via emission of rubber particles if the driving conditions are causing an unexpectedly high amount of tread wear. Estimating tyre performance in an online setting is therefore of interest, and the feasibility to estimate friction performance, velocity performance, and tread wear utilizing available information from the automotive grade sensors is investigated in this thesis. For the friction performance, a trend analysis is performed to investigate the correlation between tyre stiffness and friction potential. Given that there is a correlation, a model is derived based on the trend having a stiffness parameter as an input in order to predict the friction performance. Tendencies for a linear trend is shown, and a linear regression model is fitted to data and is evaluated by calculating a model fit and studying the residuals. Having a model fit of $80\%$, the precision of the expected values stemming from the proposed model is concluded to be fairly low, but still enough to roughly indicate the friction performance in winter conditions. A tread wear model that can estimate the amount of abrasive wear is also derived, and the proposed model only utilizes available information from the automotive grade sensors. Due to the model having a parameter that is assumed to be highly tyre specific, only a relative wear difference can be calculated. The model is evaluated in a simulation environment by its ability to indicate if a tyre is under the influence of a higher wear caused by a higher ambient temperature. The results indicates that the model is insufficient in an online setting and cannot accurately describe the phenomena of softer tyres having a larger amount of wear caused by a high ambient temperature compared to stiffer tyres. Lastly, a double lane change test (ISO 3888-2) is conducted to determine the critical velocity for cornering manoeuvres, which defines the velocity performance. The test was executed for six different sets of tyres, two of each type (winter, all-season, and summer). The approach to estimate the velocity performance in an online setting is analogue to that of the friction performance, and a trend analysis is performed to investigate the correlation between longitudinal tyre stiffness and the critical velocity. The results are rather unexpected and shows no substantial differences in velocity performance, even though the tyre-road grip felt distinctively worse for the softer tyres according to the driver. It is concluded that the bias stemming from the professional driver's skills might have distorted the results, and that another approach might need to be considered in order to estimate this performance.