This study evaluated the effect of wind speed on 10 and 40 yard sprint times and stride frequency. Twenty-two men and women (Mean ± SD; age, 20.4 ± 1.4 years; body mass, 73.0 ± 12.5 kg) ran 6 sprints into variable speed headwinds, as assessed by wind vane and anemometer. Sprint data from the slowest and fasted wind conditions were kept for analysis. Ten and 40 yard sprint speed was assessed using an infrared timing system, and stride frequency was calculated from video analysis. Differences between 10 and 40 yard sprint times and stride frequency in slow and fast wind conditions were assessed using paired sample t-tests. Additionally, differences in scores were calculated for the slow and fast wind conditions for the 10 and 40 yard sprint times, as well as for wind speeds. Regression analysis was used to determine if a change in wind speed was a statistically significant predictor of changes in sprint times. Paired sample t-tests revealed that slow and fast mean wind conditions of 2.36 ± 1.06 and 6.73 ± 2.52 miles per hour (MPH), respectively, were significantly different (p ≤ 0.001). Mean 10 yard sprint times were 1.97 ± 0.17 seconds and 2.02 ± 0.16 seconds in the slow and fast wind conditions, respectively (p = 0.004). Mean 40 yard sprint times were 5.70 ± 0.52 seconds and 5.88 ± 0.64 seconds in the slow and fast wind conditions, respectively (p = 0.005). There was no significant difference in stride frequency between the slow and fast wind conditions of the 10 (p = 0.50) and 40 (p = 0.11) yard sprint. Results of regression analysis indicated that a change in wind speed is a significant predictor of a change in 40 yard sprint time (R2 = .22; p = 0.034) but not for the 10 yard sprint time (R2 = .05; p = 0.034). From these results, the following regression equation was created: Δ 40 yard sprint time = .054 (wind speed) - 0.055. Running into the wind decreases 10 and 40 yard sprint times, without affecting stride frequency. Changes in 40 yard sprint times can be predicted from wind speed. Running against the wind is an economical resisted speed development strategy. Coaches can use the regression equation from this study to determine the effect of forecasted or assessed wind speeds on resisted running performance, thus quantifying the nature of this training stimulus. Table 1 provides example data.