By computing your average speed over a distance, you basically sample the distance (delta S) and measure the time (t_i) each time you reach the defined sampling distance. The formula then to compute your average speed would be:

Then the problem starts. By decreasing your sampling distance as previously proposed to increase your "accuracy", you will reduce the time difference (t_i - t_(i-1) ). Let say you decrease your sampling distance towards zero, your time difference will tend towards 0 to... Which lead to a mathematical problem of 0/0, which is undetermined... It shows that the by decreasing the sampling distance, your average speed will increase, which is not correct.

The only correct average speed you can get from this formula is by choosing your sampling distance to the complete distance of your ride. You have then only one sample (n=1) and t_0 is your start time and t_1 your end time.

But if you want to "mathematically" increase your average speed, then you can apply this formula and chose a sampling distance which corresponds to your wish.

By computing your average speed over a distance, you basically sample the distance (delta S) and measure the time (t_i) each time you reach the defined sampling distance. The formula then to compute your average speed would be:

Then the problem starts. By decreasing your sampling distance as previously proposed to increase your "accuracy", you will reduce the time difference (t_i - t_(i-1) ). Let say you decrease your sampling distance towards zero, your time difference will tend towards 0 to... Which lead to a mathematical problem of 0/0, which is undetermined... The only correct average speed you can get from this formula is by choosing your sampling distance to the complete distance of your ride. You have then only one sample (n=1) and t_0 is your start time and t_1 your end time.

But if you want to "mathematically" increase your average speed, then you can apply this formula and chose a sampling distance which corresponds to your wish.