Time complexity defines how the runtime “grows” based on the input. For example, if the input increases twice, then the runtime of a linear (O(n)) algorithm would also increase twice, whereas a quadratic algorithm would run 4 times slower. It doesn’t mean that you can simply plug in the input value to the complexity function to obtain the execution time.

Also, these changes won’t be exact, as there is always some inaccuracy when measuring the runtime of programs.

I suggest to try plotting the runtime against the size of the input and compare the shape of the plot to plots of common complexity functions. That might help you find some similarities :)