Red and blue can be understood as essentially overlapping, depending on the confidence levels given to the error bars of the red line. A stopwatch is going to be a pretty bad measurement technique if operated by hand, so I would expect your confidence level to be pretty low for any given measurement, meaning that it is plausible that the 'real' measurement could be at the extreme ends of the error bars rather than clustered closely to the measured data points. Another way to look at it -
Let's say in one instance you have a computer trigger the stopwatch as the car passes. In this instance, we would still have error bars on the measurement, but we would be fairly confident that the 'real' measurement would be very close to what was actually measured rather than out on the error bar. This is because generally computers are stable and we do not expect much variation in how they measure things even as we still leave open the possibility of uncertainties.
Now in another instance you have a person measure the car with a stopwatch. In this instance, we do not expect the person to be very precise or repeatable. In this case we would say that we have low confidence in the measurements such that we would not be surprised if the 'real' measurement was actually way out on your error bar rather than very close to the actual measurement.
There are more formal, precise ways to explain confidence but they're beyond my understanding.
For Doppler shift, it is again almost overlapping the predicting value except in the last measurement. In this case you could either claim there are unknown variables either in your prediction itself or in the Doppler shift measurement technique.
I'm just spitballing though and I could be entirely wrong.