I try to predict a score $S$ at the end of a time $Τ$ with measure taken from time $h_1$ to $h_f$ (~10 constant intervals) from different sources (always different but close behavior).
My goal is to try to predict $S$ at time $h_1$, $h_2$, ... , $h_f$.
My measure evolve during $h_1$ to $h_f$ but $S$ stay the same. I don't know if I can consider this dataset as time series because target doesn't change during time and measures are taken from different sources. Apply an ARIMA model could be a good idea ?