As others have pointed out, it is a good idea to encode domain knowledge in your time series model through specification and priors. Prophet rarely beats a well specified GLM or SARIMA in real world applications, especially when uncertainty estimates are needed. Professionally, I have succesfully applied Gaussian Processes to many such cases.

A GP is an intuitive and expressive way to code time covariance in a model. A famous example is the relative birthdays model, discussed by Gelman et al in Bayesian Data Analysis and here [1].

[1] https://avehtari.github.io/casestudies/Birthdays/birthdays.h...