Predicting game scores using sklearn
If I understand correctly, you're trying to predict the target variable 'Full_Time_Home_Goals' based on the four features ['HomeTeam', 'AwayTeam', 'Full_Time_Away_Goals', 'Full_Time_Result'] (the first two being being categorical and one-hot-encoded).
In your test set, you only receive (or only use) the first two, and fill the last two (which are, naturally, the more important ones) with a value of 1.
Now, let's imagine that your model decides that the teams aren't important, and makes the prediction based solely on the two latter variables... but in your test set, those all have the same value - so they'll get the same prediction.
The lesson here is that when you're training a model, do not use features that are (mostly or completely) missing from the test set.