What's a good way of generating football scores based on team strength?

About a year ago I tried to make a simple text-based football simulation program but I abandoned it and I want to start from the beginning since it wasn't really good. My problem is finding a good algorithm for calculating the scores.

I don't want this program to just be a big Math.random() mess, but instead, use a combination of Math.random() and team strength (each team was given attack and defense ratings of 1-20, but that could be improved too since I'm not sure if that's the optimal way of doing it) in order to calculate the scores, and maybe throw home advantage and form/morale into the mix (but that would be later since it's slightly more complicated).

In my previous program, the algorithm compared the attack and defense ratings of the 2 teams and then decided how many goals to randomize. So for example, if a team had a max of 20 attack rating and played against a team with 5 defence rating, they would most likely score a few goals. A few problems with this algorithm are:

1. I think will be really hard to incorporate home advantage and form using this algorithm. It was a lot of if's and else's with a random integer between 1 to 100 to have different chance percentages.
2. There were not a lot of surprise results, despite the fact that I gave smaller teams a chance to score a few goals.
3. The scores were insane, with teams winning 5-1 week in, week out.
4. It didn't technically check if a team is better overall, just decided the number of goals a team would score based on attack vs defense. So theoretically, attack could be overpowered (I might be wrong though).
5. Let's say a team who has to win the league and they are playing against a team who already secured a mid-table finish: that wouldn't have had an effect on the game. I suppose this is something to add next to form but I don't know.

Considering these points, do you have a good idea for a better algorithm? I don't know machine learning and all that stuff, I want this program to be somewhat simple. I also don't need you to write the whole algorithm for me of course, just give me some general ideas. Thanks a lot

My suggestion (just thinking out loud, I have no experience at all on football scores simulation).

I would assign every team a relative "goal potential", meaning like "how many goals would that team score on average" (against the whole population of teams). Then the simulation would be based on a normal distribution with the mean equal to the difference of goal potentials of the two players, and a some standard deviation.

To get an idea of appropriate values, you could take historical data of a few teams and compute their average number of goals (per match played), and the global standard deviation.

You could refine the model by assigning the teams different standard deviations, which will reflect their "regularity". Again you can compute these on actual data to get an idea of realistic values (and check if using different values makes any sense).

The home advantage can be modelled as just a fixed increment of the goal potential. You can also measure actual home advantage by computing the two average goal-per-match of a given team, both when home or visitor, and taking the difference (this is a way to see if home advantage is real or just folklore).