So, I've always thought you should adjust the input into a model for results that are affected by things such as weather, freak occurrences, injuries, etc. The problem is, I don't really know how much you should adjust.
Some ideas I have:
1. Adjust the final score for each team up to the league average
2. Adjust the final score for each team up to the average of both teams
3. In football, add a touchdown to each teams score
Of course, there's no guarantee the game would've reached the league average had conditions been good. Low scoring games can obviously occur when conditions are perfect. One compromise might be to adjust the score to 80% of league average or something along those lines.
Also FWIW, I got this idea from an article on Tony Bloom who runs "Starlizard". Apparently they adjust soccer results for things like missed penalties, shots that hit the crossbar, etc. For example: if the score was 0-0 but one team missed a penalty they might put the result in as 0.8-0 to the team that missed.
Any thoughts?
Cheers
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Some ideas I have:
1. Adjust the final score for each team up to the league average
2. Adjust the final score for each team up to the average of both teams
3. In football, add a touchdown to each teams score
Of course, there's no guarantee the game would've reached the league average had conditions been good. Low scoring games can obviously occur when conditions are perfect. One compromise might be to adjust the score to 80% of league average or something along those lines.
Also FWIW, I got this idea from an article on Tony Bloom who runs "Starlizard". Apparently they adjust soccer results for things like missed penalties, shots that hit the crossbar, etc. For example: if the score was 0-0 but one team missed a penalty they might put the result in as 0.8-0 to the team that missed.
Any thoughts?
Cheers

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