Hello guys, Ive got an issue with a log. regression and I think its mostly a logical mistake, maybe you can help me out.
What I want to do:
1. Use a binary model, use different variables to predict 0 = Lose the game, 1= win the game.
2. Check the regression data the probit / logit and LS regression gives you.
3. Use them and get the probabilities for winning (=1) and losing (=0).
Here is my issue (and I think I got a lot more, unsolved yet as I don't know them actually).
I got the y=0 values and y=1 values in the regression.
Therefore I get probabilities for the winner and the loser of the match. Those summed probabilities are >1.
Any idea how to deal with this? The mistake has to be already in the first 3 steps. Usually I should be able to work with p and 1p.
But as 0 and 1 values have to be in the model, I cant just deal with winners probabilities, can I?
I will attach the results and my excelsheet in which I tried to sum it all up (not the complete sheet).
What I want to do:
1. Use a binary model, use different variables to predict 0 = Lose the game, 1= win the game.
2. Check the regression data the probit / logit and LS regression gives you.
3. Use them and get the probabilities for winning (=1) and losing (=0).
Here is my issue (and I think I got a lot more, unsolved yet as I don't know them actually).
I got the y=0 values and y=1 values in the regression.
Therefore I get probabilities for the winner and the loser of the match. Those summed probabilities are >1.
Any idea how to deal with this? The mistake has to be already in the first 3 steps. Usually I should be able to work with p and 1p.
But as 0 and 1 values have to be in the model, I cant just deal with winners probabilities, can I?
I will attach the results and my excelsheet in which I tried to sum it all up (not the complete sheet).
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