Sorry, I'm a Brit so that's soccer to most of you!
I'm interested in deriving a prediction equation for the number of goals scored in a match based on the two teams' average scoring and conceding rates.
Using the match results of the whole of last year's Premiership season I am going to find the average goals conceded and scored per match by each team simply by dividing total goals scored/conceded in the season by the number of matches.
Then I want to try and find a correlation which would tell me, say, if Team 1 (scoring rate S1/Conceding rate C1) plays Team 2 (Scoring rate S2/Conceding rate C2) what is the expected number of goals scored by each team?
Thus, if one were plotting it, you would obtain a 3-D plot with scoring rate and conceding rate on the x- and y- axes and number of goals scored on the z-axis.
But from here I'm stuck. How does one derive the best (maximum likelihood?) prediction equation? Will it even be linear? What if I plot the points and it's not a straight line? I can't believe I did Statistics at Uni and it's (nearly!) all gone.
I'm interested in deriving a prediction equation for the number of goals scored in a match based on the two teams' average scoring and conceding rates.
Using the match results of the whole of last year's Premiership season I am going to find the average goals conceded and scored per match by each team simply by dividing total goals scored/conceded in the season by the number of matches.
Then I want to try and find a correlation which would tell me, say, if Team 1 (scoring rate S1/Conceding rate C1) plays Team 2 (Scoring rate S2/Conceding rate C2) what is the expected number of goals scored by each team?
Thus, if one were plotting it, you would obtain a 3-D plot with scoring rate and conceding rate on the x- and y- axes and number of goals scored on the z-axis.
But from here I'm stuck. How does one derive the best (maximum likelihood?) prediction equation? Will it even be linear? What if I plot the points and it's not a straight line? I can't believe I did Statistics at Uni and it's (nearly!) all gone.