Assume that the expected number of goals scored by a team in a match is distributed in the following way: 0 goals: 10% 1 goal : 40% 2 goals: 30% 3 goals: 20%
Assume also that the probability of a goal is the same in any minute of the match. If there is still no goals scored at half time, what would be the distribution of expected goals at that time?
Typically, across the top European leagues over last few seasons, an average of about 43.5% of goals have been scored in the first half, varying maybe a % or two from country to country. So whatever goal rate you've used for the initial calc, multiplying it by 56.5% should give a decent measure of second half goal expectancy.
However your assumption of goal prob being the same in any minute gives the impression that you're considering half goals will occur in first half and half in second assuming same added time) - which would be wrong (but then again your goal distribution seems to be built on sand as well). I suspect i probably haven't answered your question, and that you haven't heard of Poisson.
Typically, across the top European leagues over last few seasons, an average of about 43.5% of goals have been scored in the first half, varying maybe a % or two from country to country. So whatever goal rate you've used for the initial calc, multipl
Not trying to be annoying but the question is contradictory, so can't be answered.
If we assume that the probability of a goal is the same in any minute of the match then each of these probabilities implies a different goal rate.
Goals
Prob
Implied Goal Rate/Min
0
0.1
0.0256
1
0.4
0.0102
2
0.3
0.0133
3
0.2
0.0179
so we're a bit farked
Not trying to be annoying but the question is contradictory, so can't be answered.If we assume that the probability of a goal is the same in any minute of the match then each of these probabilities implies a different goal rate. Goals Prob Implied
Ok, if we ignore "Assume also that the probability of a goal is the same in any minute of the match"
then we could assume that Distribution of goals in H1 is same as H2, but then we get problems because you've assumed 0% chance of > 3 goals....
So we have to change your distribution. The closest I can calculate is: Goals per team in match 0 13% 1 34% 2 32% 3 15% 4 5% 5 1% 6 0%
which makes: Goals per team in either half 0 36% 1 48% 2 12% 3 4%
Ok, if we ignore "Assume also that the probability of a goal is the same in any minute of the match"then we could assume that Distribution of goals in H1 is same as H2, but then we get problems because you've assumed 0% chance of > 3 goals....So we h
Thanks for your replies. Realized after posting that the question was flawed. I guess my assumption of same prob of goal each minute would lead to Poisson being the right tool, and that was just what I was trying to avoid, due to the mismatch of Poisson for 0-0, 0-1 and 1-0 scores.
Thanks for your replies. Realized after posting that the question was flawed. I guess my assumption of same prob of goal each minute would lead to Poisson being the right tool, and that was just what I was trying to avoid, due to the mismatch of Pois
You need to modify your Poisson for zero-inflation. http://www.bettingexpert.com/blog/how-to-calculate-probabilities-for-football-betting-using-poisson-part-2
off the top of my head and a quick calculation i make it
0 goals 40% 1 goal 40% 2 goals 15% 3 goals 5%
this isn't allowing for any more goals btw ,and don't forget more goals are scored second half in reality
off the top of my head and a quick calculation i make it 0 goals 40%1 goal 40%2 goals 15%3 goals 5%this isn't allowing for any more goals btw ,and don't forget more goals are scored second half in reality
during a game you don't really get much time to work on poisson distributions and games vary anyway - they're Football matches) not very good mathematical models
during a game you don't really get much time to work on poisson distributions and games vary anyway - they're Football matches) not very good mathematical models