How to define the probability for never occurred event between players
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I would like to find a probability between opponents that have never played with each other.
I would like to explain what I mean in an example.
Player A won m times against Player B and never lost a match against Player B.
Player B won n times against Player C and never lost a match against Player C.
If Player A and Player C play a match, As a sense, we can easily say that Player A has big advantage against Player C even though they have never played a match before.
I would like to find a formula to define the probability for such events that we need to formalize such kind of probability events.
Firstly, I want to define limit possibilities
A won all matches against B. $P_{A/B}=1$
B won all matches against C. $P_{B/C}=1$
Let's define probability before a real match between A and C
the probability of winning A against C: $$P_{A/C}=1$$
A lost all matches against B . $P_{A/B}=0$
B lost all matches against C . $P_{B/C}=0$
Let's define the probability before a real match between A and C
The probability of winning A against C: $$P_{A/C}=0$$
Other limit possibilities:
A won all matches against B. $P_{A/B}=1$
B lost all matches against C. $P_{B/C}=0$
We can not say anything about a real match between A and C. We can consider their chances are same as limit definition for this condition.
$$P_{A/C}=1/2$$
A lost all matches against B. $P_{A/B}=0$
B won all matches against C . $P_{B/C}=1$
We can not say anything about a real match between A and C. We can consider their chances are same as limit definition for this condition.
$$P_{A/C}=1/2$$
More Generally
A won m times against B in n games. $P_{A/B}=frac{n}{m}$
B won x times against C in y games. $P_{B/C}=frac{x}{y}$
I would like to find an estimated probability before a real match between A and C
$$P_{A/C} =f(m,n,x,y)$$
Some properties of the function $f(m,n,x,y)$ must satisfy that:
The limit conditions:
$f(0,n,0,y)=0 tag{1}$- $f(0,n,y,y)=frac{1}{2} tag{2}$
- $f(n,n,0,y)=frac{1}{2} tag{3}$
- $f(n,n,y,y)=1 tag{4}$
Other important property:
A won x times against B in y games. $P_{A/B}=frac{x}{y}$
B won m times against C in n games. $P_{B/C}=frac{m}{n}$
We should have the same probability with previous result. $$P_{A/C} =f(x,y,m,n)=f(m,n,x,y)$$
Thus,
- $f(m,n,x,y)=f(x,y,m,n) tag{5}$
Other property is:
$$P_{C/A} =1-P_{A/C}$$
- $f(y-x,y,n-m,n)=1-f(m,n,x,y)$
Because of property 5 above, we can write that
$f(y-x,y,n-m,n)=f(n-m,n,y-x,y)$
- $f(n-m,n,y-x,y)=1-f(m,n,x,y) tag{6}$
I have found the candidate function that satisfies these 6 conditions:
$$f(m,n,x,y)=frac{1}{2} (frac{m}{n}+frac{x}{y}) =frac{P_{A/B}+P_{B/C}}{2} tag{7}$$
$$P_{A/C} =frac{P_{A/B}+P_{B/C}}{2} tag{8}$$
I want to extend the idea for 4 players and
I tested the candidate function(7) for 4 players conditions but the candidate function did not work
Let's see the status for 4 players.
A won m times against B in n games. $P_{A/B}=frac{n}{m}$
B won x times against C in y games. $P_{B/C}=frac{x}{y}$
C won k times against D in z games. $P_{C/D}=frac{k}{z}$
I want to find $$P_{A/D} =g(m,n,x,y,k,z)$$
Limit conditions:
$P_{A/D}=g(0,n,0,y,0,z)=0 $
$P_{A/D}=g(0,n,0,y,z,z)=frac{1}{2}$
/Absolutely, C is the most powerful player but We cannot say anything between A and D before a real match, so we need to give same chance for A and D before a real match. (C>[A,B,D])
$P_{A/D}=g(0,n,y,y,0,z)=frac{1}{2}$
/Absolutely, B is the most powerful player
but we do not know the level between A and D. (B>[A,C,D])
$P_{A/D}=g(0,n,y,y,z,z)=frac{1}{2}$
/Absolutely, B is the most powerful player but we do not know the level between A and D.(B>[A,C,D])
$P_{A/D}=g(n,n,0,y,0,z)=frac{1}{2}$
/Absolutely, The worst player is B but we do not know the level between A and D.([A,C,D]>B)
$P_{A/D}=g(n,n,0,y,z,z)=frac{1}{2}$
/Absolutely, The worst player is B but we do not know the level between A and D.([A,C,D]>B)
$P_{A/D}=g(n,n,y,y,0,z)=frac{1}{2}$
/Absolutely, The worst player is C but we do not know the level between A and D.([A,B,D]>C)- $P_{A/D}=g(n,n,y,y,z,z)=1$
other properties:
- $g(m,n,x,y,k,z)=g(m,n,k,z,x,y)=g(x,y,m,n,k,z)=g(x,y,k,z,m,n)=g(k,z,x,y,m,n)=g(k,z,m,n,x,y)$
$P_{D/A} =1-P_{A/D}$ thus $g(n-m,n,y-x,y,z-k,z)=1-g(m,n,x,y,k,z)$
EDIT:
I have found an candidate function $P_{A/D}$ for 4 players : It satisfies all 10 conditions above .
$$P_{A/D}=frac{1}{2}(P_{A/B}+P_{B/C}+P_{C/D})-frac{1}{2}(P_{A/B}P_{B/C}+P_{B/C}P_{C/D}+P_{A/B}P_{C/D})+P_{A/B}P_{B/C}P_{C/D}$$
My candidate function for 5 players ${{A,B,C,D,E}}$ and known values $P_{A/B},P_{B/C},P_{C/D},P_{D/E}$
$$P_{A/E}=frac{1}{2}(P_{A/B}+P_{B/C}+P_{C/D}+P_{D/E})-frac{1}{2}(P_{A/B}P_{B/C}+P_{A/B}P_{C/D}+P_{A/B}P_{D/E}+P_{B/C}P_{C/D}+P_{B/C}P_{D/E}+P_{C/D}P_{D/E})+frac{1}{2}(P_{A/B}P_{B/C}P_{C/D}+P_{A/B}P_{B/C}P_{D/E}+P_{B/C}P_{C/D}P_{D/E}+P_{A/B}P_{C/D}P_{D/E})$$
I would like to generalize the problem for n players . What is the function for n players case?
I haven't seen such probability formula during my search. Please let me know if you know a research about it.
Thanks
Best Regards
probability probability-theory
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add a comment |
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I would like to find a probability between opponents that have never played with each other.
I would like to explain what I mean in an example.
Player A won m times against Player B and never lost a match against Player B.
Player B won n times against Player C and never lost a match against Player C.
If Player A and Player C play a match, As a sense, we can easily say that Player A has big advantage against Player C even though they have never played a match before.
I would like to find a formula to define the probability for such events that we need to formalize such kind of probability events.
Firstly, I want to define limit possibilities
A won all matches against B. $P_{A/B}=1$
B won all matches against C. $P_{B/C}=1$
Let's define probability before a real match between A and C
the probability of winning A against C: $$P_{A/C}=1$$
A lost all matches against B . $P_{A/B}=0$
B lost all matches against C . $P_{B/C}=0$
Let's define the probability before a real match between A and C
The probability of winning A against C: $$P_{A/C}=0$$
Other limit possibilities:
A won all matches against B. $P_{A/B}=1$
B lost all matches against C. $P_{B/C}=0$
We can not say anything about a real match between A and C. We can consider their chances are same as limit definition for this condition.
$$P_{A/C}=1/2$$
A lost all matches against B. $P_{A/B}=0$
B won all matches against C . $P_{B/C}=1$
We can not say anything about a real match between A and C. We can consider their chances are same as limit definition for this condition.
$$P_{A/C}=1/2$$
More Generally
A won m times against B in n games. $P_{A/B}=frac{n}{m}$
B won x times against C in y games. $P_{B/C}=frac{x}{y}$
I would like to find an estimated probability before a real match between A and C
$$P_{A/C} =f(m,n,x,y)$$
Some properties of the function $f(m,n,x,y)$ must satisfy that:
The limit conditions:
$f(0,n,0,y)=0 tag{1}$- $f(0,n,y,y)=frac{1}{2} tag{2}$
- $f(n,n,0,y)=frac{1}{2} tag{3}$
- $f(n,n,y,y)=1 tag{4}$
Other important property:
A won x times against B in y games. $P_{A/B}=frac{x}{y}$
B won m times against C in n games. $P_{B/C}=frac{m}{n}$
We should have the same probability with previous result. $$P_{A/C} =f(x,y,m,n)=f(m,n,x,y)$$
Thus,
- $f(m,n,x,y)=f(x,y,m,n) tag{5}$
Other property is:
$$P_{C/A} =1-P_{A/C}$$
- $f(y-x,y,n-m,n)=1-f(m,n,x,y)$
Because of property 5 above, we can write that
$f(y-x,y,n-m,n)=f(n-m,n,y-x,y)$
- $f(n-m,n,y-x,y)=1-f(m,n,x,y) tag{6}$
I have found the candidate function that satisfies these 6 conditions:
$$f(m,n,x,y)=frac{1}{2} (frac{m}{n}+frac{x}{y}) =frac{P_{A/B}+P_{B/C}}{2} tag{7}$$
$$P_{A/C} =frac{P_{A/B}+P_{B/C}}{2} tag{8}$$
I want to extend the idea for 4 players and
I tested the candidate function(7) for 4 players conditions but the candidate function did not work
Let's see the status for 4 players.
A won m times against B in n games. $P_{A/B}=frac{n}{m}$
B won x times against C in y games. $P_{B/C}=frac{x}{y}$
C won k times against D in z games. $P_{C/D}=frac{k}{z}$
I want to find $$P_{A/D} =g(m,n,x,y,k,z)$$
Limit conditions:
$P_{A/D}=g(0,n,0,y,0,z)=0 $
$P_{A/D}=g(0,n,0,y,z,z)=frac{1}{2}$
/Absolutely, C is the most powerful player but We cannot say anything between A and D before a real match, so we need to give same chance for A and D before a real match. (C>[A,B,D])
$P_{A/D}=g(0,n,y,y,0,z)=frac{1}{2}$
/Absolutely, B is the most powerful player
but we do not know the level between A and D. (B>[A,C,D])
$P_{A/D}=g(0,n,y,y,z,z)=frac{1}{2}$
/Absolutely, B is the most powerful player but we do not know the level between A and D.(B>[A,C,D])
$P_{A/D}=g(n,n,0,y,0,z)=frac{1}{2}$
/Absolutely, The worst player is B but we do not know the level between A and D.([A,C,D]>B)
$P_{A/D}=g(n,n,0,y,z,z)=frac{1}{2}$
/Absolutely, The worst player is B but we do not know the level between A and D.([A,C,D]>B)
$P_{A/D}=g(n,n,y,y,0,z)=frac{1}{2}$
/Absolutely, The worst player is C but we do not know the level between A and D.([A,B,D]>C)- $P_{A/D}=g(n,n,y,y,z,z)=1$
other properties:
- $g(m,n,x,y,k,z)=g(m,n,k,z,x,y)=g(x,y,m,n,k,z)=g(x,y,k,z,m,n)=g(k,z,x,y,m,n)=g(k,z,m,n,x,y)$
$P_{D/A} =1-P_{A/D}$ thus $g(n-m,n,y-x,y,z-k,z)=1-g(m,n,x,y,k,z)$
EDIT:
I have found an candidate function $P_{A/D}$ for 4 players : It satisfies all 10 conditions above .
$$P_{A/D}=frac{1}{2}(P_{A/B}+P_{B/C}+P_{C/D})-frac{1}{2}(P_{A/B}P_{B/C}+P_{B/C}P_{C/D}+P_{A/B}P_{C/D})+P_{A/B}P_{B/C}P_{C/D}$$
My candidate function for 5 players ${{A,B,C,D,E}}$ and known values $P_{A/B},P_{B/C},P_{C/D},P_{D/E}$
$$P_{A/E}=frac{1}{2}(P_{A/B}+P_{B/C}+P_{C/D}+P_{D/E})-frac{1}{2}(P_{A/B}P_{B/C}+P_{A/B}P_{C/D}+P_{A/B}P_{D/E}+P_{B/C}P_{C/D}+P_{B/C}P_{D/E}+P_{C/D}P_{D/E})+frac{1}{2}(P_{A/B}P_{B/C}P_{C/D}+P_{A/B}P_{B/C}P_{D/E}+P_{B/C}P_{C/D}P_{D/E}+P_{A/B}P_{C/D}P_{D/E})$$
I would like to generalize the problem for n players . What is the function for n players case?
I haven't seen such probability formula during my search. Please let me know if you know a research about it.
Thanks
Best Regards
probability probability-theory
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It doesn't seem like a purely mathematical problem. Take boxing. Frazier seemed to have an advantage over Ali. Ali beat Foreman in their 1 fight. But Foreman completely dominated Frazier. A vs B and B vs C here tell us nothing useful about A vs C.
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– WDS
Dec 7 '18 at 10:06
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@WDS I just mention probability calculation before the event occurs. For example, the probability of having head for a fairy coin is 1/2 but you can get 2 times tail after flipping 2 times it. The probability of an event does not show what you will get in the future.
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– Mathlover
Dec 7 '18 at 11:09
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This is what rating systems are for, for example ELO: en.wikipedia.org/wiki/Elo_rating_system
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– Alex R.
Dec 7 '18 at 19:25
add a comment |
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I would like to find a probability between opponents that have never played with each other.
I would like to explain what I mean in an example.
Player A won m times against Player B and never lost a match against Player B.
Player B won n times against Player C and never lost a match against Player C.
If Player A and Player C play a match, As a sense, we can easily say that Player A has big advantage against Player C even though they have never played a match before.
I would like to find a formula to define the probability for such events that we need to formalize such kind of probability events.
Firstly, I want to define limit possibilities
A won all matches against B. $P_{A/B}=1$
B won all matches against C. $P_{B/C}=1$
Let's define probability before a real match between A and C
the probability of winning A against C: $$P_{A/C}=1$$
A lost all matches against B . $P_{A/B}=0$
B lost all matches against C . $P_{B/C}=0$
Let's define the probability before a real match between A and C
The probability of winning A against C: $$P_{A/C}=0$$
Other limit possibilities:
A won all matches against B. $P_{A/B}=1$
B lost all matches against C. $P_{B/C}=0$
We can not say anything about a real match between A and C. We can consider their chances are same as limit definition for this condition.
$$P_{A/C}=1/2$$
A lost all matches against B. $P_{A/B}=0$
B won all matches against C . $P_{B/C}=1$
We can not say anything about a real match between A and C. We can consider their chances are same as limit definition for this condition.
$$P_{A/C}=1/2$$
More Generally
A won m times against B in n games. $P_{A/B}=frac{n}{m}$
B won x times against C in y games. $P_{B/C}=frac{x}{y}$
I would like to find an estimated probability before a real match between A and C
$$P_{A/C} =f(m,n,x,y)$$
Some properties of the function $f(m,n,x,y)$ must satisfy that:
The limit conditions:
$f(0,n,0,y)=0 tag{1}$- $f(0,n,y,y)=frac{1}{2} tag{2}$
- $f(n,n,0,y)=frac{1}{2} tag{3}$
- $f(n,n,y,y)=1 tag{4}$
Other important property:
A won x times against B in y games. $P_{A/B}=frac{x}{y}$
B won m times against C in n games. $P_{B/C}=frac{m}{n}$
We should have the same probability with previous result. $$P_{A/C} =f(x,y,m,n)=f(m,n,x,y)$$
Thus,
- $f(m,n,x,y)=f(x,y,m,n) tag{5}$
Other property is:
$$P_{C/A} =1-P_{A/C}$$
- $f(y-x,y,n-m,n)=1-f(m,n,x,y)$
Because of property 5 above, we can write that
$f(y-x,y,n-m,n)=f(n-m,n,y-x,y)$
- $f(n-m,n,y-x,y)=1-f(m,n,x,y) tag{6}$
I have found the candidate function that satisfies these 6 conditions:
$$f(m,n,x,y)=frac{1}{2} (frac{m}{n}+frac{x}{y}) =frac{P_{A/B}+P_{B/C}}{2} tag{7}$$
$$P_{A/C} =frac{P_{A/B}+P_{B/C}}{2} tag{8}$$
I want to extend the idea for 4 players and
I tested the candidate function(7) for 4 players conditions but the candidate function did not work
Let's see the status for 4 players.
A won m times against B in n games. $P_{A/B}=frac{n}{m}$
B won x times against C in y games. $P_{B/C}=frac{x}{y}$
C won k times against D in z games. $P_{C/D}=frac{k}{z}$
I want to find $$P_{A/D} =g(m,n,x,y,k,z)$$
Limit conditions:
$P_{A/D}=g(0,n,0,y,0,z)=0 $
$P_{A/D}=g(0,n,0,y,z,z)=frac{1}{2}$
/Absolutely, C is the most powerful player but We cannot say anything between A and D before a real match, so we need to give same chance for A and D before a real match. (C>[A,B,D])
$P_{A/D}=g(0,n,y,y,0,z)=frac{1}{2}$
/Absolutely, B is the most powerful player
but we do not know the level between A and D. (B>[A,C,D])
$P_{A/D}=g(0,n,y,y,z,z)=frac{1}{2}$
/Absolutely, B is the most powerful player but we do not know the level between A and D.(B>[A,C,D])
$P_{A/D}=g(n,n,0,y,0,z)=frac{1}{2}$
/Absolutely, The worst player is B but we do not know the level between A and D.([A,C,D]>B)
$P_{A/D}=g(n,n,0,y,z,z)=frac{1}{2}$
/Absolutely, The worst player is B but we do not know the level between A and D.([A,C,D]>B)
$P_{A/D}=g(n,n,y,y,0,z)=frac{1}{2}$
/Absolutely, The worst player is C but we do not know the level between A and D.([A,B,D]>C)- $P_{A/D}=g(n,n,y,y,z,z)=1$
other properties:
- $g(m,n,x,y,k,z)=g(m,n,k,z,x,y)=g(x,y,m,n,k,z)=g(x,y,k,z,m,n)=g(k,z,x,y,m,n)=g(k,z,m,n,x,y)$
$P_{D/A} =1-P_{A/D}$ thus $g(n-m,n,y-x,y,z-k,z)=1-g(m,n,x,y,k,z)$
EDIT:
I have found an candidate function $P_{A/D}$ for 4 players : It satisfies all 10 conditions above .
$$P_{A/D}=frac{1}{2}(P_{A/B}+P_{B/C}+P_{C/D})-frac{1}{2}(P_{A/B}P_{B/C}+P_{B/C}P_{C/D}+P_{A/B}P_{C/D})+P_{A/B}P_{B/C}P_{C/D}$$
My candidate function for 5 players ${{A,B,C,D,E}}$ and known values $P_{A/B},P_{B/C},P_{C/D},P_{D/E}$
$$P_{A/E}=frac{1}{2}(P_{A/B}+P_{B/C}+P_{C/D}+P_{D/E})-frac{1}{2}(P_{A/B}P_{B/C}+P_{A/B}P_{C/D}+P_{A/B}P_{D/E}+P_{B/C}P_{C/D}+P_{B/C}P_{D/E}+P_{C/D}P_{D/E})+frac{1}{2}(P_{A/B}P_{B/C}P_{C/D}+P_{A/B}P_{B/C}P_{D/E}+P_{B/C}P_{C/D}P_{D/E}+P_{A/B}P_{C/D}P_{D/E})$$
I would like to generalize the problem for n players . What is the function for n players case?
I haven't seen such probability formula during my search. Please let me know if you know a research about it.
Thanks
Best Regards
probability probability-theory
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I would like to find a probability between opponents that have never played with each other.
I would like to explain what I mean in an example.
Player A won m times against Player B and never lost a match against Player B.
Player B won n times against Player C and never lost a match against Player C.
If Player A and Player C play a match, As a sense, we can easily say that Player A has big advantage against Player C even though they have never played a match before.
I would like to find a formula to define the probability for such events that we need to formalize such kind of probability events.
Firstly, I want to define limit possibilities
A won all matches against B. $P_{A/B}=1$
B won all matches against C. $P_{B/C}=1$
Let's define probability before a real match between A and C
the probability of winning A against C: $$P_{A/C}=1$$
A lost all matches against B . $P_{A/B}=0$
B lost all matches against C . $P_{B/C}=0$
Let's define the probability before a real match between A and C
The probability of winning A against C: $$P_{A/C}=0$$
Other limit possibilities:
A won all matches against B. $P_{A/B}=1$
B lost all matches against C. $P_{B/C}=0$
We can not say anything about a real match between A and C. We can consider their chances are same as limit definition for this condition.
$$P_{A/C}=1/2$$
A lost all matches against B. $P_{A/B}=0$
B won all matches against C . $P_{B/C}=1$
We can not say anything about a real match between A and C. We can consider their chances are same as limit definition for this condition.
$$P_{A/C}=1/2$$
More Generally
A won m times against B in n games. $P_{A/B}=frac{n}{m}$
B won x times against C in y games. $P_{B/C}=frac{x}{y}$
I would like to find an estimated probability before a real match between A and C
$$P_{A/C} =f(m,n,x,y)$$
Some properties of the function $f(m,n,x,y)$ must satisfy that:
The limit conditions:
$f(0,n,0,y)=0 tag{1}$- $f(0,n,y,y)=frac{1}{2} tag{2}$
- $f(n,n,0,y)=frac{1}{2} tag{3}$
- $f(n,n,y,y)=1 tag{4}$
Other important property:
A won x times against B in y games. $P_{A/B}=frac{x}{y}$
B won m times against C in n games. $P_{B/C}=frac{m}{n}$
We should have the same probability with previous result. $$P_{A/C} =f(x,y,m,n)=f(m,n,x,y)$$
Thus,
- $f(m,n,x,y)=f(x,y,m,n) tag{5}$
Other property is:
$$P_{C/A} =1-P_{A/C}$$
- $f(y-x,y,n-m,n)=1-f(m,n,x,y)$
Because of property 5 above, we can write that
$f(y-x,y,n-m,n)=f(n-m,n,y-x,y)$
- $f(n-m,n,y-x,y)=1-f(m,n,x,y) tag{6}$
I have found the candidate function that satisfies these 6 conditions:
$$f(m,n,x,y)=frac{1}{2} (frac{m}{n}+frac{x}{y}) =frac{P_{A/B}+P_{B/C}}{2} tag{7}$$
$$P_{A/C} =frac{P_{A/B}+P_{B/C}}{2} tag{8}$$
I want to extend the idea for 4 players and
I tested the candidate function(7) for 4 players conditions but the candidate function did not work
Let's see the status for 4 players.
A won m times against B in n games. $P_{A/B}=frac{n}{m}$
B won x times against C in y games. $P_{B/C}=frac{x}{y}$
C won k times against D in z games. $P_{C/D}=frac{k}{z}$
I want to find $$P_{A/D} =g(m,n,x,y,k,z)$$
Limit conditions:
$P_{A/D}=g(0,n,0,y,0,z)=0 $
$P_{A/D}=g(0,n,0,y,z,z)=frac{1}{2}$
/Absolutely, C is the most powerful player but We cannot say anything between A and D before a real match, so we need to give same chance for A and D before a real match. (C>[A,B,D])
$P_{A/D}=g(0,n,y,y,0,z)=frac{1}{2}$
/Absolutely, B is the most powerful player
but we do not know the level between A and D. (B>[A,C,D])
$P_{A/D}=g(0,n,y,y,z,z)=frac{1}{2}$
/Absolutely, B is the most powerful player but we do not know the level between A and D.(B>[A,C,D])
$P_{A/D}=g(n,n,0,y,0,z)=frac{1}{2}$
/Absolutely, The worst player is B but we do not know the level between A and D.([A,C,D]>B)
$P_{A/D}=g(n,n,0,y,z,z)=frac{1}{2}$
/Absolutely, The worst player is B but we do not know the level between A and D.([A,C,D]>B)
$P_{A/D}=g(n,n,y,y,0,z)=frac{1}{2}$
/Absolutely, The worst player is C but we do not know the level between A and D.([A,B,D]>C)- $P_{A/D}=g(n,n,y,y,z,z)=1$
other properties:
- $g(m,n,x,y,k,z)=g(m,n,k,z,x,y)=g(x,y,m,n,k,z)=g(x,y,k,z,m,n)=g(k,z,x,y,m,n)=g(k,z,m,n,x,y)$
$P_{D/A} =1-P_{A/D}$ thus $g(n-m,n,y-x,y,z-k,z)=1-g(m,n,x,y,k,z)$
EDIT:
I have found an candidate function $P_{A/D}$ for 4 players : It satisfies all 10 conditions above .
$$P_{A/D}=frac{1}{2}(P_{A/B}+P_{B/C}+P_{C/D})-frac{1}{2}(P_{A/B}P_{B/C}+P_{B/C}P_{C/D}+P_{A/B}P_{C/D})+P_{A/B}P_{B/C}P_{C/D}$$
My candidate function for 5 players ${{A,B,C,D,E}}$ and known values $P_{A/B},P_{B/C},P_{C/D},P_{D/E}$
$$P_{A/E}=frac{1}{2}(P_{A/B}+P_{B/C}+P_{C/D}+P_{D/E})-frac{1}{2}(P_{A/B}P_{B/C}+P_{A/B}P_{C/D}+P_{A/B}P_{D/E}+P_{B/C}P_{C/D}+P_{B/C}P_{D/E}+P_{C/D}P_{D/E})+frac{1}{2}(P_{A/B}P_{B/C}P_{C/D}+P_{A/B}P_{B/C}P_{D/E}+P_{B/C}P_{C/D}P_{D/E}+P_{A/B}P_{C/D}P_{D/E})$$
I would like to generalize the problem for n players . What is the function for n players case?
I haven't seen such probability formula during my search. Please let me know if you know a research about it.
Thanks
Best Regards
probability probability-theory
probability probability-theory
edited Dec 7 '18 at 16:06
Mathlover
asked Dec 7 '18 at 9:25
MathloverMathlover
6,22222467
6,22222467
$begingroup$
It doesn't seem like a purely mathematical problem. Take boxing. Frazier seemed to have an advantage over Ali. Ali beat Foreman in their 1 fight. But Foreman completely dominated Frazier. A vs B and B vs C here tell us nothing useful about A vs C.
$endgroup$
– WDS
Dec 7 '18 at 10:06
$begingroup$
@WDS I just mention probability calculation before the event occurs. For example, the probability of having head for a fairy coin is 1/2 but you can get 2 times tail after flipping 2 times it. The probability of an event does not show what you will get in the future.
$endgroup$
– Mathlover
Dec 7 '18 at 11:09
$begingroup$
This is what rating systems are for, for example ELO: en.wikipedia.org/wiki/Elo_rating_system
$endgroup$
– Alex R.
Dec 7 '18 at 19:25
add a comment |
$begingroup$
It doesn't seem like a purely mathematical problem. Take boxing. Frazier seemed to have an advantage over Ali. Ali beat Foreman in their 1 fight. But Foreman completely dominated Frazier. A vs B and B vs C here tell us nothing useful about A vs C.
$endgroup$
– WDS
Dec 7 '18 at 10:06
$begingroup$
@WDS I just mention probability calculation before the event occurs. For example, the probability of having head for a fairy coin is 1/2 but you can get 2 times tail after flipping 2 times it. The probability of an event does not show what you will get in the future.
$endgroup$
– Mathlover
Dec 7 '18 at 11:09
$begingroup$
This is what rating systems are for, for example ELO: en.wikipedia.org/wiki/Elo_rating_system
$endgroup$
– Alex R.
Dec 7 '18 at 19:25
$begingroup$
It doesn't seem like a purely mathematical problem. Take boxing. Frazier seemed to have an advantage over Ali. Ali beat Foreman in their 1 fight. But Foreman completely dominated Frazier. A vs B and B vs C here tell us nothing useful about A vs C.
$endgroup$
– WDS
Dec 7 '18 at 10:06
$begingroup$
It doesn't seem like a purely mathematical problem. Take boxing. Frazier seemed to have an advantage over Ali. Ali beat Foreman in their 1 fight. But Foreman completely dominated Frazier. A vs B and B vs C here tell us nothing useful about A vs C.
$endgroup$
– WDS
Dec 7 '18 at 10:06
$begingroup$
@WDS I just mention probability calculation before the event occurs. For example, the probability of having head for a fairy coin is 1/2 but you can get 2 times tail after flipping 2 times it. The probability of an event does not show what you will get in the future.
$endgroup$
– Mathlover
Dec 7 '18 at 11:09
$begingroup$
@WDS I just mention probability calculation before the event occurs. For example, the probability of having head for a fairy coin is 1/2 but you can get 2 times tail after flipping 2 times it. The probability of an event does not show what you will get in the future.
$endgroup$
– Mathlover
Dec 7 '18 at 11:09
$begingroup$
This is what rating systems are for, for example ELO: en.wikipedia.org/wiki/Elo_rating_system
$endgroup$
– Alex R.
Dec 7 '18 at 19:25
$begingroup$
This is what rating systems are for, for example ELO: en.wikipedia.org/wiki/Elo_rating_system
$endgroup$
– Alex R.
Dec 7 '18 at 19:25
add a comment |
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$begingroup$
It doesn't seem like a purely mathematical problem. Take boxing. Frazier seemed to have an advantage over Ali. Ali beat Foreman in their 1 fight. But Foreman completely dominated Frazier. A vs B and B vs C here tell us nothing useful about A vs C.
$endgroup$
– WDS
Dec 7 '18 at 10:06
$begingroup$
@WDS I just mention probability calculation before the event occurs. For example, the probability of having head for a fairy coin is 1/2 but you can get 2 times tail after flipping 2 times it. The probability of an event does not show what you will get in the future.
$endgroup$
– Mathlover
Dec 7 '18 at 11:09
$begingroup$
This is what rating systems are for, for example ELO: en.wikipedia.org/wiki/Elo_rating_system
$endgroup$
– Alex R.
Dec 7 '18 at 19:25