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Two player $A$ and $B$ are playing a tournament.

For Player $A$ (for a single game)

\begin{align}P(\text{Win})=\frac12\\ P(\text{Draw})=\frac16\\ P(\text{Lose})=\frac13\end{align}

The player who will win two consecutive games win the tournament.

Question

Find the probability of

(i) $A$ winning the tournament

(ii) $B$ winning the tournament

atin
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    This site isn’t a HW mill. Show your work. – Max0815 Nov 08 '19 at 14:25
  • @Max0815 I tried considering cases like WLWL...WW etc,but this doesn't seem to work – atin Nov 08 '19 at 14:43
  • Welcome to Math.SE. We are not here to blindly answer your homework questions. Please show the work you have done already to answer this question. This means that we can give answers which are at the right level of knowledge for you (so you don't get confused) and we won't repeat avenues you have already tried. If you truly cannot get started, then please list some of the techniques you have learnt about to answer this kind of question and we can help you get started. – lioness99a Nov 08 '19 at 14:43
  • @AtinLM10 Trying WLWL combinations won't work as there are infinite possibilities – lioness99a Nov 08 '19 at 14:51

3 Answers3

1

For player $A$, we have the following probability, for each game:

$$ P(Win) = p_W = \frac{1}{2}$$ $$ P(Draw) = p_D = \frac{1}{6}$$ $$ P(Loose) = p_L = \frac{1}{3}$$

There is a way to address this problem by considering states.

For example, at a given time, if the last game was a draw (D), then the two players are in the same situation, independently of the previous games, assuming no one as gained before. This corresponds to a neutral state. This neutral state is also attained at the start of the tournament.

We will call :

  • $P_0$: the probability of the neutral state
  • $P[W]$ the probability of the state attained when $A$ has gained the last game, but not the previous one
  • $P[WW]$ the probability of the state corresponding to a final victory for $A$, i.e. he gained the last two games
  • $P[L]$ the probability of the state attained when $A$ has lost the last game, but not the previous one
  • $P[LL]$ the probability of the state corresponding to a final loss for $A$, i.e. he lost the last two games

Then, it is straightforward to get the following relations:

$$P_0(t=0) = 1$$ $$P[W](t=0) = P[L](t=0) = P[WW](t=0) = P[LL](t=0) =0$$ $$P_0(t+1) = 1 + p_d(P_0 + P[W] + P[L])(t) $$ $$P[L](t+1) = p_L (P_0(t) + P[W])(t) $$ $$P[W](t+1) = p_W (P_0 + P[L])(t) $$ $$P[WW](t+1) = p_W P[W](t)$$ $$P[LL](t+1) = p_L P[L](t)$$

Finally, the global probability $P[WW]$ is obtained by summing all $P[WW](t)$ over (t).

At this point, much work is still needed to get $P[WW]$, but the problem has been simplified.

Note: a figure representing the states and their different relations help understanding the method and the relations above. This figure is relatively easy to draw by hand, I encourage you to do it.

There is sometimes the possibility to address this kind of problem by defining polynomials representing the status of a state at all time, for example:

$$P_0(X) = 1 + P_0(1) X + P_0(2) X^2 + P_0(3) X^3 + \dots$$

and to translate the previous relations in terms of polynomials.

For example: $$P_0(X) = 1 + p_D\,X(P_0(X) + P[W](X) + P[L](X)) $$

In this case, at the end, $P[Final Win] = P[WW](X=1)$

I will let you explore it if you want.

Damien
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1

Taking help from @Damien's approach
First I noticed that

P($A_w$)+P(B$_w$)=1

Because the probability that the tournament will continue forever i.e. Nobody wins is zero.
The summation of probabilities of all possible combination till the last draw is same for both A and B
$$X=\sum_{}{} P(......D)$$
Cases after last Draw for A's win={LWW,LWLWW,....} U {WW,WLWW,....}
$$P(A_w)=X*(1/4)*\sum_{n=0}^{\infty}(1/6)^n+X*(1/4)*(1/3)*\sum_{n=0}^{\infty}(1/6)^n$$ $$P(A_w)=X*(1/4)*(6/5)*(1+1/3)$$ $$P(A_w)=2X/5$$ Similarly $$P(B_w)=X/5$$
Now putting in above equation $$P(A_w)+P(B_w)=1$$ $$X=5/3$$ $$P(A_w)=2/3$$ $$P(B_w)=1/3$$

Sorry for the bad formatting I'm new at this site.
Any edit would be appreciated

atin
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  • @Damien is the answer and approach correct – atin Nov 10 '19 at 13:21
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    You simplified my approach! Simple solution at the end – Damien Nov 11 '19 at 08:12
  • @Atin: If a Markov chain is used, the answer that emerges is different. – true blue anil Mar 19 '21 at 17:22
  • @trueblueanil I'm not familiar with Markov chain, can you send the solution or maybe any hints? I'll also look up markov chain. – atin Mar 19 '21 at 17:56
  • @trueblueanil Also I don't have any official solution/answer for this, it's just a random question my friend asked me :/ – atin Mar 19 '21 at 18:02
  • Have a look here: https://math.stackexchange.com/questions/4063842/please-if-someone-help-me-to-find-the-winning-probability/4064092#4064092 – true blue anil Mar 19 '21 at 18:18
  • I didn't really got the question. The sum of probabilities of win, draw and loss doesn't add up to 1? – atin Mar 19 '21 at 19:47
  • @trueblueanil Let's chat on https://chat.stackexchange.com/ instead of here in comments – atin Mar 19 '21 at 19:48
  • @atin: Idk know anything more, but i found a question that gives a link that explains very simply. https://math.stackexchange.com/questions/2989382/conditional-probability-problem-anomaly – true blue anil Mar 20 '21 at 02:33
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For (i), you can try to consider all possible cases and find a pattern. For the question, all possible cases would mean letting the tournament "run to infinity".

For (ii), you can make use of the idea of complement.

Ethan Mark
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