MHB Winning Tennis with Probability 0.3 and 0.7

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The probability of winning a tennis game from Deuce with a point-winning probability of 0.3 is approximately 15.51%. The analysis involves calculating the probabilities of winning and losing points, leading to a series of independent trials. A state transition probability matrix can be constructed with states including Deuce, Ad-In, Ad-Out, and Game, where Game is an absorbing state. The winning probability can also be derived using a formula that simplifies the calculations by considering two points played at a time. Overall, the discussions emphasize the mathematical modeling of tennis scoring probabilities.
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Hi,

What is your probability of winning a game of tennis, starting from the even score Deuce (40-40), if your probability of winning each point is 0.3 and your opponent’s is 0.7?

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My answer:
I think the sequence of independent trials are required to win a game of tennis starting from even score Deuce(40-40),each of which is a success with probability (0.3 × 0.3 =0.09) or a failure with probability (0.7 × 0.3 + 0.7 × 0.3 =0.42). Suppose, the independent trials to win a game of tennis are n. That means after (n-1) trials of failures, the nth trial is success.

$$ \displaystyle\sum_{n=0}^{\infty} 0.09 \cdot (0.42)^n =\lim_{n \to \infty}\frac{0.09\cdot ( 1 - 0.42^n)}{1- 0.42}= 0.15517 $$ = 15.51 %
 
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Have you worked out the states and the state transition probability matrix?
I see the states as
Deuce, Ad-In, Ad-Out, Game

with Game being an absorbing state.
 
Write out all the conditional probabilites P(W|X) where X = A, B, D. You will have a linear system of three unknowns and three equations, which can be solved by standard methods.

For example: If you are in state B, you must win the next point to have any chance of winning. If you lose the point you lose the game, so
P(W|B) = q P(W|D)
because if you do win the point (which you do with probability q), then you will be in state D and your probability of winning will be P(W|D).
 
There is a useful shortcut in considering two point played at a time. If the probability of winning a point is ##p##, then the probability of winning the game (##P##) satisfies:
$$P = p^2 + 2p(1-p)P$$Hence$$P = \frac{p^2}{2p^2 - 2p + 1}$$With ##p = 0.3##, this gives ##P \approx 0.155##.
 
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PeroK said:
There is a useful shortcut in considering two point played at a time. If the probability of winning a point is ##p##, then the probability of winning the game (##P##) satisfies:
$$P = p^2 + 2p(1-p)P$$Hence$$P = \frac{p^2}{2p^2 - 2p + 1}$$With ##p = 0.3##, this gives ##P \approx 0.155##.
Other way of seeing this: Probability of winning in two points is ##p^2##. Probability of losing in two points is ##(1-p)^2 = 1-2p+p^2##. Probability of winning must therefore be
\[
\frac{p^2}{p^2 + (1-p)^2} = \frac{p^2}{2p(p-1) + 1}
\]
as otherwise we return to the same state.
 
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There is a nice little variation of the problem. The host says, after you have chosen the door, that you can change your guess, but to sweeten the deal, he says you can choose the two other doors, if you wish. This proposition is a no brainer, however before you are quick enough to accept it, the host opens one of the two doors and it is empty. In this version you really want to change your pick, but at the same time ask yourself is the host impartial and does that change anything. The host...

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