Stat 35b: Introduction to Probability with Applications to Poker

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Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Standard undergrad probability course, not a poker strategy guide nor an endorsement of gambling. The usual undergrad topics + random walks, luck and skill,
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
HOW TO PLAY POKER.
Presentation transcript:

Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: Multiple callers with AA, 55, or KK Pot odds calculations Wasicka/Gold/Binger example HSP example: Gus vs. Daniel P(flop a full house) P(4 of a kind), by the river. Next time: Uniform random variables in R, Project A teams   u    u 

1) Heads up with AA? Dan Harrington says that, “with a hand like AA, you really want to be one-on-one.” True or false? * Best possible pre-flop situation is to be all in with AA vs A8, where the 8 is the same suit as one of your aces, in which case you're about 94% to win. (the 8 could equivalently be a 6,7, or 9.) If you are all in for $100, then your expected holdings afterwards are $188. a) In a more typical situation: you have AA against TT. You're 80% to win, so your expected value is $160. b) Suppose that, after the hand vs TT, you get QQ and get up against someone with A9 who has more chips than you do. The chance of you winning this hand is 72%, and the chance of you winning both this hand and the hand above is 58%, so your expected holdings after both hands are $232: you have 58% chance of having $400, and 42% chance to have $0. c) Now suppose instead that you have AA and are all in against 3 callers with A8, KJ suited, and 44. Now you're 58.4% to quadruple up. So your expected holdings after the hand are $234, and the situation is just like (actually slightly better than) #1 and #2 combined: 58.4% chance to hold $400, and 41.6% chance for $0. * So, being all-in with AA against 3 players is much better than being all-in with AA against one player: in fact, it's about like having two of these lucky one-on-one situations.

What about with a low pair? a) You have $100 and 55 and are up against A9. You are 56% to win, so your expected value is $112. b) You have $100 and 55 and are up against A9, KJ, and QJs. Seems pretty terrible, doesn't it? But you have a probability of 27.3% to quadruple, so your expected value is 0.273 x $400 = $109. About the same as #1! [ For these probabilities, see http://www.cardplayer.com/poker_odds/texas_holdem ]

Want multiple callers with KK? a) You have $100 and KK and are all-in against TT. You're 81% to double up, so your expected number of chips after the hand is 0.81 x $200 = $162. b) You have $100 and KK and are all-in against A9 and TT. You're 58% to have $300, so your expected value is $174. So, if you have KK and an opponent with TT has already called you, and another who has A9 is thinking about whether to call you too, you actually want A9 to call! Given this, one may question Harrington's suggested strategy of raising huge in order to isolate yourself against one player.

2. POT ODDS CALCULATIONS. Suppose someone bets (or raises) you, going all-in. What should your chances of winning be in order for you to correctly call? Let B = the amount bet to you, i.e. the additional amount you'd need to put in if you want to call. So, if you bet 100 & your opponent with 800 left went all-in, B = 700. Let POT = the amount in the pot right now (including your opponent's bet). Let p = your probability of winning the hand if you call. So prob. of losing = 1-p. Let CHIPS = the number of chips you have right now. If you call, then E[your chips at end] = (CHIPS - B)(1-p) + (CHIPS + POT)(p) = CHIPS(1-p+p) - B(1-p) + POT(p) = CHIPS - B + Bp + POTp If you fold, then E[your chips at end] = CHIPS. You want your expected number of chips to be maximized, so it's worth calling if -B + Bp + POTp > 0, i.e. if p > B / (B+POT).3/39 + 3/39 - C(3,2)/C(39,2) = 15.0%

3. Example: 2006 World Series of Poker (WSOP).   u  Blinds: 200,000/400,000, + 50,000 ante. Jamie Gold (4 3): 60 million chips. Calls. Paul Wasicka (8 7): 18 million chips. Calls. Michael Binger (A 10): 11 million chips. Raises to $1,500,000. Gold & Wasicka call. (pot = 4,650,000) Flop: 6 10 5. Wasicka checks, Binger bets $3,500,000. (pot = 8,150,000) Gold moves all-in for 16,450,000. (pot = 24,600,000) Wasicka folds. Q: Based on expected value, should he have called? If Binger will fold, then Wasicka’s chances to beat Gold must be at least 16,450,000 / (24,600,000 + 16,450,000) = 40.1%. If Binger calls, it’s a bit complicated, but basically Wasicka’s chances must be at least 16,450,000 / (24,600,000 + 16,450,000 + 5,950,000) = 35.0%.

3. Example: 2006 World Series of Poker (WSOP), continued Jamie Gold (4 3). Paul Wasicka (8 7). Michael Binger (A 10). Flop: 6 10 5. Given only Wasicka’s cards and the flop, P( or 9 or 4 on turn or river, or 77 or 88) = P(out & out) + P(out & non-out) + P(77) + P(88) [all 15 s,9s,4s are all outs] = (choose(15,2) + 15 * 32 + choose(3,2) + choose(3,2)) / choose(47,2) = 54.7%. Worst case scenario: what if only non- 9s or 4s, or 77 or 88 are outs? P(out & out) + P(out & non--non-out) + P(77) + P(88) [non- 9s & 4s are outs] = (choose(6,2) + 6 * 32 + choose(3,2) + choose(3,2)) / choose(47,2) = 19.7%.

4. High Stakes Poker: Daniel vs. Gus -- Which is more likely: * flopping a full house, or * eventually making 4 of a kind?

5. Suppose you’re all in next hand, no matter what cards you get. P(flop a full house)? Key idea: forget order! Consider all combinations of your 2 cards and the flop. Sets of 5 cards. Any such combo is equally likely! choose(52,5) different ones. P(flop full house) = # of different full houses / choose(52,5) How many different full houses are possible? 13 * choose(4,3) different choices for the triple. For each such choice, there are 12 * choose(4,2) choices left for the pair. So, P(flop full house) = 13 * choose(4,3) * 12 * choose(4,2) / choose(52,5) ~ 0.144%, or 1 in 694.

6. P(eventually make 4-of-a-kind) 6. P(eventually make 4-of-a-kind)? [including case where all 4 are on board] Again, just forget card order, and consider all collections of 7 cards. Out of choose(52,7) different combinations, each equally likely, how many of them involve 4-of-a-kind? 13 choices for the 4-of-a-kind. For each such choice, there are choose(48,3) possibilities for the other 3 cards. So, P(4-of-a-kind) = 13 * choose(48,3) / choose(52,7) ~ 0.168%, or 1 in 595.