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Oct 26, 2014 Baccarat can be beaten. You haven't done anything to alter the house's edge on any one bet. The sum of a string of negative numbers is a negative number. Has not only generated back the $500k I have lost over the years playing baccarat using losing methods, but MUCH more. I want people to win. Just test the theory before deciding anything!
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How to Play Baccarat - For Beginners. How To Bet On Baccarat. First things first of course we bet. Now, you can bet on the player side or the banker side, so take your pick. Unlike blackjack are many other table games, the dealer really does all of it, so at this point sit back relax and see what happens. May 18, 2016 So why do so many Baccarat players make this bet? Because it pays 9 to 1. That large a payout is enticing, and for some, even irresistible. The problem is, ties occur in fewer than 1 in 10 hands. Bottom line: betting on a tie could pay off big. But you’re more likely to waste your bankroll on what professional Baccarat players consider a bad bet.
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Introduction
On This Page
Introduction
I don't like to accept articles by other writers. Few writers out there freelance at the kinds of standards I expect of myself for this site. Until now, I believe the only outside page I have accepted is the one on Flip It, by Michael Bluejay. However, when Eliot Jacobson mentioned he had found the Dragon Bet in EZ Baccarat easily countable I was eager to cover it. As far as I know this topic has never been covered before. So I was quite happy when Eliot agreed to share the results of his analysis with my readers. Enjoy! — Wizard
The number of betting rounds depends on the poker variation.In there are four betting rounds. Texas holdem first round betting game. In there are five and in there are just two betting rounds. Read are in-depth guide to the pot bet here:.Don't make the mistake of thinking that pot-limit poker is safer for your bankroll than no-limit poker. Even if they are limited to the size of the pot, bets in pot-limit poker are generally not smaller than in no-limit.Most bets in no-limit poker are actually the size of the pot or smaller. Have courage though; there are some tricks you can use to master the pot bet. How Betting Rounds Work in PokerEach poker hand is made up of a number of betting rounds.
Card Counting the Dragon Side Bet in EZ Baccarat
By Eliot Jacobson Ph.D., © 2011 The Dragon Side Bet for EZ Baccarat is simple to describe. This side bet pays 40-to-1 if the dealer’s three-card total of 7 beats the player, otherwise the bet loses. Analysis of the wager consists of a straight forward cycle through all possible hands. Table 1 gives the analysis for eight decks, with the house edge of 7.611% appearing in the lower right cell.
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Table 1
EZ Baccarat Dragon Side Bet
Event | Pays | Combinations | Probability | Return |
---|---|---|---|---|
Winning Dragon | 40 | 112,633,011,329,024 | 0.022530 | 0.901350 |
Losing Dragon | -1 | 4,885,765,264,174,330 | 0.977470 | -0.977470 |
Total | 4,998,398,275,503,360 | 1.000000 | -0.076110 |
The key is that in order for the player to win the Dragon bet, the dealer has to draw a third card. This requirement trumps everything else. The cards that keep the dealer from drawing that third card most often are the 8 and the 9. As these cards are removed from the shoe, the edge moves quickly towards the counter’s favor. An excess of smaller cards is also helpful. The cards 1-7 are each cards that can move the dealer’s final total to 7 if he draws. Determining which of these low cards result in a final total of 7 most often is the key.
The methodology used in this study is familiar. The overall house edge for the game dealt from eight decks is 7.611%. By removing each card in turn from an eight-deck shoe, its effect on the house edge can be determined. This allows card counting systems to be developed. After arriving at candidate systems, computer simulations are run to see if these systems can generate an edge in practice. If there is an edge, the question then becomes if this is significant enough to become an opportunity for the advantage player.
Table 2 shows the number of winning and losing hands that result from removing one card from an eight-deck shoe, along with the house edge after removing that card.
Table 2
House Edge by Card Removed
Card Removed | Winning Dragon | Losing Dragon | Total | House Adv. |
---|---|---|---|---|
1 | 111,068,343,867,648 | 4,815,237,648,815,950 | 4,926,305,992,683,600 | -0.075620 |
2 | 110,900,807,733,248 | 4,815,405,184,950,350 | 4,926,305,992,683,600 | -0.077010 |
3 | 110,879,201,710,336 | 4,815,426,790,973,260 | 4,926,305,992,683,600 | -0.077190 |
4 | 110,686,449,371,648 | 4,815,619,543,311,950 | 4,926,305,992,683,600 | -0.078790 |
5 | 110,691,915,602,560 | 4,815,614,077,081,040 | 4,926,305,992,683,600 | -0.078750 |
6 | 110,618,934,007,296 | 4,815,687,058,676,300 | 4,926,305,992,683,600 | -0.079360 |
7 | 110,577,900,912,896 | 4,815,728,091,770,700 | 4,926,305,992,683,600 | -0.079700 |
8 | 111,654,703,169,536 | 4,814,651,289,514,060 | 4,926,305,992,683,600 | -0.070740 |
9 | 111,583,436,417,536 | 4,814,722,556,266,060 | 4,926,305,992,683,600 | -0.071330 |
10 | 111,112,191,215,104 | 4,815,193,801,468,490 | 4,926,305,992,683,600 | -0.075250 |
Table 3
Effect of Removal
Card Removed | EOR | EOR x 1000 |
---|---|---|
1 | 0.000500 | 0.5 |
2 | -0.000900 | -0.9 |
3 | -0.001080 | -1.1 |
4 | -0.002680 | -2.7 |
5 | -0.002630 | -2.6 |
6 | -0.003240 | -3.2 |
7 | -0.003580 | -3.6 |
8 | 0.005380 | 5.4 |
9 | 0.004790 | 4.8 |
10 | 0.000860 | 0.9 |
Looking at the values in the last column of Table 3, and adjusting slightly to make it balanced, we get card counting “system 1” with tags (0.5, -0.9, -1.1, -2.7, -2.7, -3.3, -3.6, 5.4, 4.8, 0.9). The reader will most likely consider it daunting to use system 1 in practice. However, as a baseline counting system, it is worthwhile to see how it performs. In an effort to simplify this unwieldy system as much as possible, I also considered the card counting system with tags (0, 0, 0, -1, -1, -1, -1, 2, 2, 0). I’ll refer to this as “system 2.” This latter system is easily implemented by a counter of average skill level.
To gauge the effectiveness of each, I wrote a computer program to simulate using these two systems in live play. The game I simulated has the following shuffling and cut card rules:
- The game is dealt from a shoe with 8 decks.
- At the start of each shoe, a card is burned. Based on the value of the burn card, an additional number of cards are burned, equal to the value of the card.
- The cut card is placed 14 cards from the end of the shoe.
- After the cut card is dealt, one more round is dealt before shuffling.
Table 4 gives the results of a simulation of two hundred million (200,000,000) shoes.
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Table 4
Simulation Results: 200M Shoes
Item | System 1 | System 2 |
---|---|---|
Target Count | 10 | 4 |
Expected Value | 7.315% | 8.032% |
Standard Deviation | 6.456 | 6.567 |
Frequency of Bet | 10.698% | 9.163% |
Units Won per Shoe | 0.6361 | 0.5967 |
It is clear from the last row of Table 4 that system 2, with tags (0, 0, 0, -1, -1, -1, -1, 2, 2, 0), performs remarkably well in comparison to its optimal cousin.
The person who uses system 2 should make the Dragon bet whenever the true count is +4 or higher. If he does so, then on average he will have an 8.03% edge over the house each time he makes the bet. This counter will have the opportunity to make the Dragon bet at or above the target true count on 9.16% of his hands. Given that the average shoe yields about 80 hands, the counter should be able to make, on average, about seven Dragon bets per shoe with the edge.
In dollar terms, if the house allows a Dragon bet up to $100 (say), then on a per-shoe basis the counter will average about $59.67 profit. The counter will earn about $8.03 per $100 wagered on the Dragon bet.
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It is worthwhile to check that the simulated results for system 2 make sense combinatorially. One way to get a +4 true count off the top is to remove eight 8’s and eight 9’s from the deck. This will leave 400 cards remaining in the eight-deck shoe, with a running count of +32, for a true count of 4.16. In this case, combinatorial analysis gives a player edge of 1.0227%. Using a single deck, one way to get a +4 true count is to remove one 8 and one 9 from the deck. This leaves 50 cards with a +4 running count, giving a true count of 4.16. In this case, combinatorial analysis gives a player edge of 1.3114%. Because the player is making the Dragon bet at a true count of +4 and above, not just at +4, these computations represent a secondary confirmation of the simulated results.
Cut card placement varies by casino, so it is worthwhile to investigate how the edge changes with the placement of the cut card. Table 5 gives statistics for all cut card placements from 14 cards to 52 cards, and then by half-deck increments up to four decks. A cut card placement at one deck, instead of at 14 cards, decreases the potential profit to the player by about 50%.
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Table 5
Card Counting Statistics by Cut Card DepthExpand
Cut Card Depth | Trigger Count | Hands per Shoe | Expected Value | Standard Deviation | Bet Frequency | Percent of Shoes Played | Profit per Shoe (units) | Profit per Hour (60 hands) |
---|---|---|---|---|---|---|---|---|
12 | 4 | 81.69 | 8.30% | 6.575 | 9.31% | 67.31% | 0.631 | 0.464 |
13 | 4 | 81.48 | 8.15% | 6.570 | 9.24% | 66.54% | 0.613 | 0.451 |
14 | 4 | 81.28 | 8.03% | 6.567 | 9.16% | 65.81% | 0.597 | 0.440 |
15 | 4 | 81.08 | 7.87% | 6.562 | 9.09% | 65.12% | 0.580 | 0.429 |
16 | 4 | 80.88 | 7.81% | 6.560 | 9.02% | 64.47% | 0.569 | 0.422 |
17 | 4 | 80.67 | 7.67% | 6.556 | 8.95% | 63.81% | 0.554 | 0.412 |
18 | 4 | 80.47 | 7.64% | 6.555 | 8.87% | 63.14% | 0.545 | 0.407 |
19 | 4 | 80.27 | 7.48% | 6.551 | 8.80% | 62.48% | 0.528 | 0.395 |
20 | 4 | 80.07 | 7.42% | 6.549 | 8.73% | 61.80% | 0.518 | 0.388 |
21 | 4 | 79.86 | 7.37% | 6.547 | 8.66% | 61.14% | 0.510 | 0.383 |
22 | 4 | 79.66 | 7.28% | 6.545 | 8.58% | 60.51% | 0.498 | 0.375 |
23 | 4 | 79.46 | 7.20% | 6.542 | 8.52% | 59.93% | 0.487 | 0.368 |
24 | 4 | 79.26 | 7.04% | 6.538 | 8.45% | 59.35% | 0.472 | 0.357 |
25 | 4 | 79.05 | 7.03% | 6.537 | 8.38% | 58.77% | 0.466 | 0.353 |
26 | 4 | 78.85 | 6.92% | 6.534 | 8.32% | 58.20% | 0.454 | 0.345 |
27 | 4 | 78.65 | 6.88% | 6.533 | 8.25% | 57.65% | 0.446 | 0.340 |
28 | 4 | 78.45 | 6.84% | 6.532 | 8.18% | 57.13% | 0.439 | 0.336 |
29 | 4 | 78.24 | 6.75% | 6.529 | 8.12% | 56.64% | 0.429 | 0.329 |
30 | 4 | 78.04 | 6.69% | 6.527 | 8.05% | 56.12% | 0.421 | 0.323 |
31 | 4 | 77.84 | 6.61% | 6.525 | 7.99% | 55.61% | 0.411 | 0.317 |
32 | 4 | 77.64 | 6.58% | 6.524 | 7.92% | 55.06% | 0.405 | 0.313 |
33 | 4 | 77.43 | 6.49% | 6.521 | 7.86% | 54.53% | 0.395 | 0.306 |
34 | 4 | 77.23 | 6.47% | 6.521 | 7.80% | 53.99% | 0.389 | 0.302 |
35 | 4 | 77.03 | 6.38% | 6.518 | 7.73% | 53.49% | 0.380 | 0.296 |
36 | 4 | 76.83 | 6.33% | 6.517 | 7.67% | 53.00% | 0.373 | 0.291 |
37 | 4 | 76.62 | 6.22% | 6.513 | 7.61% | 52.53% | 0.363 | 0.284 |
38 | 4 | 76.42 | 6.21% | 6.513 | 7.55% | 52.06% | 0.358 | 0.281 |
39 | 4 | 76.22 | 6.18% | 6.512 | 7.49% | 51.59% | 0.353 | 0.278 |
40 | 4 | 76.02 | 6.15% | 6.511 | 7.43% | 51.13% | 0.347 | 0.274 |
41 | 4 | 75.81 | 6.10% | 6.510 | 7.37% | 50.70% | 0.340 | 0.269 |
42 | 4 | 75.61 | 5.97% | 6.506 | 7.31% | 50.29% | 0.330 | 0.262 |
43 | 4 | 75.41 | 6.05% | 6.508 | 7.25% | 49.85% | 0.330 | 0.263 |
44 | 4 | 75.21 | 5.97% | 6.506 | 7.19% | 49.40% | 0.323 | 0.257 |
45 | 4 | 75.00 | 5.92% | 6.504 | 7.13% | 48.95% | 0.317 | 0.253 |
46 | 4 | 74.80 | 5.81% | 6.501 | 7.07% | 48.48% | 0.307 | 0.246 |
47 | 4 | 74.60 | 5.80% | 6.501 | 7.01% | 48.03% | 0.304 | 0.244 |
48 | 4 | 74.40 | 5.72% | 6.498 | 6.95% | 47.60% | 0.296 | 0.239 |
49 | 4 | 74.19 | 5.68% | 6.497 | 6.90% | 47.19% | 0.291 | 0.235 |
50 | 4 | 73.99 | 5.68% | 6.497 | 6.84% | 46.77% | 0.287 | 0.233 |
51 | 4 | 73.79 | 5.63% | 6.496 | 6.78% | 46.36% | 0.282 | 0.229 |
52 | 4 | 73.59 | 5.62% | 6.495 | 6.73% | 45.95% | 0.278 | 0.227 |
1.5 decks | 4 | 68.32 | 4.79% | 6.470 | 5.37% | 36.51% | 0.176 | 0.154 |
2 decks | 4 | 63.06 | 4.16% | 6.451 | 4.20% | 28.71% | 0.110 | 0.105 |
2.5 decks | 4 | 57.79 | 3.64% | 6.436 | 3.19% | 22.09% | 0.067 | 0.070 |
3 decks | 4 | 52.53 | 3.22% | 6.423 | 2.34% | 16.44% | 0.039 | 0.045 |
3.5 decks | 4 | 47.27 | 3.13% | 6.420 | 1.62% | 11.70% | 0.024 | 0.030 |
4 decks | 4 | 42.00 | 2.74% | 6.409 | 1.05% | 7.79% | 0.012 | 0.017 |
About the Author
For more information on Eliot, or to contact him, visit http://ijmp.org/ .Related Pages
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