by Mike Aponte on February 3, 2010
At most casinos the dealer must “burn” the first card of a shoe by placing it directly in the discard tray before any cards are dealt. In Atlantic City the 
burn card is usually shown before it’s taken out of play, but what about when the burn card isn’t revealed? This seems to cause angst for some blackjack players (“that could have been my ace”), but what impact does it really have on the game? For the vast majority of blackjack players who aren’t keeping track of the count, it has no effect whatsoever. From a card counting perspective, when the dealer burns a card it’s equivalent to moving the cut card up by one. For example, if the cut card is placed at a deck and a half (78 cards), the burn card effectively moves the cut card to 79 cards. There’s simply one more unknown card. For both card counters and the average gambler, the impact is insignificant at best.
If burning the first card doesn’t serve as an effective measure against card counting, why do casinos employ this practice? The purpose of burning a card is to protect against the steering of the top card. If a card is exposed when the cards are presented to players to cut, the exposed card can be cut into play. Steering an ace to your self is worth a whopping 51% in expected win. Cutting a ten to self is worth a not too shabby 14%. Card steering is completely legal if the card information is obtained due to the dealer unknowinlgy exposing a card. The illegal acquisition of card information is what casinos are really concerned about. Cheaters can mark tens and aces, making them recognizable when they end up at the top of the shoe. There’s also the possibility of collusion with the dealer who either flashes the top card to fellow accomplices, or peaks at it and then passes on the information. The bottom line is, even if you’re counting there’s no need to fret about an unseen burn card. Essentially, all the dealer is doing is moving the cut card up by one.
by Mike Aponte on January 20, 2010
Professional gambler has always been a moniker that makes me twinge. As a card counter, I have never considered myself a gambler. Investor is a much more fitting title for a professional card counter. Some may say that this is an insignificant matter of semantics. After all, both gamblers & investors put their money on the line with the goal of making a profit. However, there is a big difference between the approaches & outcomes of a gambler as compared to an investor.
These are the traits of a gambler:
1) A gambler does little or no research & preparation before taking on risk.
2) A gambler hopes to win despite unfavorable odds.
3) A gambler acts based on hunches, misinformation & unproven systems.
4) A gambler is affected by the emotions of greed & fear.
5) A gambler’s motivation is largely driven by thrill seeking & entertainment.
6) A gambler loses.
Conversely, these are the traits of an investor:
1) An investor completes thorough research & preparation before taking on risk.
2) An investor knows he/she has a high probability of winning (making money) because the odds are in his/her favor.
3) An investor utilizes a rational & proven model or system.
4) An investor does not allow emotions to influence his/her decisions.
5) An investor’s motivation is not risk seeking & entertainment.
6) An investor wins.
These characteristics hold true not only in blackjack, but in just about any potential gamble/investment, whether it’s the stock market, poker, real estate or buying a fast food franchise. Gamblers tend to have a narrow, short-term view of risk versus reward, focusing primarily on the upside. On the other hand, investors see the big picture & factor in risk when evaluating the long-term prospect of an investment. Of course even the savviest investment has an element of chance. But, if you have the right mindset & implement a rational, proven approach, you will maximize your odds of success.
by Mike Aponte on April 17, 2009
Most blackjack players are oblivious to whether the dealer stands or hits on soft 17. The dealer stand on soft 17 rule has always been the standard, but a growing number of casinos now require the dealer to hit on soft 17 (hands like Ace, 6). Not only do most players fail to recognize the difference, some believe the hit soft 17 rule works in their favor since the dealer will bust more often. The dealer will bust more often, but the dealer also has the opportunity to improve on a weak total of 17. The reality is the dealer will improve his hand often enough that it will more than offset the increase in dealer busts. It’s not a good feeling when you have 20 and the dealer hits on a soft 17 and pulls 21 to wipe out the table.
Below are the dealer outcome probabilities for a 6-deck shoe for the stand soft 17 rule versus the hit soft 17 rule.*
18 19 20 21 Bust
Stand Soft 17 14.62% 14.04 18.85% 7.65% 29.60%
Hit Soft 17 14.82% 14.24 19.06% 7.86% 30.00%
As you can see, when the dealer hits soft 17 rule is in effect there is a greater probability the dealer will draw to 18, 19, 20, or 21. The net result of the hit soft 17 rule is that it adds .22% to the house edge. All else being equal your odds are better when the dealer stands on soft 17.
* Probabilities rounded to the nearest one hundredth of a percent. With the dealer stands on soft 17 rule, the probability of the dealer drawing to 17 is 15.25%. With the dealer hits soft 17 rule, the probability of the dealer drawing to a hard 17 is 14.02%.
by Mike Aponte on April 10, 2009
As the dealer lays down your second card, a smile grows across your face. You just got blackjack. A moment later your smile fades. The dealer has an ace showing. She calls out for insurance bets. Before the dealer checks the hole card, she makes eye contact with you, awaiting your decision. The player next to you advises, “I would take it. Even money is the smart move. ” The dealer agrees. “Always take insurance when you have blackjack. It’s a sure thing.”
To take insurance or not take insurance. It’s a decision that becomes tougher for players when they have a good hand, particularly blackjack. The more money on the line, the more likely players are to take insurance. This is where players go wrong. Insurance is not a wager you should take to “protect” your original bet. It is striclty a side bet on whether or not the dealer has a ten or face card in the hole. Players can insure their bets by placing an amount up to half their wager in the insurance area on the table. If the dealer does have a ten or face card in the hole, the bet pays off 2 to 1.
Let’s break down the expected win of insurance for a 6-deck shoe. When the dealer shows an ace, the odds she will have blackjack are 96/311. There are 96 ten-value cards in a 6-deck shoe and there are 312 total cards in a 6-deck shoe (52 x 6). Not counting the ace showing there are 311 cards remaining. There is a 96/311 chance that the dealer will flip over a ten or face card and pay off insurance bets 2 to 1. There is a 215/311 chance that the dealer will not have blackjack and all insurance bets will lose.
Based on a $100 bet, here is how the expected win works out.
(96/311) x ($200) + (215/311) x (-$100) = $(19200/311) -
$(21500/311)
$(19200/311) – $(21500/311) = -$(2300/311)
= -$7.395
Over the long run, for every $100 you wager on insurance you can expect to lose $7.395 . The insurance bet has a 7.395% house edge. To put this in perspective, the house edge on insurance is more than 14 times the edge versus a basic strategy player, playing at a .5% disadvantage. This is why one of the cardinal rules of basic strategy is never take insurance. So the next time someone tells you to take even money, remember, the only sure thing about insurance is that it will cost you a pretty penny over the long run.
Blackjack: What are the Odds?
by Mike Aponte on April 2, 2009
Blackjack is the name of the game. So what are the odds of getting dealt a blackjack? The probability depends on how many decks are played. Of course the essential ingredients to blackjack are an ace and a ten-value card (10, jack, queen, or king). In a single deck game there are 4 aces and 16 ten-value cards. You can get blackjack in one of two orders:
1) A ten-value card followed by an ace
2) An ace followed by a ten-value card
If we add the probabilities of these two events, this will give us the odds of getting blackjack.
The odds of getting a ten-value as your first card is 16/52. 16 ten-value cards divided by the total number of cards in 1 deck. The fraction 16/52 reduces to 4/13. The odds of getting an ace as your second card are 4/51. 4 aces divided by 51 cards remaining. Multiplying 4/13 by 4/51 gives us the odds of getting a ten-value card followed by an ace.
1) 4/13 x 4/51 = 16/663
Looking at the second scenario, the odds of getting an ace as your first card is 4/52 (4 aces divided by 52 cards) which reduces to 1/13. The odds of getting a ten-value as the second card are 16/51. 16 ten-value cards divided by 51 cards remaining.
2) 1/13 x 16/51 = 16/663
Adding the probabilities of the two different orders in which you can get blackjack (16/663 + 16/663) yields the total probability of getting blackjack.
16/663 + 16/663 = 32/663 = 4.827 %
For a 6-deck shoe, the same principles apply but the number of cards changes. In 6 decks, there are 24 aces, 96 ten-value cards, and 312 total cards.
1) Ten-value cards / Cards Remaining x Aces / Cards Remaining
(16 x 6) / (52 x 6) x 24 / (52 x 6) – 1
96 / 312 x 24/311 = 288/12,129
2) Aces / Cards Remaining x Ten-value cards / Cards Remaining
3/39 x 96311 = 288/12,129
The sum of the the two probabilities is 4.749% which means that you’ll get blackjack once out of every 21 hands.
by Mike Aponte on March 26, 2009
Brian is going with the underdogs for his Thursday and Friday NCAA Tournament picks. All Vegas lines are based on line at Caesars Palace on 3/25 as noted on Vegas.com.
1. Connecticut -7.5 vs Purdue. I’ll take the points and go with Purdue here. I do think UConn wins this but it will be a little tighter than the spread. Purdue put up some solid first round wins while UConn coasted against lesser competition. And I’ve got to wonder if the recently announced potential NCAA violations might weigh on the minds of UConn and Coach Jim Calhoun.
2. Duke -2.5 vs Villanova. I like the underdog again and have this game as a virtual “pick’em”. Both teams got a big home court advantage in the early rounds and were able to get through one tough game (Villanova vs American; Duke vs Texas). Villanova matches up pretty well with Duke and has been to the Sweet 16 several times. I think this will give them enough of an edge for me to take Villanova and the points here.
3. North Carolina -8.5 vs Gonzaga. UNC has looked good in the tournament while Gonzaga has had two tough games. The big question is still the state of Ty Lawson’s big toe. UNC should win this game but I think it will be a little closer than the spread. Take Gonzaga and the points.
4. Michigan State -2 vs Kansas. This is a rematch of a game played earlier this year in East Lansing, won easily by Michigan State. I believe the Jayhawks get revenge here. Bill Self has an incredible record in “revenge” games where he’s had a chance to pay back a team for a loss earlier in the same season. The team has grown since then and the numbers show Kansas may even win this outright by a point or two. Go with Kansas here.
by Mike Aponte on March 25, 2009
Brian’s picks went 0-2 on Sunday, making his record so far in the NCAA tournament a combined 2-7. So what does Brian’s 2-7 win-loss record tell us about his handicapping system? Very little. It’s not possible to determine the long term advantage of Brian’s system based on a tiny sample of 9 picks. Evaluating a handicapping system based on 9 picks is like trying to assess if a coin is biased after only 9 flips. Even in games or ventures that present the opportunity for skilled and knowledgeable players/investors to gain an edge, natural variability has much to do with what happens in the short and mid-term. Given a large enough sample size however, it is possible to determine if a system or hypothesis is valid.
Blackjack has an inherent advantage over sports handicapping and financial trading in that the system for winning at blackjack is black and white and has been proven for more than 40 years. Back in 1959, Professor Ed Thorp had a hypothesis that blackjack could be beat. Thorp formulated and tested his system using the supercomputers at MIT. Computer simulations played out millions of blackjack hands, and confirmed that basic strategy is the optimal playing strategy and that card counting yields a long term advantage for players. The validity and effectiveness of card counting has been irrefutably proven; when most blackjack players fall short it is due to a lack of knowledge or a lack in skill in applying the system.
For those who wish to make sports handicapping or financial trading a profession, a model must be built and then tested to determine if it will make money. The keys to building a successful model are developing a hypothesis, testing the hypothesis by crunching numbers using an ample and reliable database, defining a model, and back-testing the model by applying it to historical data to see if it’s profitable. The goal is to arrive at the predictors which forecast future outcomes such as final scores and market movements. Even if back-testing the model indicates profitability there is a possibility the model may no longer be as profitable or viable at all. Since the back-testing is based on past data, Vegas line makers may now take the predictive model into account or the stock market may have adjusted to the market bias. This is an issue that does not apply to blackjack since the variables (house rules and conditions) are very easy to account for when determining the value of a a particular game. In future posts we will explore in more detail how to build predictive models.
by Mike Aponte on March 21, 2009
Brian’s picks went 1-2 on Saturday. The following are Brian’s picks for Sunday.
1. Syracuse -1.5 vs Arizona State. I show this game as essentially a pick ‘em with a very slight edge to Arizona State. The computer models continue to be unimpressed with Syracuse despite their easy first round win. Arizona State showed nicely in the first round for what may have been an underrated Pac-10 conference. The bettors seem to be with me here as this one opened as Syracuse -2.5.
2. Xavier -4 vs Wisconsin. I really like Wisconsin in this one. I think Xavier wins…but this could another one of those overtime classics. The Badger nation will fill up the auditorium in Boise and they may even sneak this one out.
by Mike Aponte on March 20, 2009
Brian’s picks went 1-3 in the first round. Here are his picks and comments for the first dayof round 2. Brian’s picks are based on the lines at Caesars earlier today which are subject to movement.
1. Gonzaga -10.5 vs Western Kentucky. I show Gonzaga covering this easily. The ‘Zags came on late against Akron and look to continue that over the Hilltoppers. It was a nice upset for them in the first round but don’t look for it to continue over what will seem like a home court for Gonzaga.
2. Memphis -8.5 vs Maryland. Memphis did not look at all good on Thursday and did not cover their line. I believe they will this time. Maryland has been an extremely inconsistent team all year and often doesn’t look like the same team from game-to-game. I think both teams show their true colors in this one with Memphis winning big.
3. Villanova -1.5 vs UCLA. Both teams struggled mightily on Thursday and neither covered. This was very surprising for Villanova in that they basically have a home game. Even accounting for that the numbers give UCLA a slight edge in this one (about 1 point) I like the Bruins in the upset.
by Mike Aponte on March 18, 2009
photo by Kevin Tsui
In anticipation of March Madness, casual and hard core fans across the country have been turning in their tournament predictions for their office pools. I have a friend, Brian, whose interest in the tournament runs much
deeper than filling out a bracket. He has been handicapping and betting on tournament games since 2002. Brian is an avid sports fan, with college basketball being far and away his favorite, but his basketball picks are based on much more than watching games on television. Using a computer aided system, Brian projects the outcome of each game to find opportunities to beat the Vegas point spread. Brian is no slouch when it comes to computer programming. He has a BS in Computer Science and a MS in Computer and Information Science with an emphasis in Cybernetics. He did quite a bit of research in Artificial Intelligence back in the day and has designed and built intelligent decisioning systems for various financial services companies over the years.
In sports betting, the most common wager is a straight bet in which you must beat the point spread to win. For example, in the opening round of this year’s tournament, the Louisville Cardinals are playing the Moorehead State Eagles. Louisville is the #1 seeded team in the tournament, while Moorehead State is a #16 seed and was the last team to qualify for the final 64. It doesn’t take a basketball expert to recognize that Louisville has a very high probability of defeating Moorehead St. To equal the playing field for betting purposes, the sports books have made Louisville a 21 point favorite. If you bet on Louisville, the Cardinals must win by more than 21 points for you to win the wager. If you bet on Moorehead State, you can cash a winning ticket if the Eagles lose by 20 points or less. A 21 point Louisville victory would result in a tie for all bettors.
To make money as a sports handicapper, you not only have to beat the point spread, you have to beat the vigorish, more commonly called the “vig.” On a straight wager, you have to risk $1.10 for every $1.00 you would like to win. If you want to win $100, you have to risk $110. The difference between what you risk and the potential payout is the vig, which is basically a sports book’s commission for booking the transaction. The point spread is set at a number the sports books believe will draw an equal amount of betting action on both sides. Taking into account the vig, a sports bettor must win more than the break even point of 52.38% of his bets to yield a profit.
There is a significant amount of free data available that rank and rate college basketball teams. In addition to looking at a team’s record you can find RPI, power ratings, and predictor models from a variety of sources. Brian combines several of these with his own proprietary “secret sauce” to arrive at a numerical power ranking for each team. However, this is not enough. A power ranking reflects a team’s overall performance to date, but does not necessarily take into account other critical factors such as home court advantage, neutral court performance, injuries, hot streaks, rivalry matches and a team’s past tournament performance.
Brian forecasts the outcome of each game by taking the power ranking for each team and then adjusting that number to reflect factors specific to the match-up. Most of Brian’s projections have point spreads that are very close to the Vegas lines. Brian tosses these games out. He’s looking for games in which the Vegas line has a statistically significant difference from his computerized point spreads. Public opinion usually accounts for these differences. In order to get balanced action on both sides, the sports books will often shade their point spreads from what they consider the true lines. The point spreads on popular teams and favorites usually have public bias factored in. A sharp sports bettor is essentially betting against the public.
A summary of Brian’s handicapping approach:
1. Compute the baseline power ranking based on a combination of ratings that are publicly available.
2. Adjust the base ranking by other more intangible factors (injuries, home court, etc.)
3. Play out each “pod” as a 4 team mini-tournament at a site (for example, the #1, 16, 8 & 9 seeds) with every possible match-up to compute a favorite and a point spread.
4. Compare computerized system’s point spreads against the Vegas line and select the games with a significant difference.
Brian’s top 16 teams according to his base power rankings:
1. North Carolina
2. Pittsburgh
3. Connecticut
4. Duke
5. Louisville
6. Memphis
7. Michigan State
8. Gonzaga
9. Oklahoma
10. Missouri
11. Purdue
12. Wake Forest
13. Syracuse
14. West Virginia
15. Kansas
16. Villanova
*** Brian’s picks are for educational and entertainment purposes only. Any money wagered on these picks is solely the responsibility of the bettor. ***
Brian’s Picks and his comments for Thursday and Friday’s first round games:
LSU -2.5 vs Butler
I like Butler. There seems to be some hesitation to pick a mid-major over a “big” school from a major conference. However, the SEC is really down this year and LSU may be a case of “in the land of the blind, the one-eyed man is king.” Their numbers just aren’t that impressive given the competition. Butler has played well despite losing in their conference tourney final and is not a newcomer to the NCAA tournament. I actually look for the Bulldogs to win this game.
Gonzaga -11.5 vs Akron
I like Gonzaga to cover this one. This game is in Portland so Gonzaga should have the feel of a home court. Akron is a nice mid-major but will be in over their head against the ‘Zags.’
Illinois -4.0 vs Western Kentucky
I like the Illini to cover this one easily. This is a very popular upset pick – everyone loves the 5/12 game. But even with the injury to Frazier from Illinois the numbers just don’t support the emotional upset pick. Although the Big 10’s power is questionable, Illinois has had some nice non-conference wins contributing to their power numbers and should be able to physically overpower Western Kentucky.
Arizona -1 vs Utah
I like the Utes in this one. Some might think Arizona has something to prove being the team many believe doesn’t belong. They are a traditional power but have struggled this year and have struggled as of late. Most importantly, every big win they’ve had has been at home. This game is in Miami. Utah has been a solid, consistent performer this year and I like them in the upset.