My first exposure to the world of computational blackjack was as a graduate student,
while working on my physics Ph.D. dissertation. I had learned that blackjack was a
game where the player could obtain a long-term advantage over the house, and, like many others,
I found this to be fascinating. Fascinating enough, in fact, that I felt the need to
explore the concept in more detail, and created a very simple program to simulate playing
millions of hands of blackjack. Rather than calculating the counting strategy myself, I
used available strategies from published books, and experimented with different betting
systems, rules, depths of penetration--the usual parameters studied in the blackjack
universe. Of course, I found that by adhering to certain styles of play and strategies,
a player could indeed maintain an edge over the house, and therefore make a profit over time.
Armed with this data, I began to interest friends and colleagues in the concept of
assembling a team to "count" cards in casinos, making use of the data I had generated
with the simulation program. As we geared up to take on the casinos, I continued to
modify the original blackjack simulation for every rule and circumstance that came up,
changing the code every week. As it became more critical that the simulations be absolutely
correct, I started looking around to find if anyone sold a program that would simulate
blackjack games, with which I could compare our own results for basic games.
In choosing among the possible options, I came across Stanford Wong's Blackjack Count
Analyzer (BCA). At the time, BCA was one of the oldest and most reliable commercial
software programs sold. Verifying that the output from BCA was consistent with my code,
at least for the rules and games supported in BCA, gave us an added level of confidence.
And confidence in the numbers was essential, as we were now risking tens of thousands of
dollars on these results!
Once I started using BCA, I found that it contained a very nice bonus; it calculated complete
count strategies amazingly quickly, usually in seconds. BCA uses a combinatorial procedure
rather than direct simulation to find strategies, sacrificing a tiny bit of accuracy and
gaining a tremendous amount of speed. This is the method outlined and used by Peter Griffin
in The Theory of Blackjack, and it produces a wealth of information almost
instantaneously. Solely because of this feature, BCA was a unique and exceptionally useful product.
After using BCA for a while, I began to consider the idea of developing a new Windows-based
software that would use the strategy analyzer in BCA as the starting point, but would provide
even more ways to access the expectations and strategies generated. In addition, I thought
there were even more possibilities for combinatorial analysis that could extend the concepts
of BCA in new program. After discussing the idea with Stanford Wong, who liked the idea and
supplied his original BCA code to me, the Professional Blackjack Analyzer (PBA) project was started.
My goal has been to produce a program that with extremely sophisticated blackjack analysis
features, but in an attractive format that is intuitive and easy-to-use. I've always been
a fan of the large amount of visual content that has been a signature of modern programs,
and thus PBA has a multiwindow format populated with numerous displays, tables, and graphs
for the tremendous amount of information generated with every simulation and strategy generation.
PBA is best described as a project, rather than strictly as a product. It is evolving, as
users provide feedback as to what they want or don't want in the program. New releases occur
fairly frequently, as the code continues to be updated and new features added.
So long as PBA is useful, I will continue to maintain and expand it. Explore these web
pages to browse the features of PBA, or to find the most current information.