So You Want To Become Rich Playing Online Poker

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So you have been playing poker on one of those free sites for a while and finally feel comfortable to try your hand with real money. So you go out to PokerStars, PartyPoker, or other favorite site and transfer some money into an offshore account (if like me you are from the U.S.)

You've studied the rules of the game, could tell anybody any odds for hitting any hand, have read all of the bluffing books, and have watched every WSOP since Chris Moneymaker won back in 2003.

So, you play for real, and you suddenly realize "Toto, I don't think we are in Kansas anymore".

Playing online is a lot of fun but don't be naive --- it is not like inviting over a bunch of your friends and putting a $20 down. And I'm not talking about the possibilities that players may collude against you. What? Players could do that? Well, yeah, any number of players could be chatting in chat windows outside of the main application. But even if that is just a remote possibility, there is another highly legal way that a player might get an advantage on you ...

DATA! They have it, and you don't!

What kind of data do they have? Let's take a look at a sample Party Poker No-Limit Texas Hold 'Em hand provided by http://www.hand-histories.com/

note: IBrakeForData has "scrubbed" the data to make it anonymous
#Game No : 8570802646
***** Hand History for Game 8570802646 *****
$10 USD NL Texas Hold'em - Monday, November 02, 11:32:42 EST 2009
Table Table 169074 (Real Money)
Seat 5 is the button
Total number of players : 9
Seat 9: Player1 ( $1.85 USD )
Seat 4: Player2 ( $11.21 USD )
Seat 7: Player3 ( $10.74 USD )
Seat 2: Player4 ( $10 USD )
Seat 3: Player5 ( $10.62 USD )
Seat 6: Player6 ( $15.15 USD )
Seat 5: Player7 ( $3.02 USD )
Seat 8: Player8 ( $9.64 USD )
Seat 1: Player9 ( $4.73 USD )
Player6 posts small blind [$0.05 USD].
Player3 posts big blind [$0.10 USD].
** Dealing down cards **
Player8 folds
Player1 folds
Player9 folds
Player4 folds
Player5 folds
Player2 folds
Player7 folds
Player6 raises [$0.35 USD]
Player3 calls [$0.30 USD]
** Dealing Flop ** [ 5h, 9h, Js ]
Player6 bets [$0.57 USD]
Player3 folds
Player6 does not show cards.
Player6 wins $1.33 USD

As you will likely notice, this is the same output that you are used to seeing when you are at the table. The key attribute, however, is the sheer volume of data that you are able to get.

If you are playing at PartyPoker and the game is No-Limit-Holdem, you can buy this data based on the dollar amount of the table. For example, for a $10.00 table game with Full-Ring (7 - 10 players) you can get 800k hands for the special price of roughly €8.00 (about $12 USD at the time of this posting) or a staggering 5 million hands for €35.00 (about $52 USD at the time of this posting)

So, this is going to be one of those cases where IBrakeForData is going to say that the data alone is not incredibly valuable. The reason is quite simple --- you don't have all day to sit and analyze data at a table. The good news, however, is that you don't have to do this. Software programs have been written specifically for the analysis of hand history data. Two of these support a wide range of sites and have many users: Poker Tracker (PT) and Poker Office (PO).

And at this point: the data, combined with specialized software, becomes INCREDIBLY VALUABLE.

Just how much of an advantage does a player get with this data? Just look at the statistics that these programs are capable of calculating for you:

The Key Statistics
VPIP Voluntarily Put Chips In Pot %: Percentage of hands in which a player puts money (other than the blinds) into the pot
PFR Pre-flop Raise %: Percentage of hands in which a player raises the pot before the flop
PFA Post-flop Aggression Factor: A measure of how aggressive a player is after the flop
WTSD Went To Showdown %: Percentage of hands in which a player goes to showdown having seen the flop
W$SD Won at Showdown %: Percentage of showdowns won by the player
BB Steal Blind Steal %: Percentage of hands in which a player has an opportunity to steal the blinds, and attempts to do so (by raising preflop)
BB Defence Blind Defence %: Percentage of big blind steal attempts which fail against this player (because they called or reraised the 'stealing' raiser)
Continuation Bet Continuation Bet %: Percentage of the hands in which the player raised preflop then bet out on the flop

A full description of some of the statistics that can be created is provided by Hand-Histories.com at http://www.hand-histories.com/Articles/1/Opponent-Profiling---Making-Use-of-your-Statistics

When you can better predict what a player is likely to do, you have gained a serious advantage over them.

IBrakeForData

A Taste of What is To Come

In my last blog post, I said that this blog would focus on "Structured Data". This is a pretty loose term and I apologize ahead of time. A friend of mine even took my lack of definition to "comment" about his organic coffee business. Perhaps I should have used the term "Relational Data". The data I deal with in my "travels" will have many of the following properties:

• Related records have a common structure (example: the phone book)
• Nearly always includes numbers, dollar amounts, or other quantitative fields that are common to every row of data
• One or more common elements between two different sets of structured data
  

Why is this important? I want to be able to come to conclusions , plain and simple, based on data, common sense, and other facts that I can bring in from the web. And if we can have a little "fun" in the process with witty observations and comments from the peanut gallery, all the better.

I encourage readers to go to http://data.octo.dc.gov/ to see an example of data that I might explore in the future. This is the District of Columbia government data site. For example, you can get a spreadsheet that has all of the reported crimes and their lattitude and longitude coordinates. This type of data is very easy to dump into excel and manipulate for just about any purpose ... Or maybe you use the locations and dump those into a Google mapping tool to help you decide which hotel to NOT stay at the next you are in Washington on business ;-) Also note that they didn't provide an automatic mapping of their crime data like they did for other data sources (now why is that?).

Hope this gives you a taste for what will come in the near future when we travel the world of data.

IBrakeForData

Traveling the World ... One Data Source at a Time

Every Saturday night at 6:30pm, there was a show on our NBC affiliate called "The Eyes of Texas". The show featured a couple of 10-minute visits to usually obscure places in Texas. Some were big, most were small, some were in the city, most were nature. Most weekends I didn't watch the show that closely, but they never seemed to run out of stories (at the time, I just wasn't their target demographic).

If the State of Texas never ran out of stories in 30 years of broadcasts, I can barely fathom what kind of show "The Eyes of the World" could be. As great as that may seem, two thoughts come to mind. There are already a lot of shows that explore the world. Many do so with a keen eye on entertainment value. Travel shows instantly come to mind.

I have been exploring a business idea for the last 5 years, and this is where my second thought comes to life. I have a slight fascination with data (structured data, specifically), and the web has only served to increase my curiosity for data of the world in much the same way that a library enhances the experience of the curious reader.

When most people think of traveling the world, contemporary transportation is usually involved: Planes, Cruise Ships, etc. However, if your worldly experience is limited to airports and ports of call, you probably are missing out on so much that the world has to offer. A golfer who only plays from the fairway similarly "misses out" by not exploring the whole course ;-).

Over time, I will explore the world and its data ... one data source at a time ... except when brining in multiple sources of data would be more interesting. Just like the Eyes of Texas, I will tell stories with the data that I come across. In doing so, I will "travel the world".