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What Kind of Records Should I Keep?

You should establish two basic statistical barometers: Your win rate, expressed as average amount of money won or lost per hour, and another figure, called "standard deviation," to measure short-term fluctuations. Your goal is to determine your average hourly expectation. Here's what to do:

Whenever you play online (or off):

Record your buy-in.
Record games, limits, and site (e.g., $4-$8 Omaha/8;).
Record amount won or lost at the end of each hour. (Although you can calculate average hourly winnings or losses without recording data every sixty minutes, you'll need this hourly information to calculate your standard deviation, which we'll show you how to do shortly.)
At the end of the session, record the number of hours played and the cash-out amount.

You'll also want to record this cumulative information:

Amount won or lost for the month
Amount won or lost for the entire year
Total number of hours played during the year

If you play at more than one online site, we advise keeping separate hourly, monthly, and yearly records for each one, then combining them monthly or at least annually for overall results.

The calculations are actually quite simple, even for the mathematically phobic. Computing your win or loss rate is just a matter of dividing amount of money won or lost by number of hours played. This calculation yields the average amount of money won or lost each hour. In statistics, we call that average figure the mean.

Knowing how much you're winning or losing on an hourly basis is important. But it's also important to know if your average, or mean, is a realistic barometer of your playing data.

That sounds confusing, but it's really not. Here's a simple case to illustrate:

Let's say San Francisco and Kansas City each have an average (mean) annual temperature of 65 degrees. But in San Francisco, the temperature rarely gets extremely hot or cold, while Kansas City is brutally hot in summer and bitterly cold in winter. While mean annual temperature might be the same for both cities, there's more of a spread between the highs and lows in Kansas City than in San Francisco. Consequently, the mean temperature of 65 degrees is more representative of San Francisco's temperate climate than of Kansas City's climatic extremes.

Now let's take the same concept to poker: Two players might each win an average of $15 per hour. One has big wins or big losses very rarely, while the other goes through wild swings or fluctuations (greater variance) to arrive at the same average win rate. Who's better off? Clearly, it's the player who achieves the same win rate while putting less of his bankroll at risk.

To measure variance - which speaks volumes about risk to your bankroll - we need to do a bit more with those observed values (amounts you won or lost each hour and recorded in your computer file or Site site) that you used to calculate average wins or losses. We need to know just how well the mean reflects reality. That's where the standard deviation comes in.

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