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Some Statistical Analysis with Poker Office
I've started gathering some statistics, using Poker Office, at Party Poker. The aim of this exercise is to identify key differences between the best and worst players. I will also publish a list of the best and worst players (from my limited sample size), so that readers of this blog can have an additional edge when selecting tables.
From the few thousand hands in my database, I have averaged the statistics for the top and bottom 5 players, on $0.50/$1.00 tables at Party Poker. I will try not to use commonly held beliefs (e.g. you should be tight-aggressive), but will point out when the evidence reinforces or contradicts them.
The Saw Flop % for the top 5 was 31.62%, and 36.86% for the bottom 5. This confirms the common belief that a strong pre-flop hand selection is important.
The % showdowns for the top 5 was 12.5%, and13.55%. While these figures aren't significantly different, it does seem to suggest that the better players fold when they know they're beaten.
The PreFlopRaise% for the top 5 was 1.41%, and 0.80% for the bottom 5. This reinforces the typical view that aggressive play is rewarded.
In the future I shall try to present more useful statistics in a more elegant manner, and maybe even publish top 10 lists for the best and worst players.
From the few thousand hands in my database, I have averaged the statistics for the top and bottom 5 players, on $0.50/$1.00 tables at Party Poker. I will try not to use commonly held beliefs (e.g. you should be tight-aggressive), but will point out when the evidence reinforces or contradicts them.
The Saw Flop % for the top 5 was 31.62%, and 36.86% for the bottom 5. This confirms the common belief that a strong pre-flop hand selection is important.
The % showdowns for the top 5 was 12.5%, and13.55%. While these figures aren't significantly different, it does seem to suggest that the better players fold when they know they're beaten.
The PreFlopRaise% for the top 5 was 1.41%, and 0.80% for the bottom 5. This reinforces the typical view that aggressive play is rewarded.
In the future I shall try to present more useful statistics in a more elegant manner, and maybe even publish top 10 lists for the best and worst players.
