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Analysis of Saw Flop % against $Won/Hand using Poker Office
Poker Office provides many useful statistics. I shall start a small project to analyse some of these statistics using data collected from Empire Poker $0.50/$1.00 fixed limit tables.
The first thing I shall analyse is the relationship between SawFlop% and $Won/Hand. SawFlop% represents the percentage of flops that an individual player has seen. $Won/Hand represents the average amount won per hands played.
The last time I performed this analysis I set 200 hands as the minimum and didn't find any results. This time I have filtered the data to only show data for players for whom I have atleast 500 hands. The results should therefore be more significant.
Below is the chart. It is a plot of $Won/Hand against sawFlop%.
There are 17 players in the data sample. The correlation is positive at 0.61. And the Pearson correlation coefficient is 0.68. This suggests that there is a significant correlation between the two variables. i.e. Loose players tend to win more than tight players!!!!
This result against all popular wisdom. However, a closer look at the chart shows that the loosest player represented has a sawFlop% of 36%. Perhaps the tighter players are too weak? And it would be interesting to see the $Won/Hand statistics for players with sawFlop%'s greater than 40%.
I shall continue to gather statistics using Poker Office and will present further findings at a later date.
The first thing I shall analyse is the relationship between SawFlop% and $Won/Hand. SawFlop% represents the percentage of flops that an individual player has seen. $Won/Hand represents the average amount won per hands played.
The last time I performed this analysis I set 200 hands as the minimum and didn't find any results. This time I have filtered the data to only show data for players for whom I have atleast 500 hands. The results should therefore be more significant.
Below is the chart. It is a plot of $Won/Hand against sawFlop%.
There are 17 players in the data sample. The correlation is positive at 0.61. And the Pearson correlation coefficient is 0.68. This suggests that there is a significant correlation between the two variables. i.e. Loose players tend to win more than tight players!!!!
This result against all popular wisdom. However, a closer look at the chart shows that the loosest player represented has a sawFlop% of 36%. Perhaps the tighter players are too weak? And it would be interesting to see the $Won/Hand statistics for players with sawFlop%'s greater than 40%.
I shall continue to gather statistics using Poker Office and will present further findings at a later date.
Comments:
# 
pokerist wrote at 8:11 AM :
Hi there, Bronson from Pokerist Poker Blog here, sure link exchange, no problem.Send the link info to headspace101(at)bigdaddymail(dot)com
# Poker Gamer wrote at 7:03 PM :
yes i'm interested with the link exchange. Please let me know your anchor text.
# other1 wrote at 12:06 AM :
I think its going to be hard to get reasonable data from .5/1. Way to many people are gonna see the flop at such low limits and I suspect that is the reason your numbers seem strange.
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