Datamining is a technique used by many professional poker players that involves observing and tracking hands on many tables at once, even when you are not playing. Software systems like SharkScope and PokerTableRatings will datamine hundreds of thousands of hands a day and sell the results to any player who wants to see their opponents involved in large numbers of hands.
Many players then proceed to import these hand into tracking applications like Holdem Manager or Poker Tracker, which has the feature of adding a heads up display on the table for each of your opponents! The advantage is clear: your opponents know nothing about you, but you have a hundred thousand hands on each of them.
It is vital for players using data mined hands to use them correctly, paying attention to the right stats and using them effectively. The easiest way to use data mined hands is to pay attention to three variables on your HUD.
The first, VPIP, or “voluntary put into pot percentage,” tells you how often an opponent sees the flop. Players with high VPIPs are loose, and players with low VPIPs are tight. Any opponent who puts money in the pot more than 25% or 30% of the time is probably a weak player.
The seconds PFR. or “pre-flop raise percentage,” determines how often a player raises pre-flop. Players with high PFRs are typically aggressive. Players who are passive have low PFRs, often under 10%. Poor players often have a large discrepancy between their PFR and VPIP numbers, signifying that they often limp before the flop.
The third number worth looking at is the opponents’ aggression factor, or AF. The AF number determines how often a player bets, as opposed to calls, after the flop. Players with high AFs are regularly betting, checking, or folding, but rarely calling. Most solid players have an AF ratio of about 3. Higher AFs can signify a maniac player at the table.
There are hundreds of stats available on most Holdem tracking programs, but these three can be placed on your HUD to provide a quick glimpse of the other players at your table. Some professional gamblers use data mining as a major part of their strategy, using ten or more statistics per player. Things like how often players fold to continuation bets, how often they lead out instead of checking to the bettor, and how often they fold before showdown. when taken together, can lead to a profile of an opponent much more complex than players can obtain without data mining.
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