If you add the VPIP statistic to your report you will see how it changes when you apply different filters. #VPIP# is a very simple expression filter that only queries the VPIP in the current/filtered dataset and when you are filtering for 'Folded River Folded to Bet' your VPIP in that sample of hands will be at or close to 100%. If you want to query lifetime statistics on filtered data then that is going to require an expression filter with a subquery:
- Code: Select all
cash_hand_player_statistics.amt_r_bet_facing > 0 and lookup_actions_r.action SIMILAR TO '(F|XF)' and player.id_player in (SELECT p.id_player from player p, cash_cache cc where p.id_player = cc.id_player group by p.id_player HAVING (( sum(cc.cnt_vpip) / (sum(cc.cnt_hands) - sum(cc.cnt_walks)) < .31)))
For more on how SELECT works see here
. For a tournament report just substitute 'cash' with 'tourney'. Bear in mind that filters like this can generate a lot of PostgreSQL processing so can take a while to complete if you have a large database and/or your database is not on an SSD. Furthermore if built-in filters are also being used then you might not get any results at all so make sure to put everything you want within the expression filter as in my example above.