James ‘SplitSuit’ Sweeney is a poker player, coach, and author dedicated to helping players think deeper and win more.
As a co-founder of Red Chip Poker and creator of numerous strategy resources — including The Poker Bank YouTube channel — he’s known for turning complex poker theory into clear, actionable advice.
How do we know when an exploitative play is winning?
Being able to demonstrate the profitability of an exploit with math is a powerful tool. It gives us the confidence to continue using that exploit, even if it appears to be failing in the short term.
Because let’s be honest, even +EV bluffs will sometimes get snapped off and +EV value shoves will sometimes get called by the pure nuts.
But by staying long-term focused and always looking for exploitative opportunities, we can develop edges far beyond attempting to perfectly mimic GTO solver output.
Solvers provide us with a theoretical benchmark, but real opponents rarely play at equilibrium. The power of exploitation lies in recognizing why deviations occur; whether from emotional tilt, cognitive bias, incorrect poker ranges, or misunderstanding of strategy — and then crafting our own plays that systematically capitalize on those leaks.
Unlike purely theoretical study, this exploitative process rewards creativity, observation, and adaptability. A sharp player doesn’t just memorize outputs; they recognize recurring human errors and build counter-strategies that thrive in imperfect environments.
Good exploits rely on solid underlying data. Once we have sufficient data, we are looking for two key types of exploits: Pool, and villain-specific.
When we have a large dataset on our player pool, we can establish which mistakes our opponents are making on average.
This allows us to target average tendencies and exploit unknown opponents by assuming they are exploitable in the same way as the rest of the pool. In some cases, our exploits will not work, but we will be right on average which is what makes the approach profitable.
Live players can make use of online hand histories to develop exploitative strategies for their live games, since the similarities outweigh the differences.
Developing large pool data requires sufficient play at a specific limit within a reasonable timeframe. While there are other means of gathering such a database, be sure to check with your poker site’s TOS first.
The most valuable data is the information we collect on individual opponents.
Exploits tailored to a specific villain take precedence over pool exploits. For online players, this usually means specific HUD stats on an opponent. For live players, this means manual observation of tendencies that may be exploitable.
In The Exploitative Edge, we consider many examples of pool exploits. Constructing villain-specific exploits follows the exact same procedure. We simply make use of villain-specific datapoints as opposed to generic pool averages.
Since pool exploits are based on the average tendencies of a certain player pool, and over a certain period of time, this might lead us to the following assumptions:
These assumptions are totally reasonable, but they do not represent reality.
A comparison of population data from separate online pools reveals the following:
We find that regardless of the player pool, the average poker player is exploitable in exactly the same ways. This is irrespective of whether they are live or online players.
Furthermore, we see the same average tendencies presenting themselves throughout the entirety of online poker’s relatively short history.
This is an expanded excerpt from the book The Exploitative Edge. The book dives into hand examples, player pool data, and more, so you develop a deeper edge in today’s games that’s not reliant on memorizing endless GTO solves!