Online result / GGPoker
3RD PLACE $468.02
- Event
- Daily Hyper $20
- Field
- 235
- Buy-in
- $20
- Players knocked out
- 12
- Duration
- 1:53:58
A fast-format online run, reaching the final three after eliminating 12 players.
Personal study / Strategy lab
POKER
CORNER.
A record of results from the felt, the tools I use to study the game, and an interactive space for thinking through decisions under uncertainty.
UTGVillain 31,940
SBVillain 11,990
BBVillain 21,980
BU · DHero2,000
Pot150
Q♣J♣
Current spot BU facing a 3× UTG open
01 Real results
02 Featured hand
03 Interactive trainer
04 Future poker tools
Results / From the felt
PLAY. TRACK.
LEARN.
I record outcomes to separate memorable hands from actual performance—and to make the swings visible rather than intuitive.
Best recorded tournament result
3RD PLACE
- Prize
- $3,145
- Field
- 107
- Buy-in
- $300
- Prize pool
- $26,215
A deep run in the Crown Wednesday Night no-limit event, finishing third from 107 entries.
Live result / PlayAPL
2ND PLACE $560
- Event
- Saturday Night
- Date
- 5 July 2025
- Buy-in
- $40
- Venue
- Tankerville
- Location
- Fitzroy, Victoria
A runner-up finish at the PlayAPL Saturday Night match at Tankerville in Fitzroy.
Favourite hand / Cash-game replay
THE $2.53K
POT.
The biggest cash-game pot I’ve been part of, reconstructed street by street in hand-replay software.
SCROLL-ACTIVATED REPLAY
Interactive trainer / Browser tool
MAKE THE
DECISION.
A browser interpretation of the Python CLI trainer I built to practise positional awareness, pot odds, range equity and realistic sizing.
poker_trainer.py — interactive session
AWAITING ACTION--- Starting Hand #8 ---
Hero(BU)D: 2000 | Villain 1(SB): 1990 | Villain 2(BB): 1980 | Villain 3(UTG): 1940
Pot: 150 | Board: --
Your Hand: Q♣ J♣
Equity vs Range: 15.5% Win / 0.8% Tie / 83.7% Lose
Action on Hero (BU) · Stack: 2000 · To Call: 60
Your options:
>
Choose an action to receive strategic feedback.
Realistic 4-Max
BU, SB, BB and UTG positions with correct action order and blind logic.
Range Equity
Monte Carlo equity against estimated ranges rather than random cards.
Opponent Profiles
Tight, loose and maniac tendencies change ranges and fold equity.
Practical Sizing
Minimum, half-pot, three-quarter-pot, pot and all-in options.
Session Metrics
VPIP, PFR, aggression factor and net results across the session.
CLI Roots
Inspired directly by the 1,400-line Python and Treys trainer.
Poker Lab / Next builds
WHAT COULD
COME NEXT.
The trainer is the first playable piece. These modules could turn Poker Corner into a deeper strategy laboratory.
01 / PLAYIn development
Play against the computer
A complete browser table with stochastic opponents, rotating positions, independent stacks and post-flop play.
02 / REVIEWConcept
Hand-history analyser
Paste a hand history and reconstruct the decision tree street by street.
03 / EQUITYConcept
Range visualiser
Compare equity, pot odds and fold equity as ranges and bet sizes change.
04 / TRACKConcept
Bankroll dashboard
Turn the spreadsheet workflow into a clean session log with filters and charts.
Poker as a decision problem
INCOMPLETE INFORMATION.
MEASURABLE UNCERTAINTY.
The attraction is not certainty—it is making the best decision possible with limited information, then learning from the result without confusing the two.
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