The TableLab Blog
How Poker Pros Handle Downswings: What Negreanu, Ivey and Adelstein’s Results Show
Negreanu lost $2.2 million in 2023, Ivey dropped $6.3 million on one online account, and Adelstein has just published a book about what winning cost him. We put their ledgers through a variance model to show what a real downswing looks like in buy-ins.
The Honest LayerAre Poker Solvers Allowed? Where the Line Is, Online and Live
Solvers, trainers, and trackers are allowed — away from the table. Open one mid-hand and it’s RTA. The exact rule text from PokerStars, GGPoker, the TDA and the WSOP, and the case that shows intent doesn’t save you.
Live Poker StrategyHow to Beat Calling Stations in Live Poker
They call everything — and research on 27M hands says the players who win the most pots win the least money. The value-betting math, the multiway problem every guide skips, and when to believe their raise.
Bankroll & VarianceWhat's a Good Win Rate in Live Poker? (bb/hr, Honestly)
Published benchmarks for a good $1/$2 win rate span $2 to $25 an hour — and none state their sample. We line them up, add the rake math, and show the hours a live win rate actually needs.
Bankroll & VariancePoker Tournament Variance: How Big a Sample Before Your ROI Means Anything?
9,208 entered the 2026 WSOP Main Event and 1,382 cashed. We ran our own variance engine on real field sizes — a true 20% ROI winner still has a 30% chance of showing a loss after 1,000 tournaments.
Live Poker StrategyHow to Read Players Without a HUD (Live Poker Reads)
No HUD live? The reads a HUD summarizes are all observable by hand. What to watch, why betting patterns beat poker faces, and how many hands a reliable read actually takes.
Bankroll & VariancePoker Bankroll Management: How Many Buy-Ins Do You Actually Need?
At least 50 buy-ins for cash, 100+ for tournaments — and the risk-of-ruin math behind why. A grounded guide for live cash and tournament players.
The Honest LayerCan AI Solve Poker? What LLMs Do vs. What Solvers Do
AI beat poker pros in 2019, but with CFR solvers, not language models. What LLMs actually do for your game, what they can't, and how to spot the hype.
More on the way: live cash and MTT strategy, pot odds and equity realization, and the rest of the series.