Garrett Adelstein is probably the most analyzed poker player on YouTube. His hands get dissected by coaches, posted on poker forums, argued about in Discord servers. He's been playing on Hustler Casino Live since its early days and his style — aggressive, fearless, capable of massive bluffs in massive pots — makes for compelling footage.
I fed one of his most discussed bluff hands into SpotMyTell's stream review tool to see what the AI would flag at each decision point. Then I compared that to what actually happened.
The results were educational — and honest about what AI analysis can and can't do.
The Hand
For context, this is based on a hand from Hustler Casino Live where Garrett ran a large bluff on a board that connected with multiple hands. Without getting into copyright territory, the setup: Garrett enters a pot in position with a speculative hand, the board runs out with texture that his range credibly hits hard, and he applies pressure across multiple streets against an opponent with a strong made hand who ultimately folds.
The pot is well into 5 figures. This is not a $1/2 hand.
Let's walk through the decision points.
Decision Point 1: Preflop (Enter the Pot)
Garrett opens or calls with a speculative holding in position. This is standard for his style — he plays a wide range in position, often for set-mining, nut draw potential, or pure positional advantage.
What SpotMyTell's AI flags here: Nothing unusual. Opening or calling a wide range in position is correct play. The AI's preflop tell analysis is limited because there isn't much behavioral signal before cards are dealt at high stakes — players at this level have tight preflop routines.
What a casual player can learn: Position matters enormously for hand selection. Garrett can play speculative hands because he'll have position on the flop, turn, and river. Those hands lose money out of position. Be very selective about what you enter pots with from the blinds.
Decision Point 2: Flop (First Major Decision)
The flop is a coordinated board — let's say it's something like 9-8-6 with two of a suit. It hits Garrett's range hard (two pair combos, sets, straights, flush draws) and is more ambiguous for his opponent.
Garrett checks or makes a small bet. The check is strategically interesting — he has board coverage (his range hits this better than his opponent's range) but checking keeps the pot small and disguises his range.
What SpotMyTell's AI flags:
Timing: Garrett's check comes quickly. In the AI's training data, quick checks in position on wet boards from strong ranges are often pot control or trap setups — not weakness. The system flags this as inconclusive without more baseline data on Garrett specifically.
Behavioral: The AI looks for body language tells but high-stakes live streams have HJ camera angles that make micro-tells hard to catalog. It notes his posture is neutral — no leaning, no chip activity change.
What a casual player can learn: On boards that favor your range, checking in position isn't weakness — it's range protection and allows you to call/raise on later streets with both strong hands and draws. This is a concept most $1/2 players miss.
Decision Point 3: Turn (The Pressure Builds)
A card hits the turn that could complete several draws or arrive a scare card for made hands. Garrett bets — a meaningful size, somewhere in the 60-70% pot range.
This is where it gets interesting.
What SpotMyTell's AI flags:
Sizing: The AI notes that Garrett's 60-70% sizing is within his normal range (established from other analyzed hands). It's not a deviation. Inconclusive as a tell.
Timing: Garrett takes slightly longer on the turn than he did preflop or on the flop. The AI flags this as a potential strength signal — long deliberation before a large bet correlates with strong hands in the aggregate data. But at this level, the deliberation might be tactical, not genuine.
Verbal: There's casual table conversation. Garrett doesn't narrate his decision. The absence of explanation is consistent with his baseline — he rarely explains himself at the table.
What a casual player can learn: The turn is where most big pot mistakes happen. Players who were "pot committed" by the flop make hero calls on the turn with hands they should fold. If you have a strong made hand but the board is screaming "you're beat" — the turn is when to reassess, not the river.
Decision Point 4: River (The Bluff)
The river completes potential draws or brings a card that Garrett's range can credibly have improved dramatically. He makes a large bet — oversized relative to the pot. His opponent tanks for a significant amount of time and eventually folds.
At showdown (or in the post-hand reveal): Garrett had a bluff. He was representing a hand he didn't have.
What SpotMyTell's AI flags:
Sizing (the most interesting flag): The overbet on the river is unusual. In Garrett's range, overbets appear in a relatively small percentage of his river spots. The AI flags: "River overbet is a deviation from this player's normal sizing range — moderate confidence signal of either very strong hand or bluff."
That's the right flag, but it's ambiguous. The AI correctly identifies the deviation. It cannot reliably tell you which direction it points without additional signals.
Timing: Garrett's river decision comes at roughly normal tempo for a large bet. No slowdown, no speedup. Inconclusive.
Behavioral: This is where human observation has an edge over AI with stream footage. In real-time, observers noted Garrett's demeanor was controlled, his chip handling casual. A specific tell that experienced live players might notice — but that doesn't consistently appear in pixel-level stream analysis.
What a casual player can learn: The river overbet as a bluff sizing is a real concept at high stakes. Betting big on the river with a bluff forces the opponent to risk their entire stack, not just a call-sized bet. At $1/2, this works less often because players call off their stacks more liberally. At $5/10+, it can be effective — but you need to be credibly representing a hand that makes sense.
What the AI Got Right
The AI correctly flagged the river overbet as a meaningful deviation from baseline. That's signal. At the lower stakes tables in its training data, river overbets are more heavily weighted toward bluffs (62%), so the flag was appropriate.
The timing analysis on the turn (longer deliberation before large bet) was a reasonable flag, even if it turned out to be strategic theater in this case.
What the AI Got Wrong
The AI had limited behavioral tell data on Garrett from this specific footage sample — he's too aware of cameras and too experienced to leak consistently in ways the AI could catalog with confidence. The "neutral posture = no information" finding was accurate but unhelpful.
More importantly, the AI couldn't evaluate the strategic logic that made this bluff credible. Garrett's bluff worked because his range on this board contains many strong hands that the villain's range does not. The AI can flag deviation patterns, but it doesn't fully model board coverage and range advantage — that requires GTO solver integration.
For that, I combine SpotMyTell with the equity calculator. One tool for behavioral patterns, one tool for range math.
The Bigger Lesson
Watching a professional bluff and breaking it down tells you more about what you shouldn't try to copy than what you should.
Garrett's bluff works because:
- He has a range advantage on the board
- He has a reputation that makes opponents fear him
- He has enough history with his opponent to know the sizing pressure would work
- He executed it with perfect composure
At $1/2, maybe one of those four conditions exists on any given bluff. Probably not all four.
The takeaway isn't "bet big as a bluff." It's: understand why a specific bluff works in a specific context, and only attempt the spots where the conditions are actually met.
SpotMyTell's stream review tool is most useful for studying players you actually play against — not just pros. Upload footage from your home game or a local stream and see what patterns the AI identifies. That data is actionable.What to Do Next
Go to SpotMyTell's stream review section and upload a hand or session clip from your own game. The analysis of players you actually sit with regularly is more valuable than dissecting Garrett Adelstein hands — even if it's less exciting.
If you want to study more professional footage, the player database has profiles on analyzed streamers and pros where the AI has enough sample size to flag reliable patterns. Check there before your next study session.