Poker move predictor

Track betting patterns over 50+ hands to spot weaknesses. If an opponent folds to 70% of river bets, target them with aggressive bluffs. Use software like PokerTracker or Hold’em Manager to log stats and identify trends automatically.

Focus on three key metrics: pre-flop raise percentage, continuation bet frequency, and fold-to-3bet rate. Players with a PFR below 15% often play too tight–exploit them by stealing blinds more often. Those who c-bet over 80%? Check-raise them frequently to force mistakes.

Adjust your strategy mid-session. If a player suddenly slows down after raising pre-flop, they likely missed the flop. Fire a second barrel 60-70% of the time to capitalize on their hesitation. Tools like GTO+ simplify these decisions by simulating optimal frequencies.

Review hand histories weekly. Note when opponents deviate from standard lines–like calling large turn bets with weak holdings. These leaks reveal future opportunities. The best predictors combine real-time reads with long-term data.

Poker Move Predictor: Analyze Opponent Strategies

Track bet sizing patterns–opponents often reveal hand strength through consistent sizing. If a player raises 3x with strong hands but 2.5x with bluffs, adjust your calls accordingly.

Spotting Timing Tells

Quick checks or rapid bets usually indicate weakness, while deliberate pauses often precede strong hands. Use software like PokerTracker to log response times and build profiles.

Compare showdown hands with earlier betting rounds. If a player bluffed on flush-draw boards twice in the last 50 hands, expect similar behavior in comparable spots.

Exploiting Positional Tendencies

Aggressive players in late position frequently steal blinds. Counter by 3-betting wider with suited connectors or pocket pairs when they open-raise.

Note showdown frequencies per position. Tight players folding 70% of small-blind hands? Apply pressure with small raises to force folds.

Update opponent profiles every 100 hands–players adjust. Recheck stats like pre-flop raise percentages and flop continuation bets to catch strategic shifts.

Collecting and interpreting opponent betting patterns

Track every bet size, timing, and position your opponent uses–these details reveal their tendencies. Players who consistently raise 3x from early position often have strong hands, while small donk bets on the flop may signal weakness.

Key metrics to record

Focus on three core stats: preflop raise frequency, continuation bet percentage, and fold-to-cbet rate. A player with 80% cbet but 60% fold-to-cbet is bluffing too often–attack their turn checks.

Notice timing tells. Instant calls usually mean draws or medium-strength hands, while delayed raises often indicate monsters. Online players using bet-sizing presets (like 33% pot) simplify pattern recognition.

Exploiting common leaks

Against passive opponents, steal blinds when they fold >70% to late-position raises. Versus aggressive 3-bettors, tighten your opening range and trap with premium hands. Adjust when they change speeds–sudden overbets often polarize to air or nuts.

Use software like PokerTracker to auto-log patterns, but review hands manually. Spotting that a player only slow-plays sets on paired boards beats raw stats alone. Merge data with live reads for maximum accuracy.

Identifying common pre-flop tendencies in players

Track how often opponents open-raise from each position. Tight players typically raise less than 15% of hands from early position, while loose players may exceed 25%. Use a HUD or note-taking tool to log these frequencies.

Positional awareness reveals player strength

Passive players frequently limp instead of raising, especially in late position. If an opponent limps more than 40% of hands, target them with isolation raises when you hold strong cards. Aggressive players often 3-bet from the blinds–adjust by widening your calling range against those who do it excessively.

Watch for sizing tells. Recreational players often min-raise or use inconsistent bet amounts, while regulars stick to standard 2.5-3x opens. An opponent who varies between 2x and 5x pre-flop likely lacks a disciplined strategy.

Exploiting predictable cold-calling ranges

Weak players cold-call too wide, especially with suited connectors or low pocket pairs. Against these opponents, increase your 3-bet frequency with strong hands to deny them equity. Solid players fold or re-raise instead of flat-calling–if someone consistently calls raises from middle position, their range is likely capped.

Note showdown hands where players defended from the blinds. Many over-defend with weak aces or small suited cards, creating profitable squeeze opportunities when you’re in late position. Adjust your stealing range accordingly when facing opponents who fold more than 60% of their blinds.

Using position to predict opponent aggression levels

Track how often opponents raise or 3-bet from each position. Late-position players (cutoff, button) tend to open wider and defend more aggressively. Early-position players (UTG, UTG+1) usually have stronger ranges and avoid excessive bluffs.

Key positional aggression indicators:

• Button raises 2.5x more often than UTG in 6-max games
• Small blind defends 15-20% wider against late-position opens
• Cutoff 3-bets 40% more frequently than hijack against early opens

Adjust your counter-strategies based on position-specific aggression:

1. Flat more against early-position 3-bets (65% of range)
2. 4-bet bluff 25% against late-position 3-bets
3. Steal 40% wider from button vs tight blinds

Use HUD stats to spot position-based leaks:

• VPIP/PFR gap >10% in early position indicates weak-passive play
• Button steal % below 50% suggests missed opportunities
• SB fold-to-steal above 65% invites more aggression

Compare aggression frequency between positions. A player with 15% 3-bet from UTG but 28% from cutoff likely adjusts ranges correctly. If numbers are similar across positions, they probably use static ranges.

Detecting bluffing frequencies through historical hand data

Track bluffing tendencies by analyzing how often opponents bet or raise with weak hands in specific spots. Focus on showdowns where they revealed bluffs, then compare those to similar non-showdown situations.

Use tracking software to filter hands where opponents:

• Faced significant aggression but folded
• Made large bets on scare cards (flushes/straights completing)
• 3-bet preflop then gave up postflop without showdown

Calculate bluff ratios with this formula:

Metric	Calculation	Target Value
Bluff Frequency	(Bluff Attempts / Total Aggressive Actions) × 100	25-35% (balanced player)
Fold-to-Bluff Rate	(Folds to Bluffs / Bluff Opportunities) × 100	Above 60% (exploitable)

Adjust your calling range against players who bluff more than 40% in late position – their value bets become thinner. Against players below 20% bluff frequency, fold more marginal hands to their aggression.

Spot timing tells in historical hands: frequent bluffs often correlate with faster-than-average bet timing (under 5 seconds in online play). Combine this with bet sizing patterns – many players use identical sizes for bluffs and value bets in specific positions.

Update your bluff detection metrics every 500 hands against regular opponents. Mark hands where your read was incorrect to refine your prediction model.

Exploiting showdown stats to adjust your playstyle

Track how often opponents reach showdown and their win rate in those spots. If a player shows down weak hands frequently, tighten your calling range against them post-flop.

Compare their showdown win rate with aggression stats. A player with low win rates but high aggression likely bluffs too much–call them down wider in marginal spots.

Adjust your bluffing frequency based on their fold-to-showdown percentage. Against opponents who rarely fold by the river, bluff less and value-bet more.

Identify players who consistently show down strong hands. Avoid bluff-catching against them unless you have clear reads or blockers to their value range.

Use showdown data to spot inconsistencies. A player who rarely reaches showdown but suddenly becomes sticky may have adjusted their strategy–recheck their recent stats.

Note position-based showdown tendencies. Some players overfold from early positions but call too much on the button–exploit by widening your value range accordingly.

Update your reads dynamically. If a tight player starts showing up with unexpected hands at showdown, they may be loosening up–adjust your 3-betting and calling ranges.

Tracking fold-to-cbet percentages for post-flop reads

Focus on opponents with a fold-to-cbet percentage above 60%–they’re likely weak post-flop and will surrender to aggression. Target these players with higher cbet frequencies, especially on dry boards where they struggle to continue.

How to calculate fold-to-cbet

Divide the number of times a player folds to a cbet by their total cbet defense opportunities. For example, if they fold 45 times out of 60, their fold-to-cbet is 75%. Track this over at least 100 hands for reliability.

Adjust your sizing based on their tendencies. Against players folding over 70% to cbets, use smaller bets (50-60% pot) to maximize profit while minimizing risk. Against those below 40%, check more often or barrel selectively with strong hands.

Exploiting positional differences

Players fold more often to cbets from late position–exploit this by widening your cbet range when acting last. If an opponent folds 80% in the blinds but only 55% in late position, increase aggression when they’re out of position.

Combine fold-to-cbet stats with flop texture. On disconnected boards (e.g., K-7-2), even tight players may fold more frequently. Against loose opponents, fire a second barrel on turn cards that complete draws they rarely chase.

Update your reads dynamically. If a player’s fold-to-cbet drops below 50% after adjusting, tighten your cbet range and focus on value hands. Use HUD stats or hand history reviews to spot these shifts quickly.

Adjusting predictions based on stack size dynamics

Treat short-stacked opponents (under 20 big blinds) as likely to shove or fold pre-flop, especially in late position. Their limited options reduce complex post-flop play, so tighten your calling range against all-in moves.

When facing deep-stacked players (over 80 big blinds), expect more multi-street bluffs and thin value bets. Their wider maneuverability means adjusting your aggression–3-bet lighter in position and avoid calling stations without strong equity.

Mid-stack opponents (30-50 big blinds) often balance survival and pressure. Probe their stack preservation habits: those who frequently min-raise or flat-call opens may fold to 65% pot-sized turn bets when stacks dip below 25 big blinds.

Track stack-to-pot ratios (SPR) post-flop. An SPR below 2 signals commitment–opponents with top pair or better rarely fold. Above SPR 5, leverage wider bluffing frequencies against cautious players who overfold in marginal spots.

Adjust your own stack strategy dynamically. If you double up early, shift toward polarized 3-betting (premium hands or weak Ax suited) to exploit medium stacks trying to ladder payouts.

Use HUD stats like “Stack-Adjusted Fold to Steal” to spot deviations. A player folding 70% at 40 big blinds but only 50% at 15 big blinds reveals exploitable short-stack desperation.

Implementing real-time HUD stats for live decision-making

Display VPIP (Voluntarily Put In Pot) and PFR (Pre-Flop Raise) percentages in a clear, color-coded format–green for passive (VPIP < 20%), yellow for neutral (20-30%), and red for aggressive (30%+). This instantly highlights opponents’ pre-flop tendencies without cluttering your screen.

• Aggression Frequency (AF): Track post-flop aggression ratios (bets + raises / calls). If AF > 2.5, expect frequent bluffs on scare cards like A or K high boards.
• Fold-to-CBet (Flop/Turn): Show separate stats for flop (e.g., 55%) and turn (e.g., 65%). Target players with high fold rates by increasing continuation bets.
• 3Bet% by Position: Highlight deviations–e.g., a player 3Betting 12% from UTG but only 6% from the CO signals positional awareness.

Use dynamic sizing for HUD elements–larger fonts for critical stats (like fold-to-steal) and smaller for situational data (like river donk bet frequency). Prioritize stats based on current street:

1. Pre-flop: VPIP, PFR, 3Bet%.
2. Flop: CBet%, fold-to-CBet, check-raise frequency.
3. Turn/River: Donk bet tendency, bluff catch rate (based on showdown history).

Set alerts for extreme deviations–e.g., if a tight player (VPIP 15%) suddenly opens to 5x, flag their bet sizing in red. Cross-reference with recent hands: did they show down a bluff earlier?

Adjust stat opacity during multi-tabling–reduce brightness for inactive tables but keep key metrics (like stack-to-pot ratios) visible. For live play, bind HUD updates to physical tells–if a player glances at chips after seeing a flop, check their aggression frequency before reacting.

Spotting bet sizing tells in different street scenarios

Compare opponent bet sizes between flop, turn, and river. A player who bets 60% pot on flops but 80% on turns often strengthens their range. Those who shrink bets on rivers frequently show weakness or block betting tendencies.

Create separate HUD stats for bet sizing by street. Track when opponents deviate from their standard sizing patterns – a 40% pot cbet followed by a 120% pot turn barrel signals polarized ranges more often than linear ones.

Note sizing differences between value bets and bluffs. Most players use 66-75% pot for thin value but overbet with nutted hands or air. Identify players who reverse this pattern by betting small with strong hands.

Adjust your calling ranges when facing abnormal sizing. Against a player who normally cbets 50% pot but suddenly uses 33%, fold more middle pair hands. Their sizing reduction typically indicates either extreme strength or complete missed draws.

Test opponents with probe bets after spotting sizing inconsistencies. If a player checks back flops with weak pairs but bets big on turns, float more flops against them to exploit this predictable line.

FAQ

How does a poker move predictor analyze an opponent’s betting patterns?

A poker move predictor tracks an opponent’s actions over multiple hands, noting tendencies like bet sizing, frequency of bluffs, and reactions to raises. By comparing this data against common strategies, it identifies patterns—such as tight-aggressive or loose-passive play—to forecast future moves. Advanced tools may also account for table dynamics and stack sizes to refine predictions.

Can these tools adapt to players who change their strategy mid-game?

Yes, modern predictors use machine learning to detect shifts in behavior. If an opponent suddenly becomes more aggressive after playing conservatively, the system recalculates probabilities based on recent actions. However, rapid adjustments may require manual input to avoid misinterpreting short-term deviations.

What’s the biggest limitation of poker prediction software?

The main drawback is reliance on historical data. Against unpredictable or highly skilled opponents who mix strategies, predictors may struggle. They also can’t account for psychological factors like tilt or table talk, which humans use to make reads.

Do professional players rely on these tools during live tournaments?

Most live tournaments ban real-time assistive tech, but pros often use predictors for post-game analysis. Online, some platforms allow certain tools (e.g., HUDs), helping players review stats like VPIP or PFR to adjust strategies between sessions.

How accurate are move predictions in heads-up vs. full-ring games?

Predictors tend to be more accurate in heads-up play due to fewer variables. In full-ring games, factors like multi-way pots and varying player styles reduce precision. Tools may prioritize tracking specific opponents rather than the entire table to compensate.

How does a poker move predictor analyze an opponent’s strategy?

A poker move predictor uses statistical models and historical data to assess an opponent’s tendencies. It tracks betting patterns, hand selection, and reaction times to identify weaknesses. By comparing actions across multiple hands, it can estimate whether a player is aggressive, passive, or prone to bluffing. Some tools also incorporate machine learning to improve accuracy over time.

Can poker prediction tools guarantee winning every hand?

No, these tools can’t guarantee wins because poker involves luck and unpredictability. They help players make better decisions by providing insights into opponents’ habits, but human error and random card distribution still play a role. The best use of predictors is to reduce mistakes, not eliminate all risk.

What data does a poker move predictor need to work effectively?

Predictors rely on large datasets of past hands, including bet sizes, timing, and showdown outcomes. The more hands analyzed, the better the tool can detect patterns. Some advanced systems also consider table position, stack sizes, and tournament stage to refine their predictions.

Are poker prediction tools legal in online games?

It depends on the platform. Many poker sites ban real-time assistance tools, including predictors, to maintain fair play. Using them could result in account suspension. However, post-game analysis software is often allowed since it doesn’t influence decisions during active play.

How do professional players use move predictors without getting caught?

Most pros avoid real-time predictors due to strict rules. Instead, they review hand histories after sessions to study opponents. Some use mental shortcuts based on experience rather than software. Those who risk detection often face severe penalties, making it a poor long-term strategy.

How does a poker move predictor actually analyze an opponent’s strategy?

A poker move predictor uses algorithms to track an opponent’s betting patterns, hand selections, and timing. It compares current actions with historical data to identify tendencies—like aggression, bluff frequency, or passive play. Some tools also factor in position, stack size, and table dynamics to refine predictions.

Can poker prediction software guarantee winning against skilled players?

No, it can’t guarantee wins. While predictors improve decision-making by spotting patterns, skilled players adapt and mix strategies. The software helps reduce mistakes but doesn’t replace intuition or psychological reads, which remain key in high-level play.

What are the limitations of using AI to predict poker moves?

AI struggles with unpredictable opponents, rare scenarios, and meta-game adjustments. It relies on data, so if a player suddenly changes tactics, the AI may lag in adapting. Also, most tools can’t interpret non-verbal tells, a major aspect of live poker.

Is using poker prediction software considered cheating?

In most online and live poker rooms, yes. Real-time assistance tools (RTA) are banned because they give unfair advantages. However, post-game analysis software for reviewing hands is usually allowed. Always check platform rules to avoid penalties.

How do professional players counter opponents using move predictors?

Pros vary bet sizes, bluff more randomly, and avoid repetitive patterns. They may also trap predictors by slow-playing strong hands or using balanced ranges. Adjusting strategies mid-game makes it harder for algorithms to lock onto tendencies.

How does a poker move predictor analyze an opponent’s strategy?

A poker move predictor uses statistical models and historical data to assess an opponent’s tendencies. It tracks betting patterns, hand frequencies, and reaction times to identify weaknesses. By comparing real-time actions with known strategies, it estimates likely moves and suggests counterplays. Advanced tools may incorporate machine learning to adapt as opponents adjust their playstyle.

Can poker prediction software guarantee winning outcomes?

No, prediction tools improve decision-making but don’t eliminate variance or guarantee wins. Poker involves incomplete information and luck, so even accurate predictions only increase edge over time. Skilled players use these tools alongside intuition and adaptability—software alone can’t replace experience.

What are the limitations of AI in predicting poker moves?

AI struggles with unpredictable opponents, especially those who bluff randomly or change tactics abruptly. It also relies on sufficient data—new players or rare strategies may confuse the model. Ethical concerns and platform rules against real-time assistance further limit practical use in live games.

How do professional players incorporate move predictors into their training?

Pros often use predictors post-game to review hands and spot leaks in their or opponents’ strategies. Some simulate scenarios against AI opponents to test reactions. However, in live play, they rely more on observed patterns and psychology—real-time predictors are usually banned in tournaments.

Reviews

ShadowReaper

*”Oh wow, another ‘revolutionary’ tool to predict poker moves—because clearly, the last dozen apps that promised to read minds at the table worked so well. Tell me, geniuses: when your algorithm gets outplayed by some drunk guy bluffing with a 2-7 offsuit, will you blame ‘unpredictable human behavior’ or just quietly update the TOS? Or maybe—just maybe—you’ll admit that poker’s still about luck, guts, and knowing when to fold before the AI starts crying over its lost data points?”* (328 символов)

Lucas

This whole idea of predicting poker moves just feels like another way to suck the soul out of the game. You sit there, staring at numbers and probabilities, pretending you’re some kind of genius, but really, you’re just letting a machine do the thinking for you. Where’s the actual skill in that? Half the fun is reading people, not some algorithm’s cold calculations. And let’s be honest—most of these tools are built by people who’ve probably never even felt the tension of a real bluff. They just crunch data and call it strategy, like that’s all poker is. News flash: it’s not. Real players adapt, improvise, play with instinct, not some pre-chewed stats. Plus, if everyone starts relying on this garbage, the game turns into a boring math test. No thanks. I’d rather lose to a human who outplayed me than win because some program told me what to do. Feels cheap. Feels empty. But hey, guess that’s what happens when people would rather pretend they’re smart than actually learn the game.

MysticFrost

*”Oh great, another fancy tool to tell me how bad I am at poker. Like I needed a program to confirm that my bluffs are transparent and my folds are pathetic. Sure, analyze my opponent’s ‘strategies’—meanwhile, I’ll just keep donating my chips like a charity for lucky amateurs. Maybe next time it’ll predict how fast I’ll go broke. Spoiler: not long.”*

Mia Garcia

“Wow, another ‘genius’ tool to read minds at poker? Please. If it worked, we’d all be rich. Just fold when they smirk—saves time.” (113)

Daniel Brooks

Dude, if you wanna crush it at poker, you gotta stop guessing and start predicting. Every hand tells a story—bet sizing, timing, even how they stack chips. Weak players follow patterns like clockwork. Spot ‘em early, exploit ‘em hard. Don’t overthink it; most regs are predictable once you know their leaks. Tight? Punish their blinds. Loose? Trap ‘em with value. Aggro? Let ‘em bluff into your monsters. The trick isn’t memorizing stats—it’s seeing the small stuff others miss. Folded to them on the button? They’re raising 80% of the time. Called three streets? They’ve got it or they’re terrible. Pay attention, take notes, and hammer their mistakes. Poker’s not about being the smartest—it’s about being the one who adjusts fastest. Stop playing cards; start playing players. That’s how you win.

Olivia

*”Oh honey, you really think your little HUD stats and preflop charts make you some kind of poker clairvoyant? Please. How many of you actually *watch* the table instead of just waiting for your turn to click buttons? When was the last time you adjusted your ‘strategy’ mid-hand because someone’s bet sizing screamed ‘I have air’ or ‘I’m terrified of the river’? Or—god forbid—you noticed a player sighing before bluffing for three hours straight? Spare me the ‘GTO-approved’ speech and tell me: what’s one tell you’ve exploited this week that no algorithm could ever catch? (And if your answer is ‘none,’ maybe fold pre.)”*

**Male Names and Surnames:**

*”Hey guys, ever notice how some players seem to read your mind at the table? Like they always know when you’re bluffing or folding. Do you think these prediction tools actually help spot patterns, or is it just luck? I’ve tried a few, but sometimes they miss obvious tells—like when a guy suddenly bets big after checking twice. What’s your take? Anyone else feel like the real skill is still in watching the opponent, not just the stats?”* (298 символов)

FrostWarden

Hey everyone! Ever had that moment at the table when you just *know* what your opponent’s next move will be, but you’re not sure how to use it? Like, their betting pattern screams “bluff,” but you hesitate—what if you’re wrong? How do you turn those gut feelings into cold, hard chips? Do you guys ever catch yourselves overthinking reads? Like, you spot a tell—maybe they take longer to call when weak—but then doubt creeps in: “What if it’s a trap?” How do you balance trusting your instincts with the math? And what about those players who switch gears out of nowhere? One hand they’re tight, the next they’re shoving like there’s no tomorrow. How do you adapt without second-guessing every decision? Would love to hear your stories—when did predicting someone’s strategy click for you? Was it a specific hand, or did it come from grinding through tons of games? Let’s swap some tricks!

James Carter

Predicting opponents’ moves isn’t just about math—it’s about reading patterns, exploiting weaknesses, and staying two steps ahead. Every bet, fold, or bluff reveals something. The key? Discipline. Track tendencies, spot deviations, and adjust before they do. Weak players repeat mistakes; strong players force them. Don’t just react—anticipate. If you’re only thinking about your hand, you’ve already lost. Focus on theirs. The best players don’t rely on luck—they engineer it. Crush predictability, and the table becomes yours.

Emma Wilson

Oh, so you wanna crack your opponent’s poker face like a cheap safe? Cute. Here’s the tea: if you’re still relying on “gut feeling” to call bluffs, you might as well fold now and save us all the secondhand embarrassment. Predictors aren’t magic—they’re glorified gossip about how someone bets when they’re sweating over a pair of twos. Spot the patterns, sure, but don’t get cocky. That “tight-aggressive” shark you’re profiling? Probably just some dude who watched too many highlight reels and now overbets like it’s a personality trait. And the “loose-passive” fish? Might be a trap. Or just drunk. Either way, if you’re not adjusting faster than they’re regretting their life choices, you’re just another sucker paying for their vacation. So go ahead, crunch those numbers—just don’t cry when they suddenly start bluffing like they’ve got a PhD in chaos theory. Poker’s not math, darling. It’s psychological warfare with chips.

Gabriel

“Wow, another magic crystal ball for poker? How many times have you actually seen these ‘predictors’ work when some drunk whale shoves all-in with 7-2 offsuit? Or is this just fancy math to justify bad beats?” (224 chars)

PhoenixSoul

Girls, I’m so curious—how do you even keep track of all those poker faces at the table? Like, do you have a little mental checklist for spotting bluffs, or is it just pure gut feeling? My husband swears by “tells,” but half the time I’m too busy trying not to giggle when someone does that dramatic eyebrow twitch. 😂 And what’s your take on those apps that claim to predict moves? Sounds fancy, but I’d probably forget to check it mid-game while reaching for my wine. Seriously though, do you think memorizing patterns actually works, or is it better to just wing it and hope for the best? Spill your secrets, ladies—I need all the help I can get before our next game night! ♠️♥️♣️♦️

NovaStrike

“Hey everyone! Those of you who’ve tried poker prediction tools—how much do you actually adjust your play based on their analysis? I’ve noticed some opponents adapt instantly when they sense you’re using stats against them, while others never catch on. Do you think these tools work better against certain player types, or is it more about how you apply the data? Curious to hear your experiences.” (424 chars)

RogueStorm

Predicting poker moves isn’t just about crunching numbers—it’s reading people. The best players spot patterns, not just in bets but in hesitation, timing, even how someone stacks chips. Tools that analyze strategies can help, but they’re no substitute for paying attention. I’ve seen guys rely too hard on software, missing the human element. A tight player suddenly raising? Maybe he’s bluffing, or maybe he’s finally got the nuts. Data might hint at it, but your gut confirms it. The trick is balancing stats with instinct. And let’s be real—predictors work until they don’t. Opponents adapt. What worked last week might backfire today. The real edge comes from mixing cold analysis with old-school observation. Watch the table, not just the screen. At the end of the day, poker’s still a conversation. The best “predictor” is staying sharp enough to listen.