PS @psanix

@vijn_crypto these are the times That agents not only simplified everyday life but also started earning instead of us

@mopozeuX thats true

Quant desks pay $400,000 for one reflex: pricing a bet before taking it. An MIT professor who built a billion-dollar internet company taught that reflex in one free lecture. Ten minutes in, he casually solves what risk desks charge fortunes for. His name is Tom Leighton. Co-founder of Akamai — a third of the internet's traffic runs through his company. Every year he taught MIT undergrads the course where probability turns into money: expected value. He opens with a trap. The expected value of a die roll is 3.5. No die has a 3.5. The most important number in gambling is one you will never see land. That single idea is the wall between retail and professional. Amateurs grade a bet by its last outcome. The house grades it by the average of all possible outcomes — invisible in one roll, unbeatable over ten thousand. Then the formula desks actually run: a system failing with probability p survives, on average, 1/p steps. One line. It prices server farms, disk arrays, and every "when does my losing streak arrive" question in finance. The lecture has been sitting on MIT OpenCourseWare for years. Pascal wrote the math in 1654. Casinos have run on it ever since. The formula costs nothing. Asking "what is this worth on average?" before "will this one hit?" — that question is the whole edge. Most will save this post. Few will watch the hour

@kamin00ntee Now everyone can create movie

@kamin00ntee 💯💯

@Polymarket

Everyone thinks the hardest part of trading esports is predicting who wins. I found something more interesting. You don't need to predict the winner. You just need to know which teams the market is overrating. 1. Claude analyzed 160 esports matches across Dota 2, LoL, and Valorant. The first thing I noticed was strange. When the market is extremely confident, it's usually right. 13¢ sides win ~13% of the time. 87¢ sides win ~88%. The market is actually very good at spotting obvious favorites. 2. But move toward the middle of the curve and everything changes. Sides priced at 50–65¢ won just 43% of the time. Sides priced at 35–50¢ won 58%. The market isn't bad at finding favorites. It's bad at deciding which team should be the favorite. 3. So I tested the simplest strategy possible: Buy every side priced between 35¢ and 50¢ one hour before the match. No team analysis. No player stats. No prediction model. Just the price. 84 trades. +38% ROI. z ≈ 3.0. 4. Then I asked the obvious question: Where is this coming from? Dota 2: underdogs won 35%. LoL: 41%. Valorant: 49%. Valorant matches are basically coin flips. Yet the market keeps pricing one side like it's meaningfully better. That's where the anomaly is hiding. 5. And it gets even stranger. I checked whether smart money enters before the match and pushes the eventual winner higher. 3 hours before: 55¢. 1 hour before: 55¢. 5 minutes before: 55¢. Nothing. The closing price isn't meaningfully smarter than the price from 3 hours earlier. 6. This is probably the most important finding. The market is efficient where the serious money is. Big Dota 2 markets? Sharp. Clear favorites? Sharp. Smaller Valorant and second-tier leagues? That's where the pricing starts to break. 7. The opportunity isn't necessarily "predict esports better." It's finding where the market is forcing a favorite into a match that should be much closer to 50/50. The crowd wants a favorite. Sometimes the data doesn't. 8. Of course, there are caveats. Only 160 matches. One 7-week period. Multiple hypotheses tested. And backtested prices aren't always executable in real time. If bots start trading this pattern, the edge could disappear. 9. But the result is still hard to ignore. A mechanical strategy. No proprietary model. No information advantage. Just buying moderate underdogs where the market appears to overrate the favorite. Maybe the best way to trade esports isn't predicting who wins. It's knowing when the market is wrong about who should be favored.

@polybacktests So to find something valuable now, need to analyze the past.

@0xsael I agree with u The crowd loves a narrative

@sindikitil This is a very important indicator On which millions are earned Because people do not always correctly assess the probability of events, this gives a couple of percent of profit for big players

@mahera777 @PolymarketTrade OnlyBrainNoLuck

@Kropanchik @Polymarket @PolymarketTrade @poly_data maths

@Kropanchik 😅yeah

moved to another country. Who can guess what city this is?

@mahera777 Right 🤝

@PredictWire_ @Polymarket Why do u think like that ?

Spider-Man: Brand New Day is off to an insane start: -$72M in previews — new record -$167–170M on Friday, beating Endgame's $157.5M But I still think it won't beat Endgame's $357.1M opening weekend why?? I think it's more front-loaded, with fans rushing out on Thursday and Friday And unlike Endgame, Spider-Man has real competition Nolan's The Odyssey is out now, has the IMAX screens, and personally, I'd rather watch it If Saturday hits $100M+, I think the record falls At $90–95M, Spider-Man probably falls short The odds are flipping hard throughout the day What's your call: YES or NO?

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@ninedol He has a nice strategy

@ninedol @Polymarket I think no