Commander.Ted

We’ll be publishing an official Looking Ahead update on all things TED soon. Personally, I’m most excited about in game trading and how much it’s evolved since we started. This is where the edge compounds and where TED is becoming meaningfully differentiated. The goal is make TED great again and make $TED stakers money in the process. Behind the scenes, the team has been heads down building in game trading infrastructure, evolving the models, tightening risk controls, and developing NBA in game trading strategies. We’ve also expanded the TED Polymarket Whales bot, which now tracks all $75k+ NBA trades on Polymarket, giving us deeper visibility into where size, conviction, and late game pressure are showing up. @TheAgentTed @polywhaleswatch As Always in TED we TRUST!

@TheAgentTed Tech improving

TED × Polymarket Whales Bot This week we launched NBA for TED’s whale bot that monitors large-size Polymarket flows ($75k+) to better understand how capital actually moves in prediction markets. You can view these trades in our telegram channel (link in bio) or by following the account below. In TED we TRUST

Most prediction market frontends are just: “a list of questions.” That’s not a consumer product. That’s a database. The next PM winners look more like Spotify/TikTok: a personalized feed that routes you to markets where you actually have an edge. Truth needs distribution

@browomo This is described incorrectly

The question of whether Polymarket will ban bots is not what you should be thinking about. The right question is how one Python bot manages to make $736K a week. I'm talking about the wallet SeriouslySirius. Its stats look like a glitch in the matrix 400K% ROI and over $3.8M in net profit. <> His profile: @SeriouslySirius?via=roovxKu" target="_blank" rel="nofollow noopener">polymarket.com/@SeriouslySiri… Here's how it works. There's no magic or gut feeling for picking winners. It's pure math and algorithms. The secret behind the strategy: It doesn't guess outcomes. The bot doesn't try to figure out who will win. It trades price differences. Only liquid markets. NFL and NBA. Huge volumes there so you can enter a $500K position without crashing the market instantly. Vegas as the benchmark. The bot is tied to Vegas bookmaker lines not to crowd emotions on Polymarket. Catching lag. This is the real juice. When a Vegas line moves by 0.5 to 1 point Polymarket lags for a few minutes. The bot sees this movement before everyone else and jumps into the trade while the platform price hasn't caught up yet. This gives 3 to 8 cents of guaranteed profit per dollar. Buying underdogs. If the crowd overvalues the favorite the bot buys the underdog below 50 cents and just waits for the market to correct the price. Will it get banned? Probably not. The bot doesn't break the system it makes it more efficient by adding liquidity. Essentially this is not a gambler but a high frequency hedge fund operating on sports events. This is an example of how Python code and understanding market mechanics beats any expert analysis. Copying this manually is almost impossible because you simply can't keep up with the robot in those 2 to 3 minutes when the opportunity window opens. But the logic itself of looking for price mismatches relative to Vegas is a solid approach. Tracking wallets that repeat this execution pattern is easier with @PolyCop_Trader

@ArchiveExplorer Seems like narrative fluff. Even if the bot parses game state quickly... polymarket prices dont update per kill so he would need someone to trade against in sufficient size

Another bot trading live markets made $230k on just $950 deposit and that's only in 3 months focuses exclusively on esports bot monitors live game in real-time parses data faster than people when kill, objective, fight happens checked his deposit and withdrawal history on @BullpenFi ( 0DB66F ) example: CS2 match bot sees the kill before crowd enters position immediately 5-10 seconds later crowd reacts → profit locked profile: @TeemuTeemuTeemu?via=archive" target="_blank" rel="nofollow noopener">polymarket.com/@TeemuTeemuTee…

@carverfomo @PolymarketTrade So he picks up the pennies in front of a stream roller. What could possibly go wrong?

A GitHub bot with thousands of lines of code turned $333 into $3.8M on Polymarket in 6 months. $532K/week pace. swisstony didn’t get lucky. The same routines just kept cycling. What it actually does, in plain words: It buys NO at 99 cent when the outcome is basically locked, then waits for the $1 payout. Tiny edge, repeated with size. Sometimes two related markets disagree for a few minutes. The script buys the side that’s clearly too cheap and sells once prices snap back together. Why sports works: news hits late, crowds overreact and liquidity is deep enough to cycle thousands of small trades without moving the market. This is why the curve looks unreal. It’s not one bet. It’s repetition. → No - Arsenal vs Liverpool polymarket.com/sports/epl/gam…

@goatyishere @Polymarket These kinds of trades are picking pennies up in front of a steam roller. He's buying @ 99c right before the market resolves. Wouldnt say thats really much of a strategy. One trade can wipe out his entire account

This cheat bot doesn’t even know what a loss is on Polymarket! 99.4% Win Rate Profile: @Sharky6999?via=goaty" target="_blank" rel="nofollow noopener">polymarket.com/@Sharky6999?vi… This bot turned $17 into $479,101 in just one year! That’s absolutely insane! A 99.4% win rate across 19,387 trades it literally never makes mistakes. I’ve never seen results like this before The bot works not only on standard 15-minute BTC/ETH markets, but also on sports and esports bets Just imagine: while you’re guessing whether the price will go up or down, some guy has written a script that prints money every single day without errors or downtime I’ve already added it to my watchlist!

@k1rallik Looked through the actual fills. This isn't arbitrage, its market making on thin books, especially late in matches looking to capture wide spreads when liquidity thins out. This carries a ton of inventory risk and does not rely on Yes + No < $1 or speed. The edge is the spread.

Bot Makes $100k A Day On Sports Most traders are placing bets. RN1 is running code This bot printed a Lambo in cash in a ONE week - Week: $408k - Month: $1M - Total: $3M No predictions. No opinions. Just ruthless execution and speed you can't match by clicking buttons Here's how it actually works: 1) runs pure arbitrage. The math is simple: When YES + NO < $1, buy both sides 2) pays for institutional feeds like Sportradar that deliver data seconds before your TV broadcast While you wait for the stream, the bot executes trades in milliseconds via API, front-running the entire market Sounds easy? It's NOT The strategy is simple. The execution is BRUTAL Vibe coding on Claude won't cut it. This requires real engineering this profile: @RN1?via=sales" target="_blank" rel="nofollow noopener">polymarket.com/@RN1?via=sales

@nursexxl @St_STEIN_ @Argona0x @PolymarketTrade This is only on the taker side for crypto price markets

@St_STEIN_ @Argona0x @PolymarketTrade linear fees on 15m markets on polymarket

just bought claude code to make $1m on polymarket someone made $75k in january with an alert bot that tracked unusual wallet movements market makers are pulling $700-800 per day with basic automation i'm building both setup is simple: → alert system catches whale movements and new wallets making big bets → market making bot provides liquidity on both sides and earns spreads claude code writes the entire thing i don't need to be a programmer, just describe what i want and it builds it polymarket processed $3.7 billion last year bots extracted $40 million in profits the top traders are already automated literally anyone can do this now $20 subscription, some time, and discipline this is either $1m or a really good learning experience either way i'm doing it

@ArchiveExplorer Math is not mathing here

These bot make $15-50k per month on polymarket bot analyze fights in real-time and place bets before crowd reacts every punch and moment makes a big difference it uses computer vision to analyze the fight detects events and processes at 50 FPS with ~200-400 ms latency predicts outcome before market reacts example: Joshua vs Paul fight bot sees Joshua landing heavy punches while crowd hasn't reacted yet odds unchanged bot immediately buys Joshua win 10-15 seconds later when crowd reacts, it sells bot architecture: - Forecaster - evaluates event probability using visual data - Critic - identifies missed context - Trader - makes buy/sell decisions and position sizing to create such a bot you need access to direct video feed of the fight not TV broadcast, but YOLO v8/v9 for real-time detection OpenCV for video stream processing GPU acceleration is critical for low latency UFC events on Polymarket roughly 8-12 per month with that volume the bot could easily make up to $50k

@big_duca relatable

Being a founder is really tough. Bc your to do list only grows in size. And if you take a day off. Even a holiday. It means that days work is transferred to another day. Which is already overflowing with stuff. So you just simply don't take off.

@itsmaximilian Prediction markets aren’t better forecasts. They’re better early warning systems for when consensus is about to fail.

Prediction markets are positive sum. Pearl clutchers can cry about it but this sector isn’t slowing down and it will be net good for the world.

@thenarrator Front doors win by lowering thinking cost, not click count

the prediction markets aggregator wars is officially heating up. everyone wants to be the front door: more venues, more data, more abstraction. winners won’t be the loudest, they’ll be the ones that actually reduce friction.

In short PMs aren’t better forecasters they’re better at detecting when the old forecasting framework is breaking

Just read through the new 1st Kalshi Report and honestly it seems like everyone’s focused on “prediction markets beat CPI consensus.” That’s not the insight. The insight is that PMs don’t win by being faster. They win by aggregating weird, fragmented, non-modelable information that surveys can’t touch. That only matters when structure breaks. research.kalshi.com/articles/crisi…

One thing that changed how I see sports betting: When sportsbooks adjust odds, they frequently settle on the same numbers across operators. That doesn’t happen in markets driven by deep, independent models. It happens when pricing is built to manage risk, not understand the game.

@PantherQB19 @TheAgentTed IYKYK

While the public sat on Philly, @TheAgentTed was razor sharp on LA 10,000 $TED (~$19 USD) gets you access to all his picks What are you waiting for?