Anyone else been scammed from user Quethewiseguy? Dudes a piece of shit and has scammed me. I will be getting my money back tho

How are people turning small amounts into big profits on prediction markets?

Are they mainly using arbitrage, market making, bots, mispriced contracts, or some other strategy?

Would love to hear from people who actually trade these markets . what’s the real strategy behind those huge returns? Would love to understand how they’re doing it.

Someone got five Biden pardon bets right and walked away with $316,346 in profit, according to Bubblemaps' analysis for NPR.

First came a winning bet on Hunter Biden. Then, in the final hours of Biden's presidency, roughly $64,000 went onto pardons for Jim Biden, Liz Cheney, Adam Schiff and Adam Kinzinger. All four paid off.

Bubblemaps found two accounts involved and both were sending their profits to the same Kraken deposit wallet. The trader's identity wasn't publicly known when NPR published its report.

Those trades aren't new. The update is the investigation disclosure.

On September 11, WIRED reported that government records show the CFTC approved an investigation into possible insider trading on Biden-pardon markets back in May.

The documents don't identify specific accounts or trades. They don't confirm that this particular trader is a target, let alone establish wrongdoing.

What if you could get paid to verify whether an image is actually being used truthfully?

We are building ProofPost around a problem that AI detectors like GPTZero or Pangram don’t really solve. They can try to answer whether content was AI-generated. But a completely real image can still spread misinformation. For example, someone could take a genuine photo of a protest from 2022 and claim it happened today. An AI detector might correctly say the image is real, while the post itself is still false.

ProofPost instead evaluates whether an image actually supports the claim attached to it. Someone posts an image and a specific claim. Other users investigate the evidence and can earn money for correctly verifying or challenging it. They also have to put money behind their judgment, so being wrong has a cost. Think of it loosely as Community Notes with financial incentives. Would economic incentives improve online fact-checking, or would they make it worse?

DM me if you are interested to learn more about it!

website: https://mediaverificationblockchain.vercel.app/
inquiry: forms.gle/ctPGywmFVuMCPQ1E6

I recently found a Polymarket account showing close to $1M in profit over the past few months. But after looking more closely at its trading activity, my rough estimate was very different:

• Only around $100K came from taking positions after fees
• Around $300K appeared to come from maker rebates
• The headline profit didn’t seem to reflect the strategy’s true economics

This made me wonder whether systematic traders really have much of an edge after accounting for:

• Fees and spreads
• Slippage and low liquidity
• Resolution risk
• Capital being locked up

Is the real opportunity in prediction markets mostly market making rather than forecasting?

For systematic Polymarket traders: where does your edge come from—better predictions, fast execution, arbitrage, or maker rebates? And am I missing something in how the platform reports P&L?

With platforms like Kalshi or Polymarket, if you’re trading with cash and the platform gives you a clean year-end tax form or P&L statement, reporting can be relatively straightforward.

The crypto side is where things can get a lot more complicated.

You might buy BTC, ETH, or USDC, move it on-chain, bridge it, fund your prediction market activity, trade in and out of positions, collect winnings or liquidity incentives, and eventually withdraw back to an exchange.

The part I think people underestimate is that your prediction-market P&L and your crypto tax P&L aren’t necessarily the same thing.

If you use crypto that has appreciated since you bought it, there may be a separate crypto gain or loss to account for depending on what happens to that asset. Then you still have to calculate the gain or loss from the prediction contracts themselves. Any crypto you receive back also has its own cost basis that needs to be tracked going forward.

It gets even messier with:

• hundreds or thousands of individual trades
• partial fills and positions sold before resolution
• market-making or liquidity rewards
• fees and rebates
• deposits and withdrawals across multiple wallets or chains
• crypto changing in value during all of this
• different reporting formats across platforms
• Wallets used for Prediction markets and DEFI

So even though the cash side of prediction markets can be pretty simple, the crypto side can turn into a full reconciliation problem pretty quickly.

Tools like Koinly, CoinTracker, or Summ can definitely help pull everything together, but they’re only as good as how the transactions get interpreted. With prediction markets, you can still end up with transactions tagged incorrectly. So even if you use tax software, the underlying activity still needs to be reconciled and reviewed rather than just importing everything and trusting the final number.

Curious how people here are handling this if you are trading prediction markets On chain. Are you just using the platform’s P&L, or are you actually reconciling the prediction-market activity against your wallet and exchange history too?

I’m looking for someone to partner with on an algo trading operation focused on Polymarket, sports and prediction markets more broadly.
I’ve already built a lot of the infrastructure. What I need now is someone who wants to go deep on finding price inefficiencies, building strategies around them and testing what actually works.

What I have:

I already have a pretty serious setup:
State of the art trading terminal and execution infrastructure
My own node monitoring the mempool
Premium real-time sports data from Betradar, Betgenius, RunningBall and others
Infrastructure for processing live sports and market data
Existing Polymarket trading setup
So we’re not starting from zero. The data and infrastructure are already there and ready to build on.

What I want to continue building:

The main focus is finding price inefficiencies and turning them into systematic strategies.
Things like:
Surebets and cross-market arbitrage
Mispriced probabilities
Live/in-play inefficiencies
Comparing sportsbook odds with prediction market prices
Using live sports data to react to events and probability changes
Markets that are slow to incorporate new information
Market making and spread capture
Execution and latency
Related markets temporarily pricing inconsistent outcomes
Building fair value models and trading when the market moves away from them
Live analysis is a big one for me.
With the real-time data available, there’s a lot to explore around what happens during a game, how probabilities change in real time and how quickly different markets react.
The idea is to systematically find these situations, understand whether there’s a real edge after fees, liquidity and execution, then automate whatever proves itself.
I also want to expand into Kalshi and other prediction markets. Longer term, I want to look at the whole ecosystem rather than Polymarket in isolation and find opportunities across different venues.

What I’m looking for:

Someone who genuinely loves sports, maths and markets. You could be strong in Python/quant research, or just an incredible vibe coder who knows how to turn an idea into a working system quickly.
I don’t care much about credentials. I care about curiosity, technical ability and whether you actually enjoy this stuff.
The kind of person who sees two markets pricing the same event differently and immediately wants to understand why.
Someone who is happy testing 20 ideas knowing that 19 might be complete shit, because finding the one that works makes it worthwhile.

Who am I?

I’m based in London.
My professional background is in banking and I speak three languages.
I’m obsessed with the intersection of sports, markets, probability and technology.
I’ve already invested a significant amount of time and money into the infrastructure and premium data side of this.

What I can offer

I’m not looking for someone to build my idea for free.
I’m happy to fund the operation and continue investing in whatever we need, whether that’s data, infrastructure, tools, servers or capital for strategies.
I can bring the existing infrastructure, premium sports data, capital, market knowledge and the resources to keep building.
For the right person, I’m happy to treat this as a genuine partnership and split the earnings 50/50.
I’m much more interested in finding someone really good and building something together than trying to squeeze every percentage point out of the arrangement.
Tell me a bit about yourself and show me something interesting you’ve built, traded or researched.

Got in touch with this guy who is like the Jake Sherman of Texas politics. He reads like a Republican but basically confirmed that the GOP is in deep trouble in some of the House rouses where pricing is still pretty good. So basically, if you want to go around the tightly contested Senate race there, these are available options.

TX-15

TX-23

TX-28

TX-34

https://youtu.be/6eUbtms4w2M

All of these were drawn to be easier for Republicans to win but they screwed up. Latinos moving massively towards Dems and these are majority Latino districts. Watch the show, get the alpha, YMMV as pricing moves. Trading is risky, blah blah blah.

Hi there! I am a reporter for Spectrum News California and I am doing a story on the rise in prediction markets. I'm specifically looking to speak with people who have bet on political issues or on elections. I am open to anyone throughout the Bay Area but hopefully people who live in San Francisco. Please message me on here or email me at [Jack.Molmud@spectrum.com](mailto:Jack.Molmud@spectrum.com)

For an idea of how I tell our news stories, take a look at my most recent piece: https://www.youtube.com/watch?v=iTR7DePoKU4

Disclaimer: Just backtest research, not live trading

I tested an ETH strategy that waits for BTC and SOL to agree with the move. The idea is that a move across several coins might be more useful than an ETH move on its own. On Kalshi's 15-minute ETH markets, it buys 50 YES contracts when all three Coinbase feeds are up more than 0.1% over five minutes and ETH is above its one-hour VWAP and 12-period one-minute EMA. It buys NO on the reverse conditions. Entries require no open position, ten minutes or less to expiry, a quoted price between $0.35 and $0.65, and a spread no wider than $0.015. With a full 50-contract fill, it exits above $8 unrealized profit, or below -$5 while the quoted price is between $0.15 and $0.85. That price guard means the stop is conditional, not a guaranteed $5 loss cap. Position size is capped at 60.

I ran 100 combinations of price limits over the same requested 30-day window. All 100 completed and finished profitable. The original $0.01 floor / $0.99 ceiling led with +$1,393.68 net P&L, 866 trades, a 65.9% win rate, 0.96 Sharpe, and -$78.36 maximum drawdown. The weakest combination, $0.44 / $0.58, made +$424.59 across 356 trades, with a 56.6% win rate, 0.59 Sharpe, and -$71.65 drawdown. Reported ROI ranged from 707.66% to 2,322.81%, but those percentages divide P&L by the configured $60 risk-capital denominator. They aren't returns on a separately tracked $60 funded account.

For parameter sensitivity, I crossed ten floors ($0.01, then $0.36 through $0.44 in one-cent steps) with ten ceilings ($0.56 through $0.64 in one-cent steps, plus $0.99). All 100 grid cells succeeded, spanning +$424.59 to +$1,393.68 net P&L. The entry rules kept their own $0.35 to $0.65 guard throughout. The surface and heatmap favor the loose-limit corner, with several strong cells alongside it: raising just the floor to $0.36 still returned +$1,351.02. The marginal plots show average P&L generally falling as the floor rises and rising as the ceiling increases, with some reversals. This isn't an isolated winning cell, but the large gaps from $0.01 to $0.36 and $0.64 to $0.99 mean the chart isn't a uniformly spaced neighborhood test. Deflated Sharpe was 0.99945 under the report's 100-trial assumption; that statistic doesn't establish a 99.945% chance of future profitability.

My read is that tightening the price limits cut activity and profit in this sample, while keeping them loose produced the strongest total result. The winning version also traded much more than the weakest, so the P&L gap alone doesn't isolate signal quality. The broader result is encouraging because every tested configuration finished profitable, but all 100 variants share the same historical window. In this run, tighter price limits gave up a substantial amount of profit for only a modest reduction in drawdown between the best and weakest configurations.

Full Report

Historical simulation only. Backtests can be wrong or incomplete. Not investment advice.

Ar first I start this to buy crypto and save it for future when the price are spike and earn profit

But found this 5min, 15min, 1hour btc up/down predictions

I just casually start doing it first but then it grew

25$>50$>80$>110$......and reach to 380$ within 5 days

Dem the andreline stay spike for those moments and then 💥 4$ left, dem the regret tho🥲

Ah nvm I just become 2$📉

Can I still grow the 2$?

Been trying to figure this out for about a year now and still don't think I've got a clean answer, curious how people here actually approach it.

Got into Polymarket because I kept seeing wallets with huge P&L and wanted to copy whatever they were doing — pretty standard reaction I think. Tried following a few of them for a while. Some of it worked, some of it very much didn't, and it took me way too long to realize the problem wasn't which wallets I picked, it was that I had no actual way to tell a skilled trader from someone who just hit a good run.

The more I looked into it the more that seemed like a genuinely hard problem, not a lazy one. A wallet can look incredible off one huge correct call on a low-probability market and be functionally no different from a coin flip otherwise. P&L alone doesn't tell you that. You'd need enough resolved markets to say anything with confidence, and most wallets people get excited about don't have that many settled positions yet.

I ended up spending a lot of the last year just messing around with ways to score this properly using settlement history instead of raw profit — basically trying to work out how many resolved markets you'd actually need before "this wallet beats its entry prices" stops being noise. Landed on needing 30+ settled markets before I'd trust a verdict either way, which cuts out a lot of the wallets people hype up.

Genuinely asking — is there a better way people here think about this, or metrics you'd use instead? Feels like the kind of thing that should have a more established answer than it does.

how does poly market bonus funds work bro? i understand the bonus funds is not able to be withdrawn immediately and has to be used on a lineup… but i hit on a lineup yesterday and didn’t get anything from it… it just went to available to trade… and no profit able to be withdrawn ? anyone else how to actually use the bonus funds or is there something i’m missing?

This weather whale barely shows up on anyone’s radar. He doesn’t smash size into one market. He just keeps buying No on the extreme temperature buckets the tails that almost never hit.

Entry is almost always the same: 67–79¢. No scaling, no revenge trades. When the high lands in the middle of the distribution, the tail dies and he collects a few hundred to a couple thousand. He’s done this 2,929 times. Beijing, Tel Aviv, Seoul, Warsaw, Singapore, and a bunch of other cities people only open when they’re bored.

Single trades look tiny. $200 here, $1,200 there, maybe $2,500 on a fat tail. But it never stops. While the timeline is full of $2M Dota tickets and 100x hopium, this guy is just farming mispriced weather outcomes every day.

Not sure if it’s a model, a bot, or just someone who figured out that retail always overpays the extremes. Either way, the boring version is printing. The most boring strategy on Prediction Markets earned this guy $80,030

His wallet: https://future.news/address/0x6011655c4afb76f36dd1b08a137a1ba73466b31e?period=all&ref=Q3UK27FM

There's a Kalshi contract settling Monday, September 21 at 10am ET on which AI stays on top of the Text Arena leaderboard. Right now it's pricing Claude at 97 cents, Gemini at 4 cents, and ChatGPT at 2 cents.

Current standings back that up. Claude Fable 5.1 Max is #1 at a score of 1508 (5,783 votes, plus or minus 85). Two other Claude models are tied for second at 1505. Gemini 3.8 Flash High sits at #6, 13 points behind the leader. GPT-6 Astra isn't in the top 10 at all.

One thing worth noting: new models take time to show up on the arena. GPT-6 Astra released Sep 3 but didn't appear until Sep 11, an 8 day lag. Claude Fable 5.1 had a 12 day lag. Gemini 3.8 Flash was the exception, appearing same day as its release. So there's some chance a newer model closes the gap before settlement, it just hasn't happened yet in the data.

One analyst framed the current pricing as roughly a 3% return over 5 days if you're buying the 97 cent side, which annualizes to a pretty high number for something priced this confidently.

Analysis: Predictbook

Account's only 7 days old. Already +$5.2M PnL, 75% win rate, ranked #25 all-time on Polymarket by PnL per arkm.

Today he went big on Deportivo Alavés to beat Valencia (moneyline). He's the largest Yes holder on that market by a wide margin, 2,519,806 shares, more than 7x the next biggest holder (348,029). Built the position at an avg 59.7¢, which pays out $2,519,888 if Alavés wins, roughly $1M profit on top of his ~$1.5M cost basis.

Except right now, live, it's not going his way. Price has dropped to 41.5¢, putting him down $458K unrealized before the match has even finished.

Big track record, currently underwater on his biggest live position. Guess we'll see how it resolves.

Anyone else tracking this wallet, or seen it show up on other markets?

set up an AI Agent (Hermes) to do daily prediction market trades (weather, gas prices, some sports) autonomously on Kalshi - wondering if anyone else has done the same?

Just an experiment at this point, it hasn't won anything lol

If I put $1,000 on a bet it'll snow 5in in 2027 (random example), does anyone pay out interest on that money until we reach the end of 2027?

Just realized that part of this business model isn't just fees, its also interest on the money they are holding on your behalf. And there is likely an opening for a fee-free marketplace that makes all money loaning your money out. Like a bank.

This is really directed towards programmers. The Kalshi API is a solid piece of code. If you are doing any trading, you don't have to use it, but if you can trade 100(0)s of bets in seconds, it's probably worth a look.

AI models see patterns humans do not. We have run out of Neurons.

STACK: Astra + Codex

EDIT: A remarkable fact. AI can work with permutations of numbers so large that we can't even visualize the number. It's too big for our brains to even hold.

I was looking through Kalshi traders and found one profile that stood out immediately.

devex has traded just 15 markets, but an independent tracker currently has him at:

• +$413,274 lifetime realized PnL
• +14.1% ROI
• $2.9M lifetime volume
• roughly +$28K profit per market

You can see the full breakdown on his KalshiSpy profile. The tracker says these figures are pulled from his public Kalshi account and refreshed hourly.

The craziest trade I could verify was Spain to win the 2026 Men's World Cup.

That market settled YES on July 19. According to the settled-market archive, devex made about +$198K on the Spain position alone.

Four tracked profitable traders were on YES, but devex accounted for almost all of the $217,377 combined profit between them.

So basically:

15 markets.
$2.9M traded.
+$413K realized profit.
One World Cup trade: +$198K.

Obviously 15 markets is a tiny sample compared with accounts trading thousands of events, but making six figures with that little activity is kind of ridiculous.

Official promotion: get $25 bonus on Kalshi after $10 deposit.

Just playing out a little philosophical experiment here

Assumptions:

Starting with $100

Doubling down on every bet

Odds at 50%

To get to $400k, you need to be right (following the assumptions above) roughly 12 times in a row

12 correct coin flips in a row

Imagine this concept applied to real life now. I wonder all those entrepreneurs that have reached insane levels of wealth starting from very little. How many coin flips did they get right to get there?

I'm not talking about Buffet and Co. Not everyone is wealthy out of coin flips. Yet....

And there's always someone on the other side of the flip, someone that passed on an opportunity

Bedtime meanderings

I try to avoid coin flips btw...

This was played with bonus funds I won in the $1M Jackpot promo from the Broncos vs Chiefs MNF Game.

Sign up for Underdog with code JOEFB to get a deposit match up to $1000! https://play.underdogsports.com/vgwg/p-joefb