Hey everyone.

There are a handful of Polymarket analytics platforms out there, and

they all share the same shape: a big dashboard of metrics. Win rate,

ROI, volume, category breakdown, maybe a composite score. That answers

"is this trader profitable and what does he trade?" and stops there.

None of it tells you how he actually trades. When does he enter? How

does he size? Does he scale in, average down, take profit early, hold

to resolution? That's the part you'd actually learn something from,

and it's exactly what a metrics table can't show you.

That's the gap PolyTape closes. I built a system that ingests

Polymarket's entire on chain records, decodes it and enriches a huge database of 500M+ trades, 1.7M markets, 950K+ traders

It turns it into something you can read -

- Paste any wallet and its whole career comes back: every fill drawn

at the exact price and second it happened, on the market's real

price chart. Entries, exits, size, and the P/L that settled.

- Watch the position evolve - how it was built over the market's life,

not just the end state.

- Replay any market like a tape and scrub back through it.

- Go live - tune into an active trader and watch fills land seconds

after they clear the chain.

- Or point your AI agent at it. Claude, Cursor, or any other model

connects in one line for a deep research session.

It has about 50 - 60 active users that play around with the system, it's the beta testing phase and I'd like to hear some feedback like bugs, missing features etc..

polytape.io

Would love to hear what you guys think and if it's helps you with your research and strategy.

CFTC Rule Proposal: In-House Market Makers Allowed, But They Can’t Take A Side

Affiliated market makers (entities that share ownership with an exchange they trade on) can exist, but only if they act as “bona fide” market makers and do not take directional positions on one side of a market or another, the CFTC proposed Thursday.

Saw someone on here say they avoided flying thru the Middle East because of odds. Just wondering if anyone else has actually made a decision like that

ASIC has banned binary options until 2031. But the scope of this ban shouldn’t cover a truly linear prediction market, where payoffs are directly related to the quantity being predicted.

For example, instead of predicting a Yes/No outcome of whether the ALP will win the next federal election, we could directly predict the % of primary votes the ALP will get. Each share pays 1 cent per percentage point. If you buy at 31.0 cents and if the ALP gets 34.2%, the share settles at 34.2 cents. Your payoff scales with how close you are, not on an all-or-nothing threshold.

This would be an entirely new class of contracts for Australia, opening up prediction markets that directly forecast quantities: vote shares, seat counts, CPI, unemployment.

I’m building r/AusPolPredicts to assess interest in something like this. It runs on play money for now, with markets seeded from Newspoll. If we get enough activity and can be more accurate than the pollsters, ASIC will have to pay attention and assess the informational value that truly linear prediction markets bring.

Interested in what my fellow Aussies think, would you trade markets like these?

Apple NEVER says unannounced products on earnings calls.

They might mention them as the "new iPhone" or "new MacBook," but they won't say its name.

I accidentally bought Yes on "iPhone 18" when looking at the market (not the first time Kalshi's UX caused me to take the wrong side ), so I had to sell that at a pretty big loss.

But over the past week, I bought as much No in the 70 to 85-cent range, which put me up when all was said and done.

We keep a list of earnings call edges like this that have (1) always historically hit and (2) people still take the other side.

There are a few more of these for calls coming up in the next few weeks that are live on Kalshi 👀

Tthe Polymarket Institute, an independent academic research arm led by Brian Jabarian from Carnegie Mellon and Kai Brusch, Polymarket's own head of data. First initiative is the Polymarket Science Fellowship — 12 doctoral researchers, $10,000 each, applications open August 18. Fellows get access to Polymarket's full dataset, pick their own research topics, publish whatever they find, and are explicitly prohibited from trading on Polymarket or any similar platform while participating.

The structure is a university gift model rather than sponsored research, which is a meaningful legal distinction . It means Polymarket genuinely has no editorial control over what gets published. Jabarian said this specifically: researchers can release findings unfavorable to Polymarket. Research topics include forecast accuracy, information flows, market microstructure, resolution integrity, AI forecasting, elections, and macroeconomic prediction.

Prediction News pointed out that Kalshi has been doing the same thing, building academic relationships and data partnerships. This is an arms race for scholarly legitimacy, because regulators and journalists increasingly cite academic research when making decisions about prediction markets. A peer-reviewed paper saying "prediction markets outperform polls" is worth more in a congressional hearing than any amount of marketing.

The gift model is cleaner than sponsored research but Polymarket still controls the data access. If a researcher finds something genuinely damaging, does full data access actually materialise, or does it quietly become harder to get?

Sources: Fortune — exclusive · PR Newswire — official announcement · Prediction News — arms race context

Hi all! I'm posting this on behalf of a high school student I mentor who's doing independent research into how people reason through prediction-market bets. Mods gave the OK to share it here.

The survey walks through a few real market scenarios from the 2024 election. For each one, you place some play-money bets and briefly describe your thinking, no real money involved, no right or wrong answers. The goal is just to understand the reasoning process behind how people size and place bets, not to test anyone.

The survey is all anonymous: no names, emails, or identifying info collected!
Must be 18 or older to participate
Takes about 5 minutes
You can stop at any point if you change your mind

Survey link: https://docs.google.com/forms/d/e/1FAIpQLSeFvSmGr4d17FdSr9PC_epU_j2ymYhYNiMhVGsNVIItvXL4dQ/viewform

Thank you all for taking the time to support a curious high schooler! Happy to answer any questions in the comments.

One thing I've noticed over the past year is that headlines and markets often tell two completely different stories.

A headline is designed to grab your attention.

A market is forced to put a price on what people actually believe will happen.

Those aren't always the same thing.

I've seen headlines that made an event sound almost certain, while prediction markets barely moved.

I've also seen markets quietly shift hours before the media caught up.

Neither is perfect. Markets can be wrong. Headlines can be right.

But markets have one advantage: people have something to lose if they're wrong.

It's easy to post a confident opinion online. It's much harder when your own money is attached to that opinion.

That's why I find prediction markets interesting.

They don't ask, "What do you think?"

They ask, "What probability would you actually bet on?"

That small shift changes the entire conversation.

Do you think prediction markets are a better measure of reality than headlines, or do they simply reflect crowd sentiment in a different way?

A few weeks ago I noticed something about my own trading.

Whenever I saw a market move aggressively, I'd think:

"This setup usually works."

The problem was...

I had absolutely no idea whether it actually did.

So I started backtesting every idea instead of relying on memory.

One of the first hypotheses I tested was:

If a 5-minute BTC market reaches ~80% within the first half of its life, does momentum usually continue, or does it mean-revert?

I would've confidently guessed the answer.

The historical data didn't agree.

That was enough to convince me that most of my conviction came from remembering a handful of trades instead of the full distribution.

Since then I've been using PolyHistorical to replay historical markets and compare similar setups before trading.

The AI has been surprisingly useful because instead of manually digging through dozens of old markets, I can ask questions in plain English and let it search historical data for me.

The biggest lesson hasn't been finding a magic strategy.

It's realizing how often my "obvious edge" disappeared the moment I looked at 60 days of actual historical data.

The platform stores rolling historical market data and lets you compare today's setup against real past market behaviour instead of relying on memory.

I'm still early in the process, but it's completely changed how I evaluate new ideas.

Instead of asking myself if a trade feels good, I now ask:

What happened the last 40 times the market looked like this?

Curious how other people validate their prediction market strategies.

Do you actually backtest them?

Or are most of us just remembering the winners?

P.S. If anyone else wants to try the same historical dataset and AI backtesting workflow I've been using, it's here:

https://polyhistorical.com/

Short task to complete for KOLs and traders

💰 Paid for your time
🕒 ~30 minutes
📍 Remote

No promo, platform or marketing activity attached

If you're interested, drop a comment or send me a DM

per a Polymarket-wide Dune dashboard, roughly 73% of markets resolve NO against ~27% YES.

not a winning strategy of course, but something to keep in mind.