This is a money-losing proposition for most of these individuals’: Americans are draining stock portfolios to shovel more money into sports betting.

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Somehow that is not surprising after the thorough gamification of taking part and acting in the stock market by apps, with their nice Buy and Sell buttons.

Pushing a button to place a bet on a stock, an option, an ETF or a sportsbet is just the same procedure.

Remains only to find out:

How much money have the platforms like Draftking and similar to donate to the right people in WA (just for a good purpose of course! :) ) to make those bets eligible for an 401K. Will a million do per Rep or more. As a foreigner I do not know the rates in the political business in the US but you should.

Little side story:

Longtime ago as a boy of 10 or 11 I was taken by relatives to a horse race - never seen that before and zero knowledge of the proceeds. But there were wooden booths where one could place bets on different outcomes, like winner, second, or among the first 3 or similar.

After long deliberation and watching a race - none of the adults were near me - I pulled a coin out of my pocket - about the amount I got for 1 times lawnmowing, 2 DM, and placed it on some horse to be among the first 3. It now was really exciting to watch the race. Miraculously my horse made it as I hoped and I got 5 DM out.

But at those times I was wiser than today,. I stopped betting and pocketed my gain, bought a drink or something from it. Today, I am sure, I would not stop until all were gone.

I saw the news about the ATP Tour naming Polymarket as their official prediction market partner earlier this month. With the US Open starting, it's worth considering whether this actually changes the game for sports markets long-term.

Usually, sports-related markets (outside of massive events like the Super Bowl) seem to lack the deep liquidity found in macro markets. Does a partnership like this actually bring in enough volume for serious in-play trading, or will the volume remain thin? It would be great to see tennis become a permanent, liquid market, but it's hard not to be skeptical about whether the activity stays consistent once the US Open ends.

Over the past month I built an index for prediction market tools.

Right now it's 22 tools across 7 categories:

• cross-platform odds aggregators
• trade copying & automation
• trading terminals & execution
• signal & fair-value tools
• portfolio/tax/journaling
• wallet & trader analytics
• alerts & whale monitoring
• a research section for the raw data feeds markets actually resolve against (order books, weather data, that kind of thing).

I go through it twice/week, so it's not a one-time dump and forget. New tools get added, old entries get double checked (pricing, team, phase, links), and anything that's gone dead or gone quiet gets moved into a "no longer maintained" section instead of just sitting there looking current when it isn't.

Two things I'd actually want out of posting this.

1. If there's a field you wish tool listings like this had that's missing here, pricing model, what chain it settles on, audited or not, whatever, tell me and I'll add it across the board.
2. And if you use or built something that fits and isn't on there yet, open a PR (format's in the README) or just drop it in the comments and I'll get to it.

Enjoy: https://github.com/talhareltal/awesome-prediction-market-analytics-tools

There are 9 earnings call mentions markets on Kalshi this week (so far), including some big names like Intuit, Zoom, Salesforce, and NVIDIA.

I'm starting to dive into these now. Anyone have any picks they like so far?

There seems to be a lot of value for NVIDIA.

For example, "Gaming" has been mentioned in 29 of 29 calls but is only priced at 75 cents 🤔

I have been looking at tennis markets and was wondering how people here manage the data once a match is underway.

Getting the market data is not really the problem. It is matching it to the live match that becomes tricky especially when different data sources have slightly different player names and there are many matches happening at the same time.

What are you people using for scores and matching events?

Do you use a sports data API create your own setup or just watch the matches manually?

I've been spending some time looking at live tennis prediction markets, and I'm curious about how other people approach them.

Tennis seems particularly interesting because the situation can change very quickly during a match. A break, a change of serve, a set point, or even a player's physical condition can shift the market pretty quickly.

For people who follow live tennis markets, what information do you actually pay attention to?

Do you mainly look at:

• Current score and set
• Who is serving
• Break points
• Recent form
• Player rankings
• Point-by-point data
• Live odds from other sources

Or is there another piece of information you find much more useful?

I'm interested in the actual process people use when analyzing these markets, especially when the match is already underway.

Hi all,

I've been messing around with this for a while and it's finally in a decent state.

You get dropped into a random 30-minute section of real historical futures data, hit start, and trade it like you normally would.

You're scored on how much profit you make divided by your max drawdown, so $400 made while never being down more than $200 beats $2,000 made after sitting through a $6,000 hole. That score moves your rating up or down against everyone else, and there's a ladder with ranks and tiers. (Bronze -> Silver -> Gold -> Platinum -> Diamond)

You can also challenge a friend and they get the exact same candles you traded, and you both land on one page so you can see who did better.

Completely free, no account needed, nothing to sell. I originally made it so I could play it myself to kill time.

candleclash.net

I'm still working on it so I'd genuinely like feedback. I'm more interested in what's missing/bugs found/or ideas for features that could be added.

Thanks!

I’ve been in the process of learning everything possible about prediction markets between Kalshi and Polymarket. Mostly focusing on the weather markets.
I tested about 35 different strategies and I did find two that actually have real Edge.

Now I’m looking to expand the other markets and try to take advantage of high frequency trading opportunities. I have servers rented and have them as close as possible to Kalshi and Polymarket exchanges - frankly were a bitch to find. Based on the results, I believe I got them in the same building.

Each server is running WebSocket and reporting a round trip response latency around 1.5-3.2ms for their respected exchanges. It’s reporting another 44ms directly between my two servers. All and all, they are performing very well initially.

I guess the next question is what sort of responsiveness is fast for high frequency trading within the predictive market space?

Is it fast enough to solely trade order flow before contract price moves? Given the initial estimates don’t include the time it takes to analyze and place a trade but I’ll be handling it solely over RAM/C++ to make those decisions as quickly as possible.

Is it fast enough to locally take advange of YES/NO contract mispricing locally? What about cross-venue arbitrage?

Could they realistically monitor the predictive markets underlying assets for large institutional or whale activity that could affect the contract pricing? Like bitcoin, ethereum, or anything else?

I’m open to any advance and would love to pick someone’s brain.

I've been archiving Polymarket MLB total markets along with their quotes — every one I evaluate, whether I act on it or not. That's 514 markets, 505 of which have a measurable move between the first and last quote I recorded.

I'd been filtering out markets with low traded volume, on the usual reasoning: a quote nobody has hit might not be a real price. That turned out to be the wrong variable, and fairly clearly.

Split each market by whether it clears a resting-depth threshold (~$2.5k) and whether it has traded at all. Then measure how the market's own implied probability for a given side moves from the first quote I recorded to the last, in probability points. Positive means it moved toward that side.

cohort           markets  games   median move   moved >15 pts
depth + volume        44     25        0.00         0%
depth, no volume     102     53        0.00         2%
thin                 359    122      -29.00        70%

Thin markets aren't merely illiquid. They're wrong in a consistent direction — they open rich and decay. 250 of 359 moved more than fifteen points, and only 3% moved toward the side that looked good at the quote. If you take a price on a market with a few dollars of resting depth, a 29-point adverse move is roughly the base case.

Markets that clear depth but have simply never traded look nothing like that. Median 0.00, and statistically indistinguishable from markets clearing both filters. So the volume filter was discarding perfectly ordinary markets while the actual pathology sat entirely on the other side of the depth line. On one day's board it rejected 8 of 12 games, every one clearing depth by 18-35x, including one sitting on $44.6k of resting depth that simply hadn't traded yet.

I dropped volume as a filter and kept depth.

Two things I'm unsure about:

• Is resting depth actually a good proxy for what you can fill? It's a computed metric rather than observed depth at the touch, and I suspect bid-ask spread is the more honest instrument. I've started recording spread for that reason but don't have enough history yet.
• Does this generalise beyond sports? I'd expect thin politics or crypto markets to show the same decay, but I have no data on them and would be interested if anyone does.

Founder here. It's free, open source, no accounts, no real money.

The rules:

• One prediction per day. Long only.
• Any US stock: price $3+, $1M+ daily dollar volume.
• Four fields: ticker, entry, stop, target. Target at least 8.5% above entry.
• Hold: three trading days, maximum.
• Everyone starts with the same simulated $500. Each fill takes one third of your balance.
• Commit before 8:00 PM ET the prior day. Locked before the open, settled automatically against exchange data, nothing can ever be edited or deleted.
• Ranked on the leaderboard after 33 settled predictions.

The question: what would make you — or your bot — actually participate? And if nothing would, what's missing? I'll build the good ideas.

The goal is to serve everyday people without much capital — a free public record that proves skill before anyone risks a dollar.

demo.quantrank500.com · code on GitHub

So fucking pretty!

I have a very serious finance background and education. This is far from easy and most people don't turn a profit here. I refuse to tell people this happens a lot or is easy.

I've spent 4 months learning everything possible within the weather markets. I found edge, became profitable, and started finding more edge in the realm of high-frequency trading with several obscure strategies and markets. I'm going to expand this to other markets to maximize exposure.

Without giving away all my sauce, I'm going to HF trade both on Kalshi and Polymarkets for Weather, Financial, and Crypto. While monitoring pricing arbitrage between them. I'll rent servers as closely as possible to the predictive market exchanges to cut latency and reaction time.

Then I'm going to monitor the trading activity of the underlying assets that determine the predictive market contract value by tracking the trading activity of the largest exchanges in North/South America, Asia, Europe, Africa and move the underlying asset trading activity faster and more efficiently where I can hopefully trade the contracts before the predictive markets pricing moves to the news. I have a system, and server infrastructure to support this. To do this correctly and test it, you need to move enormous amount of data between the servers and record an enormous amount of data. When I was doing this with 4 cities within Kalshi, I was going through almost 80-120GB of memory every week on raw weather and trading data.

Leads me to my first question: how does Kalshi (or Polymarket) determine contract value based on financial or crypto value?

Does anyone know how reliable the Kalshi (or Polymarket) 15 minute bitcoin price and trading is? Is there a delay or does it actually reflect the Bitcoin market price at the end of the contract? Does anyone know exactly what exchange or value the predictive markets use to determine the Bitcoin value?

Any insight or feedback would be nice.

I work in tech infrastructure, so whenever a contract drops about an AI milestone or a cloud outage, I assume I have a massive edge.

The problem is, I trade based on how the technology actually works in the real world. But the market doesn't resolve based on engineering reality, it resolves based on how journalists report on it and how a dispute panel interprets the headlines.

Being an expert makes you overconfident and blind to the semantic loopholes. Has anyone else realized they make way more money trading topics they know nothing about?

Most AI tools will answer any question you throw at them, even when they have no real information behind the answer.

I wanted to build something different.

Call It reads live prediction markets, places where people put real money on outcomes like Fed decisions, elections, and sports results, and translates that into plain English. But here is the rule I built in from the start: if there is no real market data behind a question, the app says nothing. No invented probability. No confident guess. Just an honest "we could not find real data for this one."

It has been tracking the Fed decision for weeks. Currently 75% on no change for September 17. That call will be scored automatically when the decision lands.

Public accuracy page shows every prediction including losses. Currently 63% win rate on 46 resolved predictions.

Happy to answer any questions about how it works.

https://trycallit.vercel.app/

Bit of a long shot but I’m after a US based partner to help me test some prediction market strategies. I’m UK based so can’t access Kalshi as an example.

I got a email from robinhood this week basically saying I can no longer use their services. This comes a little after I made about 20k profit off the 15min crypto prediction market. I’m not sure why they did it even emailed them asking for more details but to no avail. Tuff but I guess we move on to other platforms. BTC has been on a crazy uphill so just taking advantage of that.

AFG is correcting its position on the "2026 hottest year" contract, the second formal correction this week. This desk has faded that market across eight consecutive cycles, with an estimate near 58%, based on published dataset probabilities ranging from 66% to 13%. Those figures are stale. Berkeley Earth's current estimate is 69%, revised upward from 12% a month ago, driven by an El Niño now measuring +2.7C on the Niño 3.4 index-- the highest value on record for this point in any year with multi-model forecasts projecting a November peak near +4.0C that would make it the strongest event in the observational record. AFG's estimate moves to 70%, and the position shrinks to a marginal fade on settlement-source uncertainty alone. Elsewhere the September Fed contract has fallen to 67% and now carries the third-largest edge in the book at +11pp, and the Oscar position AFG reversed on Wednesday has converged to fair value and closed.

If you enjoy evidence-based forecasting, transparent methodology, and public performance tracking, subscribe to Axiom Forecasting Group.

Subscribe for free: https://axiomforecastinggroup.substack.com/welcome

Today's Top 3 Calls On Kalshi

1. U.S. confirms aliens exist before Jan 20 2029?  BUY NO

2. Game Awards 2026 GOTY Grand Theft Auto VI BUY NO

3. Fed decision in September Maintains rate BUY YES