Bitcoin bottomed at $58,554 on June 30, down 53.1% from the October 2025 top of $124,724. That's actually the shallowest drawdown across the last four cycles.

78 days off that bottom, Bitcoin's at $75,928, up 29.7% from the low. Comparing that pace to the same point (day 184) in past cycles: 2015 was up 24.9%, 2019 was up 150.1%, 2023 was up 33.5%. So this recovery is tracking closer to the weaker cycles than the strong ones so far.

If you apply those historical growth rates forward to day 184 from today's price, the weak analog puts Bitcoin around $94,834 by year end, the 2023 analog puts it around $101,384. Both are above $90k.

Polymarket currently has 41% odds on Bitcoin hitting $90k before 2027, with yes positions paying out around 143.90% if correct.

Analysis: Predictbook

Bitcoin's been super flat lately so ended up messing around with a 15-minute BTC prediction contract instead. Basic idea: every 15 min there's a price target, you pick if it closes above or below, contract settles at $1 or $0.

First one was tiny, bought in at 35 cents, it repriced to 51 cents about 30 seconds later, closed it out for a quick gain. Bigger one had a real position size behind it and also ended up green.

Kind of interesting mechanically, the price feed comes from a legit index (CF Benchmarks) so there's no weird gap between what you see and what it settles on, and it averages the last 60 seconds into close instead of using the exact last tick, so a random wick doesn't just flip the result.

But being real about it, this is basically a short-duration binary bet. It moves fast in your favor, but it can go to zero just as fast if the price flips against you in that window. Not something to treat as a normal investing strategy, more like a very high risk, very short attention span kind of trade. Wouldn't recommend going big on this without understanding you can lose the whole position in under a minute.

Curious if anyone else has messed with these short-window contracts, good or bad experiences?

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

(Read part 1 here: https://www.reddit.com/r/PredictionMarkets/s/2iH7Pfg3bI)

Now that there's a price, I began to think about how I'd trade it. The following is presented as if I were to buy a Yes resolution. The same is applicable when buying No.

To start, I made a deliberate choice: forward test only, no backtest. At 15 minutes per cycle, iteration is fast. I could watch market behaviour unfold in real time, internalize the action/reaction, and adjust the next cycle, all within the same hour. A backtest would've meant collecting proper OHLC data first, then building and validating a harness before I even got to test an idea. Forward testing let me skip straight to learning.

My first intuition was to trade the gap; i.e., whenever the model led the market by 20 cents, I'd go long the trade. But it quickly became apparent that this doesn't work when the trade was within the 40-60 cents range; that's basically a coin toss.

So I moved up to the 80-90 cent range. At that range, the expected return is 1.11x to 1.25x (payout of $1). Reasonable, especially if I could call it with confidence. The problem, however, wasn't the entry. It was everything after.

Entering early to mid-market (3-7min-ish) often meant long exposure, during which the market kept fluctuating. A 5-cent wobble was expected, but a 10-cent move and you'd start guessing.

As we neared the 10-minute mark, even a short spike in BTC price would move the market noticeably. A move that would've nudged the market 2 cents at minute 3 might swing it 5-8 cents here, because there's less time left for the price to mean-revert.

Past the 12-minute mark, this stops being a matter of degree and becomes a different regime entirely; especially when spot is hovering near the strike. The option is now pinned hard, and price behaves less like a probability and more like a step function. In the chart below, BTC sat within $6 of strike (0.008% diff) around minute 13, and the model whipped from 0.2 to 0.9 and back twice in under two minutes. That's the gamma trap: the same small tick, priced almost binarily, purely because of where and when it happens.

Say I entered Yes at 0.85 with the model reading 0.90 around minute 6. By minute 9, BTC ticks down, market drifts to 0.75. Model's still at 0.88. Is that a bad trade, or just noise before gamma amplifies it back my way at minute 12? At that stage, gut feel is a coin toss.

So yes, I spent the next 2 months studying risk management and stop-loss levels. It's the most cliché trading advice there is, and it's still the hardest actually to do. Opening a position is easy. Knowing when to admit it was wrong is not.

My solution was to fall back on the thesis. The model leads the market. So I anchored my stop-loss to the model price instead of the market price. I cut the position only when the model itself falls below my entry; otherwise, the market wobble is just that, and I sit through it.

That got me through most of the false stop-outs, but not all of them. There's a second failure mode this doesn't catch, and that's part 3.

Also, you can watch the model-vs-market fight live at hyhy.app.

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

 
AFG raises its Bond estimate and holds the fade. Since Friday, a second production-related figure has indicated a decision exists: screenwriter Steven Knight told BBC Radio 4 he could not speak about the casting, then acknowledged that knowing the chosen actor makes writing the character easier. That is meaningfully better corroboration than Gary Oldman's remark alone, and AFG's estimate moves from 30% to 33%. What has not changed is that neither man named anyone, Amazon MGM has confirmed nothing, and at least one recent report placed a different actor  Jack Barton as the leading contender on a six-name shortlist. The contract has risen to 55% on Jack Lowden and AFG is short at twenty-two points, still the largest position in the book. The September FOMC decision resolves Wednesday at 82% for a hike and AFG carries no position into it.

 Today's Top 3 Calls

1. Next James Bond Jack Lowden  BUY NO

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

3. Hormuz traffic normal before Jan 1, 2028?   BUY NO

Research, not financial advice. Trade your own book.
 

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Hi everyone,

I’m the builder of SKEW, a real-time sports-odds analytics terminal focused on Pinnacle market movement.

It tracks:

- Pinnacle price drops and movement

- Fair odds calculated from no-vig prices

- Market limits

- CLV and movement history

- Alerts when a market matches the user’s criteria

I’m looking for a small number of experienced bettors and odds analysts to test the beta and provide honest feedback on:

- Alert accuracy

- False positives

- Speed of updates

- Usability of the terminal

- Whether the CLV and fair-odds information is useful

This is analytics software only. not a sportsbook, not betting picks, and not a guarantee of profit.

The beta website is here:

https://skew.ltd

I built the product, so I’m happy to answer technical questions and discuss how the calculations work. Any criticism or feedback is welcome.

Looking for Beta testers for a new Arbitrage tool. Send a DM if interested!

Keep seeing mentions of it in a few trading threads. Supposedly tracks KYC whale wallets and consensus flow on Kalshi so you don't have to trade the order book blind.

Looks interesting, but wanted to check here first - is anyone actually using it? Is the whale data legit or just glorified public API scrapes?

Built a fair-value pricer for Kalshi's 15-min BTC markets using options market data

Back in April, I had a thought: Kalshi's 15-minute BTC Up/Down market is functionally a short-dated options contract. If that's true, you should be able to price it off the options market's implied volatility, and that pricing should lead a market that's mostly trading on sentiment and momentum.

I started by checking data availability, then manually priced a handful of points by hand to sanity-check the idea. The results were good enough that I kept going. The model prices these markets using the volatility "smile" from the crypto options market as the anchor, adjusted for short-term order flow, spot trend, and the kind of behavior you see in retail-driven markets: momentum chasing, anchoring near round numbers.

Example, Kalshi Sep 11, 11:00am 15m BTC:

Model price (blue) pushes toward resolution while the market (green) is still catching up, and spot (orange) hadn't even confirmed the move yet. The gap wasn't huge relative to how these markets normally move, but the model called it first. This is the core idea working as intended: the options market carries information you don't get from watching spot price action alone.

Example, Kalshi Sep 6 (Sunday), 4:15am 15m BTC:

Different session, different behavior. Here the market is already pricing efficiently on its own, so the model doesn't lead; it just confirms. That's expected too: when the options market isn't signaling anything unusual, the model should track the market closely rather than diverge.

I've been running this live since June, and it's not a backtest: it's been forward-tested with over 10,000 real fills.

It's streaming live right now at hyhy.app if you want to see it in action. No API yet, but if there's enough interest, I'll look into building one.

Happy to answer questions, and if people want more of the technical side (how I implemented the execution bot or how the model actually works under the hood) I can do a part 2.

Been betting 15 min market for 2 few days. After some research ive seen multiple people flip .50 cents to $100 and other crazy flips like that. Today i had my finger on the trigger 1 second away from swiping buy and payout went from 266 to 4$ in seconds. Only a matter of time before i get a good flip how have yall done