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u/Aware_Stay2054

▲ 2 r/SaaS

I accidentally turned my football obsession into a micro SaaS with 43 paying users

A few months ago I started building a side project called Pronostats⁠ because I was obsessed with one question:

“What if football predictions were treated more like a live intelligence system instead of static tips?”

So I built a platform that:

updates match probabilities every ~15 seconds

runs Monte Carlo simulations live during matches

tracks multiple AI agents publicly

recalculates probabilities after injected events (red cards, goals, etc.)

compares AI vs community predictions transparently

includes live momentum tracking based on xG, shots, possession, corners, etc.

At first it was just an experiment for myself.

Then Reddit started sending traffic. Then people started staying. Then some of them actually paid.

I launched subscriptions around a month ago and the project is now at 43 paying users (€430 MRR), mostly from organic posts and word of mouth.

Biggest thing I learned so far: people don’t care that it’s “AI”. They care that it feels alive.

The features getting the most engagement are not even the predictions themselves:

live simulations

scenario engine (“what if a red card happens now?”)

AI agents competing publicly

transparency/history tracking

I think users enjoy interacting with systems more than consuming static outputs.

Still super early, but interesting to see where it goes.

Curious if anyone else here has noticed the same shift: people preferring interactive/live products over classic dashboards?

reddit.com
u/Aware_Stay2054 — 1 day ago
▲ 2 r/saasbuild+1 crossposts

Month 1 after launching subscriptions: 43 paying users

About a month ago I finally added subscriptions to a project I’d been building around football analytics and AI.

Honestly, I delayed it for way too long because I didn’t think people would actually pay monthly for this kind of product.

Fast forward to today:

  • 43 paying subscribers
  • ~€430 MRR
  • almost entirely organic growth

Most of the early traction came from Reddit and a Telegram community I’ve been building around the project.

The project itself mixes statistical models + ML with things like:

  • live probability updates
  • simulations
  • AI bankroll strategies
  • interactive match analysis

The biggest thing I’ve learned so far is that recurring revenue changes how you think completely.

I spend much less time chasing “big features” now and much more time:

  • talking with users
  • improving retention
  • shipping small updates
  • understanding what people actually care about

Still very early, but it finally feels like there’s real momentum behind it.

u/Aware_Stay2054 — 5 days ago
▲ 1 r/roastmystartup

I’ve been building an AI platform for sports predictions.

It combines models (xG, historical data, odds, etc.) to generate probabilities and identify potential value.

There are also some content features (like AI-generated analysis), but the core is prediction.

Then I added something a bit weird:

An “AI Arena” where multiple AIs compete against each other.

Same data, same base model —

but different strategies (risk, filtering, thresholds).

Each AI runs autonomously and I track performance over time.

Users can also create their own AI and let it run.

Now I’m trying to understand:

is this actually useful

or just gambling with extra steps

or just a cool idea with no real edge

Be brutal.

https://pronostats.it/ai-arena

reddit.com
u/Aware_Stay2054 — 15 days ago
▲ 2 r/ArtificialNtelligence+2 crossposts

I’ve been experimenting with something recently and wanted to share it here.

Instead of following a single betting approach, I set up multiple strategies running in parallel:

conservative (low odds, lower variance)

balanced

aggressive (higher odds, higher variance)

value-focused

Each one:

uses the same base probabilities

evaluates the same matches

places picks automatically (virtual bankrolls)

is tracked over time

Early results (small sample, so nothing conclusive):

Balanced: +36.2%

Safe: +27.5%

Aggressive: +24.5%

Value: +20.0%

What’s interesting is that even with the same underlying model, just changing parameters leads to very different outcomes.

I’m starting to think that execution and filtering might matter as much as the model itself.

Curious how you guys approach this: do you focus more on edge selection or risk management?

u/Aware_Stay2054 — 15 days ago
▲ 1 r/PredictionsMarkets+1 crossposts

I’ve been building a football prediction platform and recently added an “AI Arena”.

Instead of a single model, I’m running multiple agents with different configurations:

risk profile (conservative / balanced / aggressive)

market selection (1X2, totals, BTTS)

minimum edge thresholds

weighting between model probabilities and bookmaker odds

All AIs:

see the same matches

use the same underlying model

place picks autonomously

are evaluated on ROI

Current snapshot:

Balanced AI: +34.4% (19 bets)

Safe AI: +26.3%

Aggressive AI: +22.3%

Obviously small sample size, but what’s interesting is how much the outcomes diverge purely from configuration.

Next things I’m exploring:

performance vs closing odds (CLV)

calibration vs raw ROI

how edge thresholds impact long-term stability

Curious if anyone here has tested multi-agent setups or different edge filters in sports markets.

You can see the live leaderboard here: https://pronostats.it/en/ai-arena⁠

u/Aware_Stay2054 — 16 days ago