The most advanced in-play over/under detection engine, built for specialists
If totals are your niche, this is your unfair advantage. Our algorithm does one thing — detect +EV over opportunities in-play — and does it better than anything else.
Sound familiar?
Saturated niche, thinning edge
Over/under is one of the most popular tipster niches. More tipsters means more competition and subscribers become harder to retain without a genuine, demonstrable edge.
Data analysis is time-intensive
Proper over/under analysis requires processing team stats, xG data, weather conditions, squad news, and live match flow. Doing this for 10+ matches daily is exhausting.
In-play timing is everything
The difference between a +8% EV signal and a -2% EV one is often just 3-5 minutes. Manual in-play detection can't consistently capture the optimal entry point.
Here's what changes
Our entire algorithm is purpose-built for over/totals markets. Not match results, not BTTS, not correct scores — exclusively in-play overs. This singular focus means deeper optimization, better probability modeling, and higher hit rates than any generalist approach.
What you get
Purpose-built for your niche
We don't spread thin across 50 markets. Our model optimizes for one thing: detecting +EV over opportunities in live football. Specialization wins.
Pre-calculated EV on every signal
Each signal includes exact expected value, true probability, and odds — so you can verify and communicate the math to your audience.
Niche authority content
Use our performance data in your content. "71.3% hit rate on in-play overs" is a powerful credential for an over/under specialist channel.
I've been an over/under specialist for 3 years. The feed catches opportunities I miss because I can't watch every match. My hit rate improved from 64% to 72% after integrating it.
Common questions
Do you cover under markets too?
Our algorithm specializes in detecting over value, which requires different modeling than under detection. We stay focused on what we do best.
Which goal lines do you signal on?
Primarily Over 0.5 through Over 3.5, with the majority on Over 1.5 and Over 2.5. The specific line depends on the live match state.
How does this compare to xG-based models?
xG correlation is one of many inputs. Our model also incorporates real-time momentum, tactical state, substitution patterns, and market movement — a multi-factor approach.
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