SDQL System #002

ByTom Herbert Hours Published on Hours Last Updated on
SDQL System #002

NCAAFB SDQL SYSTEM #002 – (NCAAFB)

ProcomputerGambler

THE RESULTS:

Current Season Record: 1-0-0 (100%) ATS
(Last Updated 9.20.2011)

Long Term Results: 56-26-0 (68.3%) ATS
(Last Updated 9.20.2011)

NCAAFB SDQL SYSTEM DESCRIPTION:

Keep this in one in your back pocket. It’s based on four parameters, and simple concept: Since 1980, College Football teams that just rolled at least two opponents…both of the wins by at least by 4 TD margin are 56-26-0 (68.3%) ATS when they face a team that just gave up at least 5 TD’s worth of points. Type, “and season” to see how this has done recently. It has been hot (up to 87.5% 30+ sample size).

[SDQL LINK]: “A and opo:points>=35 and p:margin>=28 and pp:margin>=28”
The sdql database offers powerful insights for sports bettors looking to maximize their strategies. By analyzing trends and historical data, you can identify profitable betting opportunities that might otherwise go unnoticed.

ACTIVE TRENDS (9/17):

STANFORD -8.5 WINNER

[EDIT] Week 3 went 1-0-0 ATS

ADDITIONAL READING:

Read this supplementary article to help you understand the main premise: Evidence of lucrative Momentum

Access the Full Dataset and Systems

The examples shown here are drawn from a much larger dataset that tracks market behavior, system performance, and edge development over time.

If you want access to the full structure behind these results, including daily updates and documented performance tracking, you can review the available options here:

View Full Access Options

How This Fits Into the Market

Process & Proof

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Tom Herbert is the founder and lead analyst of ProComputerGambler, where he has published sports-betting research since 2010. His work focuses on SDQL betting systems, historical database testing, sample-size discipline, ROI, p-values, line value, market context, Closing Line Value and transparent long-term performance reporting.

Tom earned a four-year degree in Industrial Design with a minor in Computer Science Engineering from the University of Illinois Urbana-Champaign. He previously worked with Joe and Ed Meyer of SportsDatabase.com, the founders of SDQL, as a specialized SDQL researcher and sales partner.

His published approach treats betting systems as research signals rather than prediction machines and emphasizes exact query disclosure, market logic, statistical limitations and documented results rather than hype-based “lock” claims.

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