26 Final 23 38 Final 61 13 Final 20 30 Final 24 34 Final 6 31 Final 34 34 Final 41 16 Final 35 19 Final 16 38 Final 35 14 Final 28 28 Final 31 38 Final 45 14 Final 42 24 Final 20 13 Final 6 20 Final 59 49 Final 51 23 Final 52 24 Final 37 38 Final 17 24 Final 25 28 Final 27 20 Final 35 10 Final 21 24 Final 27 56 Final 21 31 Final 39 24 Final 31 20 Final 31 49 Final 39 10 Final 13 23 Final 15 10 Final 28 17 Final 34 49 Final 27 17 Final 28 20 Final 24 21 Final 14 13 Final 28 31 Final 35 0 Final 26 31 Final 10 49 Final 56 20 Final 16 24 Final 57 32 Final 38 3 Final 39 17 Final 20 7 Final 24 27 Final 34 17 Final 34 31 Final 30 42 Final 19 16 Final 21 13 Final 21

How We Approach College Football Research

By · Last updated

Blue Chip Analytics treats college football analysis as something to be examined rather than protected: we publish the data, assumptions and models behind a result so another analyst can repeat the process and reach the same conclusion, or identify where they disagree. Every study states its sample explicitly - the market-efficiency work runs on 3,616 FBS games from 2021 to 2025 - and distinguishes what the data shows from what we infer and what remains uncertain. For readers and fellow analysts, this page is the standard to hold our research to.

Open to examination

College football analysis should be open to examination, not protected from it.

Our aim is to make the data, assumptions and models behind our research as transparent as possible. A result is more valuable when another analyst can understand how it was produced, repeat the process and reach the same conclusion-or identify where they disagree.

Replicable by design

That means our work should be replicable. We will explain the sample, define the measures we use and distinguish clearly between what the data shows, what we infer from it and what remains uncertain.

In practice that is why every piece of research here closes with its sample size, its window, and the caveats that come with them, and why the inputs behind the ratings are set out in our methodology.

Challenges are encouraged

Challenges are not merely accepted; they are encouraged. If a result looks wrong, a method feels questionable or an explanation does not convince you, tell us. A frank exchange of ideas is one of the best safeguards against becoming overly attached to a theory.

When we get something wrong we say so and fix it in the open, under our corrections policy.

College football is noise

This matters because college football is noise. Short seasons, uneven schedules, changing rosters, extreme scorelines and a relatively small number of games create enormous variance. That unpredictability is part of what makes the sport unique. It is also what makes analyzing it difficult.

The purpose of this research is not to eliminate uncertainty or manufacture definitive answers. It is to separate genuine signals from randomness as carefully and honestly as the available evidence allows-and to remain willing to change our minds when better evidence arrives.

Sources

Editorial Standards

Methodology

Frequently Asked Questions

What are Blue Chip Analytics' research principles?

Transparency, replicability and openness to challenge. We explain the sample, define the measures, and distinguish clearly between what the data shows, what we infer from it, and what remains uncertain.

Can I reproduce your results?

That is the aim. Every piece of research states its sample, its window and its caveats, and the inputs behind the ratings are set out in the methodology, so another analyst can repeat the process and reach the same conclusion - or identify where they disagree.

What if I think a result is wrong?

Tell us. Challenges are not merely accepted, they are encouraged. A frank exchange of ideas is one of the best safeguards against becoming overly attached to a theory, and when we get something wrong we fix it in the open under our corrections policy.

Why is college football so hard to analyze?

Short seasons, uneven schedules, changing rosters, extreme scorelines and a relatively small number of games create enormous variance. That unpredictability is part of what makes the sport unique, and it is also what makes separating signal from randomness difficult.

College football is noise, and the purpose of this research is not to eliminate uncertainty but to separate genuine signal from randomness as honestly as the available evidence allows.