Compare betting lines to Power Ratings with our Line Value Calculator - factor in HFA and customizable adjustments for weather, travel and rest to identify real value.
Last updated: July 24, 2026
Games ranked by power-rating gap (closest matchups first).
| Matchup | Date | Line | Power Gap |
|---|---|---|---|
| Memphis at UNLV | Aug-30 | UNLV -3.0 | 0.4 |
| Hawai'i at Stanford | Aug-29 | Stanford -3.0 | 0.4 |
| NC State at Virginia | Aug-29 | Virginia -3.0 | 0.7 |
| Jacksonville State at North Dakota State | Aug-29 | North Dakota State -10.0 | 3.3 |
| Sacramento State at Eastern Michigan | Aug-29 | Eastern Michigan -8.5 | 9.2 |
Build your own line: select teams, a stadium and playing conditions to generate an implied spread with adjustable power ratings, home field advantage, weather effects and more. Add a market line to identify value.
Ranks all 138 FBS teams by a margin-of-victory model build on team talent, returning production, EPA, ELO and efficiency. Ratings updated each week. See where your team sits relative to the field and whether the market spread reflects the underlying power gap.
Assigns a point value to each FBS stadium based on historical home-team margin data, controlling for roster quality. Some venues see consistent overperformance; others are effectively neutral - the tool shows you which is which.
Pulls game-time forecasts for every stadium on the schedule and flags games where wind, temperature, or precipitation cross thresholds known to suppress scoring or impact outcomes. Powered by WeatherAPI.com data.
Aggregate college football fans consensus power ratings by predicting hypothetical games. Do more predictions make better ratings? A pair-wise model experiment.
Breaks down how far each road team travels, the body-clock shift from crossing time zones, and how many days of rest each side has before kickoff. Use it to spot scheduling disadvantages the market spread may not fully price in.
Our research principles: transparent data and assumptions, a replicable method, and challenges actively encouraged. College football is noise - the job is separating genuine signal from randomness, honestly.
Most people price home field at two and a half points. Ten seasons and 6,954 games say the assumption is broadly right - but the team-by-team rankings are far noisier. Does that mean there is value? We take a look.
We ranked 131 teams by how badly ratings and bookmakers missed them across five seasons. The numbers speak for themselves, but is it predictive?
Fifty familiar beliefs about college football games, run through the same test: does the effect survive team quality, and is anything left after the line? Most are fiction, several are real but fully priced.
A factor can be completely real and still be worthless, because the line already moved. This is the ledger of what the market charged, what the games delivered, and what was left over.
Home-field advantage is worth roughly 2-3 points on average, but the range across FBS venues is large. We break down what actually drives it - crowd, travel, altitude, and familiarity - and how to apply it to a line.
Blue Chip Analytics is an independent college football analytics site built by Liam Browne. The goal is to help fans and bettors understand the lines and find value. Every number on the site is computed from publicly available data using documented methods. Blue Chip is a transparent resource that serious bettors and analysts can actually audit, and use to improve their own research and decision making. We encourage challenges and would love to hear from you - especially if you disagree with one of our numbers.
Read the full methodology or learn more on the author page.
Schedule-by-schedule breakdowns with power ratings, travel load, home-field context, and weather flags are available for all 138 FBS teams on the team pages index.
