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Stanford vs Syracuse Over/Under Pick Friday Using Expert NCAAF Projections

Two dynamic offenses in a dome headline Friday’s Stanford vs. Syracuse tilt. Utilizing PRO betting models, we can exploit the total points expected for the ACC college football game, opening up an opportunity for a Stanford vs. Syracuse over/under pick.

To add substance to this analysis, we’ve tapped into PRO Projections, proprietary betting data from our team of college football experts.

The average closing total for Stanford games this season is 60.5, indicating a propensity for high-scoring affairs. On the other hand, Syracuse showcased their offensive capabilities by going over the total in their season opener. However, their total last week closed at 60.5, reflecting a tendency for varied outcomes in line with the betting market.

Here are projections for a big edge Friday for the Stanford vs. Syracuse over/under.


Stanford vs. Syracuse Over/Under Pick

The PRO Projections tool is designed to uncover value in betting lines and totals by providing a detailed analysis and grading system. This data is invaluable for bettors who want to make informed decisions throughout the college football season. By unlocking our projections, users gain access to insightful analysis and top picks that can be used all year long.

With this as the backdrop, let’s delve into the specifics of the Stanford vs. Syracuse showdown and highlight where the betting value lies.

Syracuse enters this game as a two-score favorite, with an over/under set at 56.5. According to the PRO Projections, there’s a key discrepancy in the totals. Our fair total, calculated to be north of 59 (specifically, 59.7), presents a notable edge worth considering.

This difference between the posted total of 56.5 and our projected total of 59.1 suggests that betting the over in the Stanford vs. Syracuse over/under could prove profitable. It’s graded B by our advanced models.

PRO Projections Over/Under Pick for Stanford vs. Syracuse: Over

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Our PRO signals flag far more great picks than our staff could author each day — that’s where Action AI comes in. Using generative AI, signals that hit a high grade threshold are written up into articles that are then vetted and edited by a human to help us get you all the sharp action. Read more about how it works here.


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