This metric correctly predicted before the season even started that the Hokies would go 6-6. And while opt outs changed the complexion of the bowl game, the metric had picked the Hokies to lose that game anyway.

Still, this metric offers real insight into just how close the Hokies were to being a good team (e.g., 8-4 or 9-3), and it shows that even though Tech needed a win in the final game over UVA just to gain bowl eligibility, six wins was always the realistic floor.

Team Talent Composite

The Formula where c is a specific team's total number of commits and R_n is the 247Sports Composite Rating of the nth-best commit times 100.ExplanationIn order to create the most comprehensive Team Recruiting Ranking without any notion of bias, 247Sports Team Recruiting Ranking is solely based on the 247Sports Composite Rating.Each recruit is weighted in the rankings according to a Gaussian distribution formula (a bell curve), where a team's best recruit is worth the most points. You can think of a team's point score as being the sum of ratings of all the team's commits where the best recruit is worth 100% of his rating value, the second best recruit is worth nearly 100% of his rating value, down to the last recruit who is worth a small fraction of his rating value. This formula ensures that all commits contribute at least some value to the team's score without heavily rewarding teams that have several more commitments than others.Readers familiar with the Gaussian distribution formula will note that we use a varying value for σ based on the standard deviation for the total number of commits between schools for the given sport. This standard deviation creates a bell curve with an inflection point near the average number of players recruited per team.Below is a graphical representation of how our formula works. You can see that the area under the curve gets smaller both as the rating for a commit decreases and as the number of total commits for a school increases. The y-axis in this graph represents the percentage weight of the score that gets applied to an overall team ranking.

In this episode, I decode Brent Pry’s coach speak, examine the player personnel considerations in light of these and other injuries, and look ahead to what it all means for the rest of the season.

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Or, perhaps more accurately, can he?

Is all the focus on in-state, high school recruiting just window dressing?

I still have not drawn any firm conclusions, but going through this exercise was a clarifying experience. Hopefully it will be for listeners, as well.

This topic took on new relevancy this week when Georgia Amoore and Elizabeth Kitley addressed Tech fan reactions to Kenny Brooks leaving for Kentucky and Georgia electing to follow him to Lexington for her final season.

The insights the players share are applicable across sports, as are the takeaways from the analysis presented in this episode.

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In this episode, I talk about what’s at stake in 2024, the uncertainty hanging over the athletic department, why Kenny Brooks had to take the Kentucky job, even if he didn’t really want to, and how pressure is building on the football to team to win, and win big, in the fall.

As mentioned in the episode, here is part 1 and part 2 of an excellent short series on the history of the wishbone formation.

This 2020 ESPN article about the 1970-71 series Alabama and USC is also worth a read if you missed it when first published.

How the Hokies would stack up in each hypothetical, with the proxy measure of average player recruiting rating as a guide, is the topic of this episode of the Hokie Analytics Podcast.

• When it comes to quarterback recruiting, Virginia Tech might get less from more than any other team in the nation.

• The once vaunted DBU has a dismal hit rate (players who actually went on to start at Virginia Tech)

• Bud Foster, who was a supposedly average-at-best recruiter, did surprisingly well with his position group, the linebackers.

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I’m guessing a fair number of listeners feel the same way.

A lot goes into a 4th down decision, and analytics provide only some of the inputs.

In this episode, I’ll explain what broadcasters are talking about with regard to why teams should go for it. I’ll also list the ways in which I believe they are misapplying these “analytics”. Finally, I’ll wrap with a discussion about 4th down conversion rates in different parts of the field.

This is just one example a weird portal trend. There are plenty of others.

In this episode, I discuss the five main types of transfers, compare UVA and Virginia Tech portal losses and acquisitions, and look at portal pipelines developing to and from Virginia Tech.

Virginia Tech returns a lot of players, and the team as a whole carries a ton of momentum into the offseason.

Next year the CFP expands to 12 teams, and if Virginia Tech is a 9 to 10-win team, they will certainly merit consideration for inclusion.

What it will take to actually get a bid is the topic of this episode, as I quantify the pre-requisites in terms of both on-field performance and talent.

If successful, the Seminoles will leave the ACC, likely prompting an exodus of many, if not all, of the so-called Magnificent Seven schools, of which Virginia Tech is one.

In this episode, I break down FSU’s legal complaint, pointing out its strengths and weaknesses. I then bring things back to the Hokies, their history in past conference realignments, and the list of options from which the university will have to choose.

Solutions do exist, though, and on today’s episode, I will discuss a couple that I believe are both workable and would succeed in aligning incentives sufficiently to fix the problem.