Good morning, and thanks for spending part of your day with Extra Points.

I hope you’re all having a wonderful Holiday season, no matter what you’re celebrating this December.

I certainly am! I’m currently up in the mountains outside of Ogden, Utah, in a big ol’ house with my wife’s extended family. I’ll get back to Chicago on Saturday, so I’ve got a little more time left surrounded by snow, cookies, and a lot of toddlers.

I know how the trope goes, but I legitimately enjoy spending time with my in-laws and the families of my wife’s brothers and sisters. While spending a week on top of a mountain amid of sea of toddlers isn’t always quiet, that doesn’t mean it isn’t rejuvenating.

One of the biggest reasons I’ve come to cherish the few times a year when I can step away from the daily newsletter hustle is that it means I’m on the internet waaaaay less than I normally am. I’m sure I missed multiple outrage cycles in the sports media/sports law/terminally online world while I was busy chasing toddlers, building snowmen, and playing Dave the Diver on my Steam deck.

But I did watch the College Football Playoff, which meant that I still got exposed to several Serious Professional College Sports Thought-Leaders Being Very Angry About Indiana Football.

I don’t want to relitigate the entire thing here, but as I understood it, The Debate centered on the concept of strength of schedule. Indiana, a team that badly lost a road playoff game to Notre Dame, failed to defeat a good team during the regular season, and were thus exposed as Clownfrauds. Other teams, most notably Alabama, had defeated good teams, and thus were more worthy than Indiana, despite the disparate records, or the fact that Alabama had also lost to two lousy teams.

Personally, I don’t think this debate is really about strength of schedule, or even about Alabama at all. It’s really about the idea that some segments of the College Sports Industrial Complex simply cannot accept the idea that, sometimes, teams outside the SEC could be very good.

That’s a debate that I can’t pretend to settle in one newsletter, especially since I think that debate is deeply influenced by stuff that has nothing to do with actual football.

But it did get me thinking…what even is college football strength of schedule?

I mean, I understand the general concept, of course. A strength of schedule metric would assign some sort of number to measure the quality of competition a particular team faced. Every college sport, from basketball to softball to hockey, has some statistical tools to help with these measurements.

But football is different from just about all of those sports in two very significant ways. For one, college football teams don’t play very many games. The regular season is only 12 games. A college baseball will play around 60 games. A basketball team will play around 30. Almost everybody plays substantially more than 12 games, which means that any SOS analysis will have more data points and provide more accurate measurements.

The only important difference is that not only do football teams not play very much, period, they don’t play many out of conference games. Strength of schedule metrics require intersectional play, to create the sufficient data to actually compare teams and conferences.

For example: without much intersectional play, one might hypothetically say Alabama is an elite team, because they beat Georgia. And we know Georgia is an elite team, because they beat Tennessee. And we know Tennessee is elite, because they beat Alabama. But without intersectional data, we can’t know if ANY of those teams are actually any good. We just assume they are, because of their budgets, recruiting rankings and brand.

I’m not saying that I think it is impossible to compare college football teams. I’m comfortable saying a win over 2024 Penn State should be considered a stronger win than, say, a win over 2024 Western Michigan. But the more specific and granular you want to get with team comparisons, the less certain I become about the validity of an SOS metric. It’s going to have a high error range and could be easily influenced by our own biases.

Get the full story and subscribe to Extra Points today:

But this can be a difficult thing to write or say on television, because an SOS metric is a number. Who could possibly get in front of a microphone and suggest that the bigger number isn’t better than a smaller number? Counting is way easier than reading, after all.

I think being data-informed is awesome, whether you’re trying to seed a College Football Playoff, recruit a basketball roster, sell baseball season tickets, or run a newsletter business.

But it doesn’t matter how clever your R and Python calculations are or how sophisticated your model is if the data you’re using sucks.

I don’t think this is a problem unique to college sports strength of schedule models. I’m coming around to the idea that it’s close to the central challenge of the sports industry, from coaching to administration.

It can be very seductive to outsource your own thinking to a number that neatly fits into a spreadsheet cell or formula. Coaches and ADs spend hundreds of thousands of dollars a year, if not millions, on raw data, data that they hope they can mold into actions to defeat their competition, folks who are largely paying for the exact same data.

I humbly submit that this year, everybody ought to spend more time wondering about the quality, accuracy, and limits of the data they obtain…or at least, before they bet the proverbial farm on it.

In the case of a playoff selection committee, understanding that Strength of Schedule, (whether you use FEI or ESPN Power Ranks or ELO Chess or OMGBBQ or whatever) will have certain limitations means that you want to supplement that data with other data. I’d personally recommend efficiency-based data, like SP+, that shows how teams performed on a play-by-play basis, but certainly there are others. The only reason you have a committee is that you believe you need humans to parse and evaluate multiple datasets, right?

For athletic departments trying to figure out how they’re going to balance their salary cap and directly run payroll… it doesn’t matter how awesome your ex-NFL quant savant is if he doesn’t have accurate market information about the going rate for certain players. If you don’t have that info (ideally from multiple sources), you better figure out how you get it.

And many of the other Key Performance Indicators for the college sports business, from event attendance to social media reach, website traffic to donor lists, ought to also be interrogated. To paraphrase 2 Corinthians 13:1, “In the mouth of two or three dashboards shall every word be established.” If Google or Sidearm Sports or PFF tells you something…trust, but verify.

I try to do the same thing with how I run Extra Points. I probably shouldn’t write this somewhere where prospective advertising partners can read it, but there are a lot of problems with the validity of email data. Open rates and click-through-rates can be manipulated by bots, university firewall systems, or Google. I care about all kinds of data sources for my business, but the only one I completely trust is what I get from the ol’ Stripe Direct Deposit. The other stuff you’re going to see in Media Kits is gonna have a large error bar.

(That being said, you should totally advertise with Extra Points in 2025. Hit me up at Sales@ExtraPointsMB.com for rates and availibility)

Anyway,

I think there are essentially just four jobs in college sports in 2025

You need people to obtain the data. You need people to verify the data. You need people to analyze the data. And you need people to teach others based off that data.

Over the last 15 years or so, I think we’ve seen real growth in the sophistication and intensity of obtaining data in college sports. That’s great! The best coaches have always been, at heart, teachers…the sort of people who can explain a complicated concept to a headstrong 20-year-old very quickly. In my professional experience, I believe many departments and teams are getting much better at parsing data…but I know I’ll want to report more on what that looks like in different fields.

I do not believe that teams, administrations, and for that matter, media outlets, are good enough at the data verification part of the equation. You can make a real pretty graph and come up with a great plan based on that graph, but if the numbers don’t represent what you think they do…it will won’t help anybody.

Screw that up, and maybe those PFF grades that you used so heavily in your transfer portal evaluation services mean that you end up paying $800,000 for a 4th string left tackle. It might mean you spend tens of thousands of dollars on branding and marketing strategies that ultimately don’t lead to ticket sales, donor gifts or new students. It might mean you undersell your MMR inventory by four million dollars.

Or, it might mean you get so angry about Indiana football that you become a meme and launch furious think pieces. When in doubt, try to avoid becoming a meme.

Hey, speaking of data, I can’t sit here and say I know how to fix all of your problems. But we have put together a Library with nearly 5,500 documents, from itemized athletic department budgets, to coach contracts, to vendor contracts, and much more. Whether you’re a reporter trying to cover college sports, a vendor trying to get better pricing data, or an AD looking to hire a new assistant volleyball coach, you need the best data you can get. I believe Extra Points Library can help with that.

Give it a spin today and see if it has the sort of information you’re looking for. If it doesn’t, drop me a line, and I’ll try to get that data for you. We’re adding more stuff every week, once all those poor beleaguered records clerks come back from holiday, we’ll have loads more documents to add.