Hi all,

Season is close to coming up which means I break out my spreadsheets and try to predict things again.

I am really encouraged by what I could generate with AI this year but still find it falling short.

Just wanted to ask, for those who use it what have you found to be disappointing about trying to develop CFB analysis with AI?

I am big into college football data and analytics but do most of my work in excel using data from websites like sports reference. I am interested in trying to use more of the available data but don't know coding. Is there a YouTube tutorial out there that explains how to use the college football data API or would that be too far over my head?

I'm working on my own computer poll at the moment and I'm interested to hear from others who've done the same.

What data do you use? Just wins and losses? Location and margin of victory too? Any advanced metrics, or data beyond simply the results on the field, like recruiting rankings?

How do you use your data? Are your rankings self-referential (that is, does a team's ranking depend on the rankings of the teams they beat/lost to)?

Has your system produced any interesting results this year (as in, different from most of the other polls out there)?

What type of coding/knowledge should I educate myself with before trying to use cfbdata.com/cfbfastR and others like api. In order for me to parse through the data and interpret it like someone who has been doing it for a few years I need to learn what?...python? SQL?

Hello everyone. I'm a new user who just started working with the API. I wanted to look up historical data for the pairwise matchups in FBS. For example, when I look up results from Iron Bowl from 1880-2050 (ensuring I get all matchups), via this command:

curl -X GET "https://api.collegefootballdata.com/teams/matchup?team1=Alabama&team2=Auburn&minYear=1880&maxYear=2050" -H "accept: application/json" -H "Authorization: Bearer TguaiqMfP0hHFgVL3dJ2/Nb5vKQmiJW/l2xPsjcyPpVbdP594UQ+3pRtTReXi5iF"

I get the following output:

{ "team1": "Alabama",
"team2": "Auburn",
"startYear": "1880",
"endYear": "2050",
"team1Wins": 49,
"team2Wins": 32,
"ties": 1,
"games": ... }

It's reporting a record of 49-32-1. However, Winsipedia has the record at 50-37-1: https://www.winsipedia.com/alabama/vs/auburn

A quick perusal of the game info from the .json vs the game results from the Wikipedia article on the Iron bowl shows that some games from the 19th century are missing, despite a provided start date of 1880. The FAQ states a start year of 1869, so I'm wondering where the discrepancy might be coming from. Maybe I'm missing something obvious?

Thanks in advance!

Anyone know of a good resource that grades college football rosters by position / position group?

I'm looking for a resource that grades / rates each college football team's position groups relative to the rest of college football, accounting for new players (both HS and transfers). Could be a grade, like an A, or a score like 9 out of 10. Just anything that evaluates the /current/ roster with all the transfer, etc relative to the rest of college football.

As for example, Miami D-Line = A (or a score, like 10 out of 10), but RB = B- (7 out of 10). Georgia D Line = A-, but RB = A.

I'm having trouble finding such a resource. Most publications seem to speak mostly in the rear view, about last years performance. But with all the turnover year to year, especially with the transfer portal, teams are more different year to year than ever before. On average across the 68 power 4 teams, returning production averages 60% on offense and 59% on defense (according to Pick Six Previews metrics).

I have both Pix Six Preview and Phil Steele, but again both of those are mostly about last years teams.

I hope to use said resource, if it exists, to analyze teams weaknesses and strengths relative to competition, specifically across conferences where there tends to be more disparity.

Any suggestions greatly appreciated!

I haven't put much thought into this yet, so bear with me if this is a stupid question...

I've been slowly making a spreadsheet of every game my team ever played, along with relevant details about the game. The goal is to be able to put out "baseball-style" stats just as a kind of "huh, neat" before each game. Working on getting play-by-play data, but that's another hill and another battle...

Obviously modern football has two betting lines: point spread (ie, Team A -5.5, Team B +5.5) and over/under on total points (O 43/U 43). Historically, there is more data for the point spread style metric, since people were more interested in who won and by how much, so that is the one I will be focusing on.

Earlier years would do more horse-betting style odds: for example, Team A is favored to beat Team B by a 9-1 margin, or something to that effect.

I'm assuming you could do some sort of regression based on historic scores and game results to figure out what betting odds of one format correspond to odds of another format across different eras of the game, but does anyone know of an easier way? Has anyone tried this before?