Hello, I have been working on a little project where I need to gather historical college football data.
Using the collegefootballdata.com API with python I have extracted advanced game stats for FBS teams from 2004-2024 (garbage time excluded).

So I was messing around aggregating the data and noticed a pretty big drop off in average PPA per play prior to 2014. Combing through individual games and researching other data sources I cannot really get a clear answer. I assume this is some kind of error on my end but I can't help but wonder if there was some kind of calculation change in 2014 regarding CFBD's PPA metric or maybe this is organic.

Average PPA from 2004-2013 (874K plays): 0.04 points per play +/- (SD=0.15)
Average PPA from 2014-2024 (1.14M plays): 0.14 points per play +/- (SD=0.20)

Mean PPA (2004-2014): 0.11 points +/- (SD=0.18)

Has anybody noticed this by chance or have any ideas?

I might have just done something wrong, but while looking at the QB stats for the upcoming semi-final games, I noticed Georgia and ND seem to be missing from Riley Leonard's cfbFastR PBP stats. Assuming it's because of the postponement?

Happy new year, my fellow CFB data nerds! Is anyone else using the CFB Data API Java client generated through OpenAI (Swagger)?

I am now getting errors because the API models (Drive and Play) use Integer data types for values that exceed the data type limits. For example, io.swagger.client.api.PlaysApi.getPlays()

Exception in thread "main" com.google.gson.JsonSyntaxException: java.lang.NumberFormatException: Expected an int but was 401677184101855501

I don't know much about OpenAI code generation. Are other language libraries affected (Python, Go, PHP)? Is this the price you pay for strongly typed languages? I could try to refactor the API to use Doubles or BigDecimals but this may just lead to other issues down the road.

OpenAPI spec version: 4.6.0.

u/bluescar any thoughts?

https://www.sevenyardsback.com/post/the-point-s-after-2024-s-added-value-college-kicker-ranking

I've been using the library off and on for several years...just picked up on working on a project, and i can test calls from the Swagger site, but when i run my code that was working, first call to API just hangs......i even use the exact same code listed github page.....

https://www.formulabot.com/blog/college-football-transfer-portal-data-analysis

I often look at CFB Insiders / CFB Graphs to get an idea of how a game should go based off their EPA and Success Rate rankings, but get confused when those two don’t appear to correlate. For instance, tomorrows game between Iowa and Missouri has the following ratings:

Iowa Off EPA 98 (P) 20 (R) Def EPA 13 (P) 35 (R) Iowa Off SR 92 (P) 72 (R) Def SR 36 (P) 109 (R)

Offensive passing EPA and SR looks good, but offensive rushing is significantly different. EPA is 20th and SR is 72nd. Same for the defensive stats. Against the pass is 13/36, but against the run is 35th EPA and 109th SR.

Missouri Off EPA 37 (P) 17 (R) Def EPA 35 (P) 20 (R) Missouri Off SR 69 (P) 26 (R) Def SR 59 (P) 43 (R)

Missouri’s rankings aren’t off as much as some of Iowa’s, but rank much better in EPA metrics compared to SR.

Can someone help me understand what kind of game play results in these numbers not being similar?

Can someone share me the link where I can view games, the ranking of excitement index. I only see a description on the website.

Hi all, I just came across this API and am impressed by the amount of data available here. I've created an MCP server that you can use to make natural language queries via Claude Desktop. This enables you to run queries by just asking questions. https://github.com/lenwood/cfbd-mcp-server

Title. Trying to find historical, week-by-week data for metrics like FPI, Game Control, SOR, SOS, etc. from ESPN, but they only have historical end of season data. Same thing for the College Football Data API, unfortunately. Is there any site that I could scrape or has an API that can give me week-by-week rankings?

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 posted this to r/CFB and someone recommend I come here to post it and this is the first I'm hearing of this subreddit so now I'm excited for other football number nerds.

I'm looking for some opinions on a new computer poll that I created. It's similar to the BCS poll but I'm using Quadrants just like with the basketball Net Rankings. I'm not going to post the results currently because you're not going to like them which is why I am asking on your opinions for how much to weight the following items:

Item 1: This is what I'm using as the different Quadrants for 1-4 and for Home, Neutral, and Away. **I'm using 135 teams because any FCS school is being considered #135 and a Q4 win or loss**

Item 2: This is what I'm currently using as the weighted averages and how much of a factor it plays. This is what I'd like everyones opinions on. If there's a metric I don't have listed, please let me know what it is and why you think that should play a vital roll in the rankings.

The formula that I'm currently using is below. Will be curious if I add metrics or change weights to see how things play out:

NET = (WP*55%)+(SoS*20%)+(Eff.*15%)+(SoR*10%)+(Q1W*40%)+(Q2W*30%)+(Q3W*20%)+(Q4W*10%)+(Q1L*10%)+(Q2L*20%)+(Q3L*30%)+(Q4L*40%)

Any and all helpful opinions are welcomed.

Thanks!

Years ago, I wrote a script that implements a very simple formula to rank teams in an unbiased manner.

• You get 1 point for every team beaten by a team you beat
• You lose 1 point for every team that beat a team that beat you

The nice thing about this is it rewards playing good teams without having to base what a "good team" is on personal opinion. If a team has won a lot of games, beating them earns you more points. If a team has lost a lot of games, losing to them penalizes you more. Either beating a winless team or losing to an undefeated team will not impact your score.

This year the rankings have been very controversial, more so than usual, primarily due to the SEC cannibalizing itself. So I decided to break out this script again and see what it reveals. The following are the top 25 according to this formula.

I also scaled the points to the number of games played since I noticed some teams were getting an unfair advantage due to having played 11 games instead of 10. That is why some teams have decimal values.

#1. Oregon -- 11-0 -- 54.54545454545455 points

#2. Alabama -- 8-2 -- 48.0 points

#3. Ohio State -- 9-1 -- 44.0 points

#4. Boise State -- 9-1 -- 43.0 points

#5. Texas -- 9-1 -- 43.0 points

#6. Georgia -- 8-2 -- 42.0 points

#7. Indiana -- 10-0 -- 41.0 points

#8. SMU -- 9-1 -- 41.0 points

#9. Notre Dame -- 9-1 -- 39.0 points

#10. Miami -- 9-1 -- 38.0 points

#11. Penn State -- 9-1 -- 38.0 points

#12. Colorado -- 8-2 -- 38.0 points

#13. Army -- 9-0 -- 37.77777777777778 points

#14. BYU -- 9-1 -- 36.0 points

#15. Texas A&M -- 8-2 -- 35.0 points

#16. Iowa State -- 8-2 -- 31.0 points

#17. Ole Miss -- 8-2 -- 31.0 points

#18. Kansas State -- 7-3 -- 31.0 points

#19. Tulane -- 9-2 -- 30.909090909090907 points

#20. South Carolina -- 7-3 -- 29.0 points

#21. Clemson -- 8-2 -- 28.0 points

#22. Tennessee -- 8-2 -- 28.0 points

#23. Washington State -- 8-2 -- 28.0 points

#24. Syracuse -- 7-3 -- 26.0 points

#25. Texas Tech -- 6-4 -- 26.0 points

I don't think anyone will be surprised by Oregon at the top. Alabama at #2 was a little surprising to me, but they do have a couple ranked wins which is more than pretty much anyone else. Boise State gets some recognition, which they probably should considering their only loss is a close loss to the #1 team which is more than practically anyone else can say. Ultimately there's very little separating anyone which is quite different from what I saw in previous years but also seems accurate to how this season is going.

To those interested, here is my code and the original post explaining it.

https://gist.github.com/sem42198/f12459f2e1914fbf76c94320297595fa

https://www.reddit.com/r/CFBAnalysis/comments/e4rfey/basic_way_to_determine_rankings/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

Which resume/SOR ratings evaluate the season holistically based on historical priors? I'm envisioning a rating based on (for example) how many teams that played 8 top 40 teams (in SP+ or some independent rating system) won at least 6 games, along with how many teams that played 6 top 30 teams won 5, etc., incorporating results for each threshold. It seems relatively simple other than the data compilation, so I suspect one or more well-known systems does this, but I haven't found one on my own yet. It sounds like FPI (as just one example) is based on game-by-game likelihood of victory, which might give different results due to cross-game error correlation or other reasons.

I know this website exists because I've used it in the past, but I cannot find it for the life of me. Does anyone know where you can find historical week-by-week conference standings? The website I'm remembering was pretty basic, but had every week archived. It's driving me insane.

I am looking to improve on my CFB betting model and one area that needs significant improvement is in the early part of the season. I would like to improve this by looking at the offseason win total markets to get a better initial power rating. Does anyone know if there is historical data on the CFB offseason win total markets anywhere?

I'm using CFBFastR, and I'd like to be able to see the per-game and per-team versions of Success Rate, Explosiveness (through PPP), points per trip inside the 40 (finishing drives), field position, and turnover margin (i.e. Bill Connolly's Five Factors underlying SP+)

https://www.footballstudyhall.com/2014/1/24/5337968/college-football-five-factors

I can find a lot of them in CFBFastR. How do I get "Finishing Drives"? Do I need to write my own function of all the play by play data? Or does it exist?

So the the goal is to give every school an abbreviation with their logo in a small box. The box is only going to be 55 pixels wide, so I don't have a ton of room to work with. My max is really 4 letters. To give you an idea, here is a sample of what I am working on.

Imgur

Most abbreviations are fairly set in stone. Some of them are a little tougher. Everyone doesn't need to be completely unique since logos will be included, but the more variance is the better.

I appreciate any feedback!

Does anyone have what each team's SRS was following each week so far this season and would be willing to share? I usually grab it from (https://collegefootballdata.com/exporter/ratings/srs) but that only has season cumulative SRS.

Hopefully, someone else uses it in their model and has it saved by the week.

Thank you!

Has anyone developed a database with the following datasets/attributes? If not, is there any interest in collaborating to create one?
Historical college football results
Opening betting lines
computer model lines such as Massey and Sagarin (or others)
then looking at upcoming games with the same comparison?
Replicating for over/unders all of the above

Thanks

Does anyone know where I can find snap counts for free? Trying to see a breakdown of receivers for Alabama and having trouble finding it

Is there an alternative to ESPN for play by play data? There are no drives/plays for OSU vs Iowa.

I hate anOSU with a passion unknown to mankind, but FFS, how is there no data for a game played by a top 5 team? Is this some network contract bullshit, incompetency by ESPN or what?

I want to do some analysis related to how different formations (13 personnel, etc.) stack up against each other in terms of PPA/EPA. Is there anywhere I can find individual play formations? I, of course, could feasibly use collegefootballdata.com to scrape play-by-play stats, and manually add the observed formations. But, if someone else has already done that for me not gonna complain

On this page I can select more and then export and download all the data. I'd like to automate that process (Python if possible but not necessary). How do I do that? I'd like to download the csv automatically.

Hi all,

I once used a formula that I saw somewhere that allowed you to calculate “expected third down conversion rate” based on the distance to go.

The idea was that you could calculate all the distances faced by, say, a single team in a single game, and come up with an expected third down conversion rate (ex 28.4%) that could be compared to the actual third down conversion rate (ex 4 of 16, 25%), allowing us to return a “marginal third down conversion rate” (ex, 25% - 28.4%, or -3.4%) to see how good a team is on third down accounting for distance faced.

I remember that it was a regression formula that used the log of distance, but I don’t recall the coefficients and googling isn’t helping.

Anyone familiar with this calculation?

JMU Put up 70 points in a 70-50 win over UNC. Read all about it!

https://twsn.net/2024/09/james-madison-scores-70-points-in-shootout-win-against-unc

CFB-Graphs.com isn’t available anymore, and I’m looking for a replacement for it. I’m not sure how they were coming up with the rankings, but I think they were basing them off opponent adjusted success rate. There were rushing and passing for both offensive and defensive ranks. Looking for somewhere that ideally offers these rankings on the same page so that it’s easier for me to scrape than having to view a new webpage for each team’s profile to find them, but I’ll take that if the former isn’t available. Thanks for your help.

Who has the 2024 College Football Schedule in Excel Format.
I know the PDF is created from the Excel. So who has it?