2021 CFB Final Team Tiers

All 130 FBS teams clustered into tiers, which tier is your team in?

Georgia ending their 41 year championship drought was the final chapter of yet another fun and chaotic college football season. In case you don’t follow me on twitter, here is the final advanced box score for the national championship:

Georgia was able to clean up their turnovers, while also forcing Alabama to commit some as well. In the battle of heisman vs. elite defense, the elite defense won out. Congrats to Head Coach Kirby Smart and the entire Georgia Bulldog faithful, its been a long time coming!

The AP Poll has served as the final ranking of a college football season, but we only get to see the top 25 plus a handful of teams receiving votes. Instead of limiting ourselves to ~30 teams, we can put all 130 FBS teams into tiers to see which teams how teams played this season. The easiest way to accomplish this mission is by using our bread and butter clustering algorithm to help us group teams together using an assortment of variables.

The variables used for these tiers are as follows:

• Raw Expected Points Added per Play for both offense and defense

• Success Rate for both offense and defense

• Explosive Play Rate (EPA > 0.8) for both offense and defense

• F+ ratings, which are Brian Fremeau's FEI ratings with Bill Connelly's SP+ ratings in equal parts

• Win Percentage

• Expected Win Percentage. This is obtained using postgame win expectancy, which takes the stats in a game and calculates how often you should win that game.

2021 Team Tiers

In order to be able to plot the cluster in a two dimension graph, the variables are squished together using principal component analysis. Outside of teams like champion Georgia, runner up Alabama and Rose Bowl champion Ohio State, there is a massive clump of teams in the middle. On the other end of the spectrum you have teams like UConn, UMass and New Mexico, who will most likely not have very many fond memories of the season.

Tiers 2 and 3 would offer the most lively debate in terms of team placement. As you will see in a second, the tiers were close together in terms of averages across the variables. The reason we average the variables by cluster is to give us a quick observation about the teams in said cluster. Perhaps a strength of one cluster is high powered offenses, while another cluster may have more defensive led teams.

Tier Stats

Its pretty clear just by eyeballing the teams in the first cluster they would be head and shoulders better in advanced metrics than the other clusters. Going back to the cluster 2 vs 3 debate, you can see they both averaged about the same expected win percentage, but cluster 3 ended up winning a bit more over expectation. Turnovers and penalties are not factored in post game win expectancy, which means its likely the teams in this cluster may have benefited from these in their wins.

Advanced metrics like F+ and SP+ had, on average, the teams in cluster 2 over cluster 3. Cluster 2 teams appear to have stronger defenses than their offense, while cluster 3 teams leaned more on their offenses. Teams like Western Kentuckys vaunted Air Raid, Coastal Carolina’s triple option passing attack, and Miami’s Tyler Van Dimes show back up the claim that this cluster is filled with fun offenses.

After you get past the first three clusters, you get to the clusters of misery. For one reason or another, these teams just could not get much going this season. Boston College was looking very strong to open the season, but an injury to stud QB Phil Jurkovec derailed the Eagles. There were 8 teams that should have been bowl eligible had they met their expected win percentage, but ultimately did not make a bowl game. 4 out of those 8 teams (Cal, Florida Atlantic, Illinois, Navy) found themselves in Cluster 4.

The raw expected points added numbers tell a similar story to the adjusted metrics. Cluster 2 is very similar to Cluster 1 in terms of defensive efficiency, but the offensive numbers are lagging behind. I couldn’t think of a better cluster ambassador for this observation than the Clemson Tigers.

Clemson finished 4th in defensive EPA/Play, and 3rd in Defensive F+. They had a championship caliber defense, but their offense could not get anything going to support the defense. This will be the biggest test for HC Dabo Sweeney. His right hand man on offense, OC Tony Elliot, is now the head guy at Virginia. As of the time of this writing Clemson has not dipped their toes in the transfer portal market, making 5 star signee Cade Klubnik the main threat to incumbent starter DJ Uiagalelei. Coming off the heels of Deshaun Watson and Trevor Lawrence was always going to be hard for the next guy, but expectations were still high for Uiagalelei. It will be interesting to see if Uiagalelei can rebound, or will the Cade Klubnik era start earlier than expected.

Conclusion

The 2021 CFB season is officially over. Georgia finally sits atop the college football world after 41 long years. We got two first time playoff participants in Cincinnati, the first group of 5 team to ever make the playoff, and Michigan, who finally ended their long drought against rival Ohio State. There were so many exciting storylines in the 2021 season. Hopefully your team saw some successes, and an exciting future lies ahead.

Now that we are officially in offseason mode, you may be wondering what comes next for this newsletter. The offseason for CFB Analytics is a great time to really dive into projects and get down to some in depth analysis. Whether its recruiting, the NFL draft, or game strategy, you will be getting a good helping of all three during the offseason. If there is anything you want to see or questions you want answered, you are more than welcome to reach out to me and I will see what we can do.

Thank you all for following along this season. I really cannot thank you enough for the support of the newsletter. I appreciate each and every one of you and can’t wait to continue this data driven journey into the offseason and the 2022 season!

If you want to dive in to the data like I do, check out @CFB_Data and @cfbfastR on Twitter, where you can learn how to get started in the world of College Football data analysis!

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