Zwiller: ZeLO predicts the blue bloods in Week 4

With the third week of college football, ZeLO now boasts a record of 190-58 (76.6%). However, this weekend, the model went 54-18 (75%), so it was a slight dip from the prior weekends. I upped the in-season adjustments this week, so now the model is even more responsive to the USCs and Texas’ of the world. Hopefully, that will help to improve the model’s performance this weekend. 
Now, onto the picks!

Maryland at No. 4 Michigan

As a Michigan fan (ducks to avoid rotten tomato), I have been following the Wolverines’ season closely. Michigan started the year strong, with a record of 3-0 and an average margin of victory of 49.6. Nevertheless, any team should do reasonably well against a schedule of Colorado State, Hawaii and UConn. I did a little experiment to see how well most teams would do against that schedule. Of every single team in college football, 117 would be favored against CSU, 130 against Hawaii and 125 against UConn.

In other words, Michigan has not played anyone of consequence. So that is why I picked this game. ZeLO currently has Michigan with a 75.3% chance of victory.  If Michigan is as good as ZeLO thinks, they should get a solid win. If not, Maryland might expose the Wolverines.

No. 5 Clemson at No. 21 Wake Forest

Like Michigan, Clemson has not played anyone of note, so they look like a reasonably dominant team to ZeLO. Unlike Michigan, however, Clemson has looked fairly unimpressive, with the Tigers blowing out Georgia Tech after a slow start, a weak showing against Furman and an (okay) win against Louisiana Tech. 

Clemson enters conference play this week, and they start with No. 21 Wake Forest and then No. 12 NC State the week after. In other words, much like Michigan, it is time to find out what precisely the Tigers are made of. 
I think Clemson is a bit of a paper tiger — mascot pun fully intended — and at least one of their next two opponents should unmask them. The Tigers’ offensive production has been lackluster, with ZeLO ranking them 27th offensively (defensively, they rank fifth). 

Clemson has a 62.9% chance of victory against Wake, which is pretty good, considering Clemson is the road team. I think that number is a shade too high, and it would not surprise me if this is a closer contest than ZeLO expects and if the Tigers were to lose straight up.

No. 22 Texas at Texas Tech

Texas is arguably one of the biggest benefactors of my projection-live stats updates. Originally the model was not at all impressed with the Longhorns, having them as a middle-of-the-road team in the Big 12. Suddenly, Texas is one of its stars, and now Texas is projected as a top-2 or top-3 Big 12 squad. Their in-state opponent, Texas Tech, is by no means a bad team. Tech ranks just outside the top 50, with Texas ranking 38th overall. This should be a good game (in the eyes of ZeLO), with the Longhorns being the favorite to win (56%).

No. 3 Ohio State at Wisconsin

Ohio State seems to be fitting a bit of a trend for this week’s picks. They are certainly a good team. The question is more “how good are they actually?” Ohio State has not played anyone of consequence so far (and I include Notre Dame in that statement, ZeLO ranks them 72nd.)

Moreover, while Wisconsin may not be a ranked team, they are not a poor team. ZeLO has the Badgers with the nation’s number one defense, and their narrow loss to Washington State is their only blemish on the year. 
With Ohio State heading on the road for the first time this season against a conference opponent who should give the Buckeyes a hard time on offense. It will be time to see how good the Buckeyes are. 

No. 7 USC at Oregon State

If Texas was the team that benefited second most from the model’s new projections system, then USC is without question the primary benefactor. The Trojans have been an offensive juggernaut this season, and ZeLO has them ranked as the 10th-best offense in the nation. That mark is likely held back by the model’s pre-season projections, which has the Trojans as an above .500 team (though one that had a chance at a solid bowl game). 

ZeLO is now singing a different tune, with the Trojans ranked as the second-highest team in the conference (only Utah is higher at 10th). The Trojans are also the odds-on favorite to make the conference championship.  Just because ZeLO likes USC does not mean that it thinks they are a lock against Oregon State. However, thanks to being the road team, ZeLO has the Trojans as just a slight favorite (51.3%).

In all fairness, the distinction is that USC is the road team. If the Beavers were on the road, it would be a somewhat different story.

Notre Dame at UNC

That Notre Dame is a +2 underdog despite opening up as a -1 favorite is surprising. As good as UNC has looked on paper, the Tar Heels boast wins against Florida A&M, a shootout with Appalachian State and a narrow win against Georgia State. The Tar Heels looked impressive in zero of those games, looking great offensively but atrocious defensively. I see the Tar Heels as a bit of a paper dragon (or would it be paper ram?). 

I honestly think that ND can win this game. They have the defense to slow down UNC, and the lackluster offense might find new life against a UNC defense that would be lucky to stop a pee-wee football team. 
However, you are not here for my takes. You are here for ZeLO’s takes. And like I said way back in August when I first wrote about what the model predicted for ND, this game should be a struggle for the Irish. In fact, because of the two teams’ respective performances, UNC is now the favorite to win the match. The Tar Heels have a 60.3%-win probability and an excellent chance to beat the spread.

Contact Tom at

The views expressed in this column are those of the author and not necessarily those of The Observer.


Addressing ZeLO’s flaws

Earlier this week, when I wrote the “ZeLO Picks: Week 2 column,” I mentioned that despite only being Week 2 (or 3, if you count the ever-annoying Week 0), ZeLO had some problems and shortcomings.

And that is entirely true. As good as a 77.3% pick percentage might sound, even when compared to ESPN’s FPI of 84%, there is an enormous chasm between those numbers that go beyond the 6.7% difference. I hope to address some of those problems and then offer a few different solutions.

First things first, I track both ZeLOs and FPI’s performances in more ways than just their win-loss record. While that is a strong indicator of your correctness, there is a difference between me giving someone a 51% chance of winning vs. me giving someone a 90% chance of winning. 

If I am repeatedly more confident (and correct) about a result, I am making a better forecast about the given outcome. 

Well, the same is valid with FPI and ZeLO. While ZeLO has agreed with FPI on a vast majority of the games the two models have picked, FPI tends to be more confident in the teams it picks to win. 

Take, for example, the Week 2 matchup of Marhsall vs. Norfolk State. FPI gave Marshall a 99.3% chance of victory, while ZeLO only gave Marshall an 85.5% chance.

Both models got the pick right, but on the sliding scale of correctness, FPI was “more right.” And there are a lot of instances where that is the case; both models get it right, but ZeLO is a lot less confident in its pick. 

There is a mathematical way to measure this, called a Brier Score or Net Brier Points. Essentially, Brier Points are scored by taking the prediction you made and running it through the following formula: 

25-((Predicted Outcome-100)^2/100) = Brier Score.

So, for example, using our Marshall outcome, since the Thundering Herd won the game, FPI would have scored 24.9951 Brier Points, while ZeLO would have scored just 22.8975. That difference might not seem like a lot, given that it is not even a total three points difference, but through the first Week of College football, the difference in Brier points is almost 285 points.

FPI is just a lot more confident in its picks that it will rack up a large total. I expect FPI’s confidence to lessen as teams like Alabama stop playing Utah State and start playing games where the outcome is more questionable. Still, I think the Brier Point bridge is not going anywhere soon. 

This does help ZeLO a little bit; when the two models have both been wrong, ZeLO does take less of a blow (the Brier Score formula I am using is 538’s, which tends to punish overconfidence). 

Had Marshall been upset, ESPN would have lost 74.986 points while ZeLO would have only lost 74.7 (not a huge difference, but you get the idea). 

There are two fixes that I currently see. The first is also a separate minor issue: FCS teams. I think I scored FCS teams a little bit too strongly, and as a result, ZeLO has much less confidence in picking against them than FPI. That is an easy enough fix and something I plan to incorporate next off-season.  

The second issue is that I think I weighted a lot of the raw statistics too lightly, so there is not enough separation between Alabama and Utah State. That fix is a bit more complicated, but I plan to adjust that too. 

ZeLO’s lack of confidence rolls right into the second glaring issue I observe from the Week 0 and Week 1 data. The second method I use to track ZeLOs stats is just by categorizing picks into four categories and seeing how ZeLO’s win-loss is doing in each of those categories.

The first category is Toss-Up (50%-59%), Lean (60-74%, Likely (75%-94%), and Solid (95%+). 

Currently, ZeLO is .523 in the Toss-up category, .686 in the Lean bucket, .950 in the Likely grouping, and 100% for the Solid category. 

At first, the issue might seem like it is the Toss-up category, which is underperforming at 12-12, and while I would like to see the performance rise to around 55%, a 50% performance is okay. 

No, the main problem is how the Likely category is at 97% when realistically, it should be a lot closer to 85%. This suggests that ZeLO has a classification problem, which is just a symptom of the confidence problem that ZeLO has. Instead of having 44 games classified as likely outcomes, ZeLO should have interpreted some of these matchups to be more solids than they were. I think the fixes for this problem are the same as before, change FCS teams and statistical weighting.   

The third problem I have already talked about in other columns is the fondness ZeLO seems to have for Group 5 teams when they match up against Power 5 teams. 

Because ZeLO is working off of stats, and because Group 5 teams perform against each other as Power 5 teams do, the difference between them is somewhat hidden, so when they faceoff ZeLO acts like it is two peers playing one another. The solution is to tweak the recruiting numbers to either recognize the quality of players Power 5 teams are getting or the quantity they are getting. 

Another solution is to be a bit more aggressive with the strength of the schedule component and add a distinction between playing Power 5 teams and Group 5 teams.

The fourth and final issue is how ZeLO plays against the spread. ZeLo is 33.6% against the spread, which is an atrocious mark. 

In part, I think ZeLO’s performance against the spread will improve when the lines are not Minnesota -36. ZeLO is not built to work against those kinds of spreads; a significant percentage of ZeLO’s losses against the spread come from ZeLO covering on spreads that are 25+ points. 

In fact I am already seeing some levels of improvement. In Week 0, ZeLO went 5-6 against the spread (.454), then 28-54 in Week 1 (.342) and this weekend 31-50 (.383). The difference could just be a bit of a random sample, but I do think ZeLO’s performance against the spread will improve.

And, of course, by addressing the other issues I have mentioned, I think ZeLO should also improve against the spread. 

Contact Tom Zwiller at


Zwiller: ZeLO NFL picks look to nail Super Bowl champ again

A little over a year ago, I penned a Sports Authority titled “Zwiller: Rams to be Super Bowl contenders this Year.”  

While I have never really liked the title “Sports Authority” (I have about as much authority over sports as a lucky quarter), my Rams article is my favorite article I have ever written here at the Observer. 

For one, it was just a fun piece to write; I love sports, but the NFL is unquestionably my favorite. Writing a season predictions column means that the NFL is back, and after months of speculation, we will have actual results to analyze and debate. 

That and the article aged like a fine wine; it’s always fun to be correct.

So, with the hope that I can keep my Super Bowl picking streak alive for another year, here goes my prediction, based on my ZeLO model, for the 2022 season.

AFC East

Buffalo Bills: 12.01-4.99

Miami Dolphins: 10.43-6.57

New England Patriots: 9.23-7.78

New York Jets: 6.68-10.32

According to the model, the Bills are projected to be the best team in the AFC East, with nearly a 70% chance of taking the crown. While the Patriots are likely to be a solid team with a good defense, the lack of an actual offensive weapon will be their downfall. Meanwhile, the Dolphins have two lethal wide receivers in Tyreek Hill and Jaylen Waddle, which finally propel them into the playoffs. The Jets take a meaningful step forward but still post a losing record on the season. 

AFC North

Cincinnati Bengals: 9.41-7.59

Baltimore Ravens: 9.29-7.71

Cleveland Browns: 7.9-9.1

Pittsburgh Steelers: 6.83-9.17

I have been a doubter since the Bengals began their legendary playoff run. I thought they would lose to the Titans, the Chiefs, then to the Rams and this year, they would regress. 

The model feels differently, as the Bengals currently are neck and neck with the Baltimore Ravens for the division. As for the Browns, they have an unremarkable season primarily due to the (well-earned) 11-game suspension of Deshaun Watson (though they will have a good defense). And speaking of good defenses, the Steelers should continue to have an elite unit, just not an offense that can make the most of it. 

AFC South

Indianapolis Colts: 8.8-8.2

Tennessee Titans: 8.28-8.72

Jacksonville Jaguars: 7.57-9.43

Houston Texans: 6.5-10.5

Since the Colts acquired Matt Ryan, they have been my favorite to win the division. Ryan will have a great o-line and run game and a solid defensive unit. ZeLO is not as optimistic, though; like the Patriots, the Colts’ lack of an elite wide receiver will prevent them from running away with the division. Meanwhile, Derrick Henry returns and produces incredible volume, but on low efficiency, just 4.2 yards per attempt, his worse mark since 2017. Both the Jags and Texas take significant steps forward, with Trevor Lawrence performing much better under Doug Pederson.

AFC West

Los Angeles Chargers: 11.40-5.6

Kansas City Chiefs: 9.53-7.47

Denver Broncos: 9.46-7.54

Las Vegas Raiders: 8.98-7.02

It certainly feels weird not to have the Chiefs here (and I am sure I will regret it). But the Chargers are a loaded team, boasting a better defense than KC and, yes, a better offense. Mahomes is currently the second in the model’s MVP chase, but Herbert has the better supporting cast. The Broncos certainly got an upgrade with Russell Wilson, and it could bring them into the playoffs as a wildcard, but it will not be enough to get them over KC. Vegas has a good first year under Josh McDaniels but falls short of the playoffs. 

NFC East

Dallas Cowboys: 11.52-5.48

Washington Commanders: 10.06-6.94

Philadelphia Eagles: 9.11-7.89

New York Giants: 5.73-11.26

My rule of thumb for both the Cowboys’ defense and the Commanders’ defense is to estimate that both will be a little worse than the model thinks. The Cowboys because the volume of turnovers produced last year is not sustainable, and the Commanders because the unit was questionable last year. As for the Eagles, I know they were a playoff team last year, but they went 0-6 against teams that also made the playoffs and just beat up on weaker teams. Meanwhile, the Giants continue the noble New York tradition of tanking.

NFC North

Green Bay Packers: 10.57-6.43

Minnesota Vikings: 10.2-6.8

Detroit Lions: 7.21-8.79

Chicago Bears: 6.69-10.31

This division will be incredibly close this year, thanks to the departure of Davante Adams. The Packers lack a true #1 wide receiver, and ZeLO thinks they will miss Adams this year. Meanwhile, the Vikings have an overwhelming amount of offensive talent; it’s up to head coach Kevin O’Connell to turn it into touchdowns. Dan Campbell continues the rebuild in Detroit, and the Bears finish fourth.

NFC South

Tampa Bay Buccaneers: 11.62-5.38

New Orleans Saints: 9.72-7.28

Carolina Panthers: 7.61-9.39

Atlanta Falcons: 5.05-11.95

Unsurprisingly with Brady back in Tampa Bay, the Bucs are a force to be reconned with and firm favorites to win the NFC South. I have some questions about the sheer volume Brady expected to produce, but ZeLO has the 44-year-old as its most valuable player. Jameis Winston leads the Saints to a winning record and a wildcard spot. Baker helps to turn the Panthers into a 7-win team, and the Falcons begin to figure out what their rebuild will look like.

NFC West

Los Angeles Rams: 9.89-7.11

San Francisco 49ers: 9.86-7.14

Arizona Cardinals: 9.49-7.41

Seattle Seahawks: 7.03-9.97

The Super Bowl champs will take a bit of a win-loss record step back here but still find a way to win the division, albeit narrowly. Assuming Lance is as good as his projections indicate, the 49ers will be an absolute force, both on the ground and defensively. The Cardinals, meanwhile, will have to navigate their first six games without DeAndre Hopkins, so repeating last year’s 7-0 start seems unlikely.

The Playoffs

The Bills and Buccaneers take the first-round bye as the 1-seeds in their respective conferences. The other AFC division winners are the Chargers, Bengals and Colts. The wildcard teams are Miami Dolphins, Kansas City and Baltimore. In the NFC, the other division winners are Dallas, Green Bay and Los Angeles. The wildcard teams are Minnesota, New Orleans and the 49ers.

The Chargers handle the Ravens, while the Bengals survive the Chiefs, and the Dolphins upset the Colts on the road. The Bills host the Chiefs, finally overcoming their most significant roadblock, while the Chargers have an electric showdown with the Bengals, emerging victorious. 

The Bills edge past the Chargers to make it to the Super Bowl. 

In the NFC, Dallas actually wins at home against the 49ers, Green Bay beat the Saints, and the Rams continue their title run by barely defeating the Vikings. The Bucs host the Rams, with the Brady Bunch ending the champs title run while the Packers fall to Dallas. Tampa rematches with the Cowboys, and the Buccaneers make it to the Super Bowl for a second time under Brady. 

The ending is different this time, with Josh Allen hoisting Lombardi in State Farm Stadium. 

Contact Tom Zwiller at


Zwiller’s ZeLO Picks: Week 2

Well, Week 1 is officially in the books, and quite honestly, it could not have gone better. And yes, I include the Notre Dame loss in that, if only because ZeLO quite frankly nailed the pick. It still had Ohio State as a favorite, but by less than ESPN and (factoring in home-field advantage) had ND as a 10-point underdog. 

ND aside, ZeLO still had a solid performance. Through the model’s first eighteen games, it went 18-0, catching an unexpected stumble against Old Dominion (as did Virginia Tech). ZeLO closed the weekend going 65-18 and finished with a record of 73-21 (.776%), compared to ESPN’s 79-14 (FPI did not pick UCF). 

If you had told me that ZeLO would finish Week 1 only six games behind FPI, I would have taken it. The fact that the model is even competent is a win; I had no idea how this would go. And yes, ZeLO has some problems and shortcomings; I plan on discussing them later in a separate column. 

Right now, I want to give out some of the model’s picks. Last week’s picks went 3-1, so hopefully I can continue giving out some good ones.  

No. 1 Alabama @ Texas

I wish I could sit here and tell you that ZeLO did not think Alabama was all that impressive and that the spunky, underdog Texas team would knock off Saban’s NFL prep school. Even with home-field advantage (Texas ranks 13th), Alabama still has a 76% chance of victory.

Even though ZeLO has Texas covering, last weekend ZeLO picked a lot more underdog covers than anything else, and since this is Alabama, it would not shock me if Alabama beats the spread by the half. 

No. 24 Tennessee @ No. 17 Pittsburgh

This was a matchup I found interesting, if only because both ESPN and the gambling world were betting on Tennessee. The newly ranked Volunteers are currently a touchdown favorite over No. 17 Pitt. ESPN gives Pitt a 45.9% chance of winning, despite being ranked and at home. 

This is one of the few games — one of seven — where ZeLO disagrees with FPI and has the Panthers as the favorites with a 60.2% chance of victory. Not entirely comforting considering Pitt’s performance last weekend against WVU, but I digress. 

No. 20 Kentucky @ No. 12 Florida

Last week, after barely surviving Utah, the Gators are rewarded with an easier opponent … not much easier when you realize the opponent is also a Top-20 team. From a harder conference, but by poll logic, an easier team nonetheless.

ZeLO currently has Florida as a favorite with a 60.1% chance of staying undefeated, but the model does have Kentucky covering the +4.5 spread, so this should be a fantastic game. 

Arizona State @ No. 11 Oklahoma State

I picked this matchup only because ZeLO is pessimistic about Oklahoma State. 

While ESPN may have its golden child in Texas as the favorite to win the B12, ZeLO has Oklahoma State as one of the Top-3 finishers, with Texas closer to fifth or sixth. 

But as much as ZeLO likes OKSU, one of its more random favorites is Arizona State. Because Arizona State was not atrocious over the four-year sample ZeLO took, and because it had a positive Return+Recruit metric, the Sun Devils ended up being a solid team.  

But back to the game at hand: Considering we just saw OKSU look like it forgot how to play defense against Central Michigan, there might be an opportunity here. 

ZeLO has the Cowboys finding the win with a 50.1% chance of victory, but Arizona State finds a way to cover the 11-point spread. 

No. 9 Baylor @ No. 21 BYU

BYU has been one of the models’ favorite teams since I first started running it back in mid-June. So while I was surprised that BYU was a -3.5 favorite over a Top-10 team in the country, I was not as surprised as I should have been. 

And while this is one of those games where ZeLO seems to like Group 5 (and now independents) more than it should when they play Power 5 teams, ZeLO has BYU as a favorite to beat the Baylor Bears.

And not only is ZeLO giving the Cougars a 63.4% chance to beat Baylor, but it also has them as likely to beat their -3.5 spread.

Marshall @ No. 8 ND

I had two thoughts when I saw the graphic in last Friday’s edition of The Observer. The first was, “Wow, that graphic looks incredible.” The second was, “Good lord — I hope that pick is correct.”

The only way to lose credibility faster than picking against the home team in the home team’s newspaper is to pick against the home team in the home team’s newspaper and be wrong. 

Thankfully (or not, depending on how much you love ND), ZeLO was right and spared me the misfortune of picking wrong against ND. 

This week, though, to fulfill my contractual obligation of talking about ND, I must warn you that Notre Dame is facing … another loss. 

I’m kidding, I’m kidding; I just did that to see if you were paying attention. 

No, in reality, ND has a 62.5% chance of beating the Thundering Herd. And while yes, that seems low, that’s because I’m still working off my original projections for the season.

This is because in the past, when I have run ZeLO for the NFL, if you use Week 1 results your predictions get a little … weird. 

For example, last year’s Week 1 gave us the shocking result of Green Bay 3 and New Orleans 38. If I tried shoving that result into the model and the other random results (like the Eagles beating the Falcons 32-6), Week 2 would be bizarre. 

So, I trust my forecasting is somewhat good until four weeks into the season when hopefully, all the quirks have evened out. 

The same rule will apply here. So, ND is a little undervalued and Marshall is probably a little overvalued. ND should win, but Marshall should cover the 20-point spread. 

No. 10 USC @ Stanford

ZeLO already dunked on LSU once, so why not give it a chance to dunk on another team unpopular in South Bend? ZeLO has not once been a fan of the Trojans and will not become a fan until Week 4 at the earliest. I did not make a coaching adjustment this offseason, and USC has had no significant changes beyond its recruiting class adjustment. 

So while yes, ZeLO has a win for the Trojans, when they face a conference foe in Stanford, it will be a lot less likely than you think, 56.6%. Stanford does get the cover, though. 

Tom Zwiller

Contact Tom at


ZeLO football season projections

Notre Dame

The Observer’s new college football projection model ZeLO has Notre Dame as the 17th best team in its rankings, boasting a defense ranked 12th with an offense ranked 42nd. This initially surprised me as Notre Dame’s weighted four-year average ZeLO ranked 10th. Notre Dames Recruit+Return Metric, however, rated 105th offensively and 51st defensively, which dramatically altered their final ZeLO number. Losing players like Kyren Williams and Jack Coan, who played many snaps, will substantially affect the returning metric. Even if Notre Dame had gotten perfect recruiting grades, the offense was going to take a step backward (as far as ZeLO is concerned).

On the other side of the ball, thanks to solid retention and recruiting, the defense essentially stayed put (if not improved ever so slightly).  
Looking at the ND schedule through the ZeLO lens, ND is currently averaging 8.7 wins. There are a few games that ZeLO has ND as an underdog in. Two of them are pretty obvious, Ohio State and Clemson. ZeLO has the Buckeyes in a different class than the Irish, but ND beating Clemson is reasonable. Two of the more surprising games ND is not favored in are UNC and BYU, though both are well within what I would consider the “toss-up” category. If both games were at home, it would be enough to swing them in favor of ND. 
The remaining games, Marshall, Cal, Stanford UNLV, Syracuse, Navy BC, and USC, should all be reasonably easy games for ND to win. 
While ND is not projected to make the CFP, the Marcus Freeman era should be off to a good start with a 9-3 or 10-2 record. 


In the Atlantic Division, Clemson is the current favorite to make the conference title game (a true shocker, I know). The fourth ZeLO-ranked Tigers are likely to be a force and are just one of a small group of teams considered to be a lock for a double-digit win total. Two other significant teams are the Wake Forest Demon Deacons (an average record of 8.5-3.5) and the NC State Wolfpack (8.7-3.3).

In the Coastal, the favorite to face Clemson is much less clear. The top three teams are all separated by less than a single game. Pitt is undoubtedly a strong contender, and with an average record of 9.8-2.2, there is no reason Pitt cannot repeat as divisional champion.

Next, is the upstart Miami squad being led by their new head coach. Miami has a relatively wide range of outcomes, sometimes finishing with a record of 7-5 but also winning the coastal with a record of 10-2 (so really an average of 8.4-3.6).

Last is Carolina (which I do not love), and they are currently projected to go on average 8.1-3.9. Since Sam Howell graduated and the offense is being turned over to Drake Maye, I expect Carolina to step back more than ZeLO is anticipating. 


The SEC East is much like the Atlantic division in that it feels largely predictable. Georgia may take a step back defensively, but it is not much of a step back; the Bulldogs are projected to remain #1 defensively. The Bulldogs are currently projected to go 11.2-0.8, so a potential undefeated season as they make it to the SEC title game. Some teams of note are Tennessee (8.4-3.6), Florida (8.6-3.4), and Kentucky (7.4-4.6, though Kentucky, is prone to having some odd
sub .500 records).

The West is reasonably straightforward (Alabama, 11.1-0.9) as far as the favorite is concerned. What is more interesting to me is the race for second. There are four teams that ZeLO currently considers contenders. Ole Miss is currently averaging an 8.5-3.5 record, Texas A&M 8.4-3.6, Auburn 8.1-3.9, and Mississippi State (7.8-4.2). For those of you who have an axe to grind with LSU, the Tigers are not geauxing anywhere; instead, they should finish with a 4.9-7.1 record.

Big 10

As a Michigan native, I was thrilled with the Wolverine’s season last year (until they played Georgia). Sadly, ZeLO thinks the Wolverines’ breakthrough season is an outlier, and Ohio State (with a record of 11.2-0.8) will take the East and the Big 10. Trailing behind the Buckeyes are the Wolverines (10-2), Penn State (8.9-3.1), and Michigan State (7.6-4.4). 

In the West, the picture is a little cloudier. Wisconsin is the highest-ranked team at eight, led by their second-ranked defense. The Badgers are projected to finish with a 10.4-1.6 record, which should give them a solid chance of winning the division. Following closely behind Wisconsin are Minnesota (9-3) and Iowa (9.3-2.6). 


This is the first year that the Pac-12 has moved away from divisions and is pitting the top two finishers against each other for the title. Currently, that pits Arizona State (9.7-2.3) against Utah (9.9-2.1). Not far behind are the Oregon Ducks, with an average record of 9.5-2.5 following the departure of Mario Cristobal. The UCLA Bruins are in a distant fourth with a projected 8.6-3.4 finish.  And for those following how well a former B12 coach will do in his new conference, ZeLO has
an unfavorable view of the USC Trojans, with the team barely breaking the five-win threshold. However, roughly once in about every five simulations, the Trojans get close to winning eight games. 


And speaking of the Big 12, guess who it’s time for? The B12 will likely see Baylor (8.9-3.1) take on Oklahoma (10.1-1.9) for the Conference Crown. I was legitimately surprised by this result seeing as Oklahoma lost Lincoln Riley to USC and ESPN’s FPI is pretty low on Baylor,
giving them less than a 10% chance of winning the conference (compared to Texas’ near 40% chance). And on the note of Texas, ZeLO currently has the Longhorns in a similar boat to the Trojans;
they should be a five to six-win team, though every few simulations, Texas does make it past the seven-win mark. The next likeliest team is the Oklahoma State Cowboys, a consistent eight-win team with an
average record of 8.4-3.6. 

Group of 5

While I could probably write a separate column about the Group of 5, I doubt we have that kind of room in the budget. So instead, I will just run through some teams that have a chance to win their respective conference. 

MAC: In the East, ZeLO likes Buffalo (7.5-4.5) and Miami-Ohio (7.4-4.6) to win their division. In the West Toledo (9.7-2.3) (what can I say, the model really likes Toledo, it is genuinely one of the more random teams).

MWC: In the Mountain division, the hands-down favorite is Air Force. The Falcons are currently a 10.7-1.3, which is an incredibly high record. Air Force is not the only high-caliber team; Boise State is currently a 9-3 team. In the West Fresno State is currently 9.9-2.1.

CUSA: In CUSA (which takes the two teams with the best record), the top four teams are UAB (9.3-2.7), FAU (8.5-3.5), and Western Kentucky (8.1-3.9), and UTSA (8.7-3.3).

SBC: The only team ZeLO sees as a legitimate competitor in the West is Louisiana, with a record of (8.7-3.3). The East is a little more competitive, with Appalachian State potentially breaking nine wins. Coastal Carolina and Marshall are both eight-win solid teams. 

AAC: The AAC is by far the most robust Group of 5 Conference, with household teams like Cincinnati (10.2-1.8), Houston (10.4-1.6), and UCF (8.8-3.2). Memphis (8-4) and SMU (8.2-3.8)

Tom Zwiller

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I built a college football model. Here’s how it works

Credit: Tom Zwiller

For those of you who have read The Observer for the past few years, there is a good chance you have run into my NFL model, which is predicated on the idea that instead of simply measuring wins and losses to rate teams, we can observe what statistics tell us down to a micro level.

At the end of the spring semester, I was asked by our Sports Editor to try and create a version of ZeLO for college football. Eager to try my hand at a college football model, I quickly got to work until I realized it was impossible for two reasons. 

Firstly, trying to manage the rosters of 130-plus college teams is a task I’m not crazy enough to try, and people who have watched me run the NFL model already think I’m crazy (depending on the week, it can take me over ten hours to update ZeLO). 

For another, there isn’t the same level of data readily available. For my money, Pro Football Reference is the best stats website and the easiest to integrate into Excel. But as immaculate as PFR is, there are just some stats missing in the NCAA. The best example I can think of is passes targeted. The NFL has both receptions and targets, but college football lacks targets. 

So, between the lack of data and the sheer size of the project, I decided to move to a team-based model. With that decision made, the pieces began to fall into place. I grabbed each team per game stats, both for and against, ran them through a modified ZeLO formula and created a net metric.

The first thing that jumped out to me was that teams who had been good recently but had a down year last year were low (think Penn State) and teams that had been poor the year before but were good last year (Baylor) were projected to be too strong. This made me want to go back to years prior, run more data and create a weighted average based on recency (for example, the most recent year is weighted at 50% and the last year is 5%). I now felt a lot more comfortable knowing that a team who might have had an outlier year in one way or the other would still get credit for it, but at the same time, it wouldn’t be the only factor.

The next phase was adding a strength of schedule component. I created a scale based on the average schedule, and if a team had a more demanding schedule, their ZeLO for that year was multiplied by a decimal greater than one. If it was easier, it got multiplied by a decimal less than.

There was also the matter of roster turnover that needed to be addressed. With the NFL model, I manually address this by moving players as I follow free agency. But with a team model, I have to make more general assumptions about which players are leaving when players graduate or are drafted. So a good team last year, like Georgia, who lost over half of their returning production, will not return with as elite a defensive unit. 

Conversely, the matter of recruiting needs to be considered, as well. According to 247 Sports, over the past four years, Georgia has been a top-5 recruiting school, ranking first (2020) and second (2019) during that span. Suddenly, that reduction of their defense seems like an overcorrection. 

My solution was simple: I took247 247Sports’ average recruiting grade and multiplied it by .36 (the 36% was found here) and added the returning production metric and the new recruiting metric. 

So Georgia, who had a 73% offensive and 44% defensive returning percent, now has a return plus  recruit score of 1.06 on offense (a slight improvement) and a .775 on defense (a relatively large regression). These two numbers should account for returning production and the new class of players joining the team.

The last thing I wanted to incorporate into the model was a home field adjustment. Two components were critical to me. The first was the team’s home win-loss record, and the second was their average home attendance (adjusted for capacity to help protect smaller schools). I used a five-year average for both stats and calculated Z-Scores (a metric that shows numerically how close something is to the mean) for both stats. 

I took these two numbers and added them to a base of 10. So, if a team has a poor win-loss record, they will have a negative Z-Score (because they are below the mean), which would lower their home adjustment from 10. The same is true if they have below-average attendance. But the worst that could happen is a team drops to plus-four — still an advantage, but minimal.

I honestly have no idea how this project is going to go. When I first built my NFL model, I got to test it by myself first. I spent a week or two just tracking results and seeing if the player values made sense and didn’t jump around too much. It worked out well and I felt good about publishing it.

This college model is completely different; you and I are going to find out how good it is at the same time.

I built it and all the decisions made were intentional and well-thought-out. It back tested incredibly well last year — on average, the model was about a game and a half off of the actual finish. By the model, Georgia won the title and Alabama finished second, mirroring the results of the actual season. Always a good sign.

So, I hope you follow along and enjoy watching the season unfold as we track ZeLO against both real results and the ESPN FPI predictions.

Tom Zwiller

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