College football statistical transition betting systems for 2023

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College football statistical systems

I hope you enjoyed last week’s College Football Personnel Transitional Systems piece on VSiN.com. It leads into this article, as I move from PERSONNEL characteristics to STATISTICAL characteristics in determining which teams are likely to improve or decline in 2023. I like to separate the pieces because, for one, it’s a lot to digest. And two, it’s really two different focuses, last week being on coaching and player personnel. This one being on some of last season’s statistical traits for teams that make them prime candidates for improving or worsening this fall.

 

Recalling some of my thoughts last week as to the foundation of this article series … One of the most difficult things about handicapping college sports is the process of evaluating teams from one season to the next. There are a lot of factors that can affect a team’s strength and or how much different they might wind up being from the season prior. You have to consider personnel losses, coaching changes, momentum lost or gained and many other factors. Sometimes the changes can be immense. Adding to the difficulty is the thought that many programs are taking players right out of their most recent recruiting or transfer class and plugging them in starting spots. The massive growth of the portal and assessing its immediate impact has only increased the challenge.

Over the last few years we have witnessed situations never seen before. The 2020 season was of course, the COVID-19 season, and that featured few to no fans in the stands, players and teams opting out and major modifications to every team’s schedule. In 2021, we saw the impact of “super seniors” and the most returning experience to the field that we’ve ever encountered. For 2022, the experience factor took a huge hit, as those super seniors were gone for the most part, leaving behind veteran but inexperienced players who otherwise would have benefited from starting roles. That had sort of a return-to-normalcy effect on college football. Other than the transfer portal expansion, we are as close to pre-COVID-era norms as we’ve been. We’ll see how it plays out in the upcoming season.

What I have sought to do in recent years in addressing the difficulty of massive year-to-year change in college football was to try to quantify the signs of potential improvement or decline out of teams when considering some year-to-year transitional situations. Last week I looked at personnel factors, many of which make up my College Football Stability scores. This week I dive into statistics from the prior season that can best forecast a team’s upcoming prospects.

Are there any revealing statistics from prior season that can predict the coming season?

Sometimes teams just catch consistently good or bad breaks throughout a season that impact their record and spread success significantly. Let’s dig through the data to see if we can find anything of this nature that might help us find some strong fade or follow teams for 2023.

·         There have been 55 teams over the last 10 seasons that have endured losing seasons despite outscoring their opponents. Of those, 21 of them brought back 13 or more starters, including their quarterback. The collective improvement of this group of teams was about 14.2% SU. These teams combined to go 53.1% ATS.

Potential improve teams for 2023: Kansas, Oklahoma, Texas A&M, UNLV

·         Alternatively, there have been 50 teams over the last 10 seasons that have enjoyed winning seasons despite being outscored by their opponents. Of those, 12 of them brought back 13 or fewer starters and turned to a new starting quarterback. Only one team improved (by one win) and the collective decline of this group of teams was a drop-off of about 15.9% SU.

Potential decline teams for 2023: Ball State, Purdue

Naturally, turnover luck is an easy-to-recognize opportunity for spotting teams capable of improving or in danger of falling from season to season. For the last 10 seasons, teams that had a turnover ratio of -1.0 or worse per game improved by 13.7% winning percentage the next season. Those that were in the -0.1 to -0.9 range improved by 4.2%. On the opposite side of the coin, teams with a turnover ratio of +1.0 or better dropped by 13.6%, while those in the +0.1 to +0.9 range were about 3.6% worse the next year. Of course, with this much straightforward data, we must dig further.

·         Over the last eight seasons, 16 teams have managed to go .500 or better against the spread despite having a -1.0 or worse turnover differential per games. Of those teams, 13 bounced back to improve the following season, improving by more than 20% and winning 3.0 more games on average.

Potential improve team for 2023: Akron, Rice

·         In the “there’s nowhere to go but up category,” since 2013, 45 teams have won two or fewer games in a season while enduring a -1.0 or worse turnover ratio. Only three of those teams got worse, while the average win improvement was 2.0 per season. The SU win % upgrade was 19.2%, and the ATS improvement was 16%. Despite the mistake-prone play, the most dramatic improvement came from teams that brought back 15 or more starters. That group of 23 teams improved by 4.5 wins per season, 26.8% SU winning percentage and 25% ATS!

Potential improve team for 2023: Akron

·         There is a potential landmine system that has affected teams coming off a season in which they enjoyed a positive 1.0 or better turnover differential but are now starting fresh at quarterback. The 32 most recent teams that have fit this bill have dropped by 1.7 wins per season in the next season, representing a 20.8% plunge outright and 11.7% dip ATS. This angle affected Louisiana and Nevada in 2022, and both teams dropped by at least six wins each!

Potential decline team for 2023: Illinois

·         It can easily be argued that the teams that got the “luckiest” in the prior season were those that had the best turnover differentials combined with smallest point differentials. It can also be predicted that these teams are due for a fall when “starting over.” Historically that is the case, as only one of the last 17 teams to have a TO differential of +1.0 or better and PPG differential of +12.0 or less with 14 or fewer starters returning went on to improve their winning percentage the next season. The average decline of this group was 2.8 wins per season, for an average percentage drop of 20.2% outright and 6% ATS. Collectively, they were 45.9% ATS.

Potential decline team for 2023: Illinois

Analyzing the quality of wins and losses from the prior season

You will find a lot of prognosticators who tout close wins or losses as motivation for a team heading into the next season. I’ll take a look at that as well as blowout wins and losses. I define close wins/losses as seven or fewer points and blowout wins/losses as 20 or more points.

·         Experienced teams have shown a penchant for bouncing back. Coming off seasons in which they lost at least six games by 20 points or more, teams with at least 14 returning starters have wiped the slate clean enough to improve by 2.2 wins per season. This represents a 18% improvement outright and jump of 22.9% ATS. There have been 49 of these such teams over the last decade and only five got worse.

Potential improve teams for 2023: None. Two teams met the loss criteria (Florida International and Colorado), but neither brings back enough experience.

·         There have been 80 teams over the last 10 seasons that have lost one or fewer games by 20 points or more in a given season but still finished with a losing record. Of the 45 that brought back 14 or more starters the next season, only seven finished worse the next season. The average win improvement of this group was 2.9 per season, good for a 18.5% jump outright and 7.4% bump against the spread.

Potential improve teams for 2023: California, Iowa State, Navy, UTEP, Texas A&M

·         There have been 31 teams over the last eight seasons that started a new quarterback after a season in which they finished with a winning record despite suffering three or more losses of 20 points or more. Only seven of those 31 teams finished with a better record the next season, with the average drop being 14%, or 2.4 wins per season.

Potential decline teams for 2023: Purdue

·         As another sign of experienced teams being able to wipe the slate clean, only nine of the last 71 qualifiers that failed to record a blowout win of 20 points or more and are bringing back 16+ starters got worse the next season. The average win gain was a whopping 2.7, good for a 16.1% bump. This group also recorded a 52.5% ATS mark.

Potential improve teams for 2023: Miami (Ohio), Sam Houston State

·         There have been 14 teams that have recorded seven or more blowout wins of 20 points or more one season then had to change coaches for one reason or another. Only ONE of the 14 teams got better the next season, by an average of 19%, or 2.7 wins per season.

Potential decline team for 2023: None

·         Close losses can be a galvanizing factor for teams that stay the course. In fact, of the 24 teams over the last nine seasons that suffered five or more close losses of seven points or less and brought back their head coach and at least half of their starters (11+), only two finished worse the next season. The average win improvement was 2.6 per season, representing a 20% jump.

Potential improve teams for 2023: Akron, Appalachian State, California, Georgia State, Iowa State, Navy, Nebraska, Oklahoma, Texas, Texas A&M

·         Not being tested by close losses can be a warning signal for inexperienced teams on the verge of dropping. There have been 45 teams over the last 10 seasons that won nine, 10 or 11 games while suffering zero or one close losses of seven points or less and brought back no more than half of their starters (11). Of these, only five teams won more games the next season, with the average win drop being 3.4 per season, a 22.2% SU slide accompanied by a 11% ATS drop.

Potential decline teams for 2023: Eastern Michigan, Marshall

·         Close wins are often characterized as getting “lucky” over the course of a season. Well, teams that have a lot of them and then come back inexperienced are naturally expected to drop. Over the last 10 seasons, 28 teams brought back 12 or fewer starters from a team that was fortunate to get five or more close wins of seven points or fewer in the prior season. Only ONE of these teams finished better the next season, with the average win drop being 3.0 per season, a 18.2% plunge.

Potential decline teams for 2023: Bowling Green, Houston, TCU, Troy

·         Subpar teams that experience zero close wins in a season also tend to improve, particularly when choosing to stay the course. In fact, since 2013, there have been 32 teams that finished under .500 and had ZERO close wins of seven points or fewer in the prior season, then brought back their starting QB, at least 12 total starters, and their full coaching staff (HC, OC, DC). Of those, 26 finished better the next season. The average win bump was 1.7 per season, a 21% surge.

Potential improve teams for 2023: Massachusetts, Oklahoma