College football systems that predict improvement or decline
Following up last week’s piece on College Football Stability, I like to take the stability data and combine it with key stats and other tidbits from the prior season to highlight systems that have predicted potential improvement or decline in the past. If you recall, I did something similar for pro football a couple of months back.
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College sports present some different challenges from the pros in that there is typically much greater turnover in rosters and coaching staffs from one season to the next. Evaluating these changes properly is one of the most crucial aspects to season-long success for bettors. 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 change is immense. Adding to the difficulty is the thought that many programs are taking players right out of their most recent recruiting class or transfers and plugging them into starting spots.
The last three seasons have presented some new variables, due to the COVID-19 pandemic and the super senior eligibility rules that are still working their way through the system. But what I have sought to do in recent years was to try to quantify the signs of potential improvement or decline out of teams when considering some year-to-year transitional situations. All of the things that come into play in this piece were factors in my College Football Stability Scores. After identifying some key criteria for each of the factors, I went back and looked at teams from recent seasons fitting certain criteria to determine their average improvement or decline.
Admittedly, the fact that the number of teams qualifying for these various systems has wavered tremendously over the last few seasons has skewed the statistics. However, I view the methodology as most important and don’t believe the fundamental logic has changed based on the unusual circumstances of the last few years.
As you will see from my findings, there are a number of obvious reasons why teams have gotten significantly better or worse from one season to another. Taking this a step further, I am using my findings to spotlight some teams to watch in 2023. Hopefully this will give you a foundation on which to start a successful handicapping run this season, both in terms of game-by-game handicapping and in attacking season win total props.
The data I used dates to the 2013 season, or the last 10 seasons.
Next week, in part 2 of this miniseries, I will address some STATISTICAL transition systems that the 2023 teams fit into.
Analyzing Number of Returning Starters
Just looking at the sheer number of returning starters on a team can provide great clues. Here are some of the systems I have discovered and have continued to track annually:
· Over the last 10 years, 115 teams have had at least six fewer returning starters than the prior season, and only 28 of them have improved that season. The average drop-off was a winning percentage decline of 12.5% and ATS drop of about 4.0%.
Potential decline teams for 2023: Bowling Green, Kent State, NC State, Old Dominion, South Florida, Stanford, TCU, Troy, UAB
Note that there were 38 on this system for 2022, about four times more than this season because of the super senior rule from 2021.
· Alternatively, of the 116 teams over the last 10 years that brought back at least six starters more than the prior season, only 36 got worse, although half of them came from 2021 when most teams had a greater percentage of their starters back. The average improvement of this group was a winning percentage bump of 9.7% and ATS rise of 4.7%.
Potential improve teams for 2023: California, Coastal Carolina, Duke, Hawaii, Iowa State, Navy, Nevada, Texas A&M, UCLA, USC, Wisconsin, Wyoming
The 2022 list of four teams was less than half of usual because of the massive loss of veteran players after 2021. This year’s list returns to normal numbers.
· The total number of starters returning has also proven to be a great predicting factor, as there have been 163 teams in the last 10 seasons that returned 10 or fewer starters, and only 36 have improved their winning percentage. The average drops for this group were 11.9% in win %, and 3.5% in ATS %. The combined ATS mark of these teams was 915-1048 ATS, or 46.6%, a clear play-against group.
Potential decline teams for 2023: Alabama, Arkansas, Buffalo, Charlotte, Cincinnati, Colorado, East Carolina, Indiana, Kent State, Lafayette, Louisiana-Monroe, Liberty, New Mexico, Old Dominion, South Carolina, Stanford, TCU, Tulsa, UAB, Utah State, Western Michigan
· The opposite group of that last system is those teams that return 16 or more total offensive & defensive starters in a season. That group has included 316 teams over the last 10 seasons and only 97 (30.6%) have recorded a worse won-lost record. The average improvement was a bump of 8.8% outright and 3.1% against the spread.
Potential improve teams for 2023: Army, Auburn, California, Connecticut, Duke, Florida Atlantic, Florida State, Iowa, Jacksonville State, Kansas, Miami, Miami Ohio, Navy, North Carolina, Ole Miss, Oregon, Penn State, South Alabama, Sam Houston State, SMU, Temple, Texas, Texas A&M, Texas Tech, Toledo, Texas-San Antonio, UCLA, USC, Utah, Wisconsin
What does a returning starting quarterback mean?
In a generic sense, returning a starting quarterback has meant an increase of about 2.0% in winning percentage. However, oddsmakers seem to place an emphasis on this fact, as there is an average decline in ATS winning percentage. Still, these teams have covered about 50.4% of their games, so in the end, it is still advantageous to back teams with returning QBs. Before last season, there was a lofty number of 78 teams that brought back their starting quarterback, and 42 of those held par or improved, while 36 wound up with lesser records than in 2021.
On the other hand, teams with a brand-new quarterback see their records drop by 3.4% on average while covering just 49.1% of point spreads. The outright winning percentage figure has been falling in recent years, thanks in large part to experienced transfers joining new programs. Let’s dig deeper to see if we can uncover more.
· Since 2013, there have been 71 teams that brought in a new starting quarterback and four or fewer total offensive starters. Of these, only 18 teams improved, and the average decline was an 11.8% decrease in winning percentage. Combined ATS% was just 47.4%.
Potential decline teams for 2023: Central Michigan, Charlotte, Cincinnati, Eastern Michigan, East Carolina, Fresno State, Kent State, Old Dominion, Stanford, TCU, Tulsa, UAB
· The opposite group of above is one you’re going to going to want to keep track of for backing in 2022. Teams with a returning starting quarterback as well as at least nine other offensive starters have shown great improvement, about 11.5% on winning percentage and 4.2% ATS. Collectively, these 75 teams have gone 51.5% against the spread over the last 10 seasons. Over the last two seasons, however, these teams have gone below .500 ATS, with 28 teams, far more than usual, qualifying. Something to watch going forward.
Potential improve teams for 2023: Duke, Kansas, Texas, Texas A&M, Texas Tech
· There is a dangerous assumption made about teams bringing back a starting quarterback from what was an explosive unit to an otherwise relatively new offensive group. In fact, teams that scored 40+ PPG the prior season and return the starting QB and four or fewer other starters have DECLINED by 2.9 wins per season on average and by 11.2 PPG. The combined ATS winning percentage of these eight teams was only 35.1%! (40-74 ATS). In 2022, just one team qualified, Coastal Carolina, and the Chanticleers dropped by two wins while going 4-9 ATS. For 2023, unfortunately, no teams will test this system, with Arkansas coming closest, having averaged 32.5 PPG last year.
Potential decline team for 2023: NONE
· Teams returning a starting quarterback for at least his third straight season as starter show nice improvement usually, typically by about 3% winning and 1.0 PPG. When you add the same head coach/offensive coordinator to the recipe along with at least eight other total offensive returning starters, the improvement jumps by 10.1% in won-lost record per season and 51.9% ATS combined.
Potential improve teams for 2023: Iowa, Kansas, Ohio, Texas Tech
• One of the biggest improvements in wins from one season to the next comes when nine or more offensive starters, including the quarterback, return from a team that won 33% or less of its games against the spread in the prior season. The average win increase is 16.5% SU and 25.5% ATS. These teams score nearly 6.0 PPG more as well and combined to go 53.1% ATS.
Potential improve teams for 2023: Miami, Ole Miss, San Jose State
• On the opposite side are the teams that are coming off of seasons in which they won 66.7% or more of their games against the spread and have six or fewer offensive starters returning, plus are breaking in a new quarterback. The 31 teams that have fit that bill have dropped by 17.6% outright, 19.1% ATS and 5.5 PPG offensively. (The five teams that added a new head coach plummeted by 5.8 wins per season, but no one qualifies for this in 2023).
Potential decline teams for 2023: TCU, Tennessee
What impact does a new coaching staff have?
One of the biggest factors affecting team stability from one year to the next is the status of a coaching staff. New head coaches or coordinators on either side of the ball can change a team’s fortunes dramatically. It’s not always negative, however, as it depends on the combination of coaches and player experience. Take a look at these recent results.
· Entire new coaching staffs (HC, OC, DC) combined with a new starting quarterback and 11 or fewer total starters returning is a very unstable situation, and certainly not a winning recipe in college football. This group of 29 teams over the last 10 seasons has seen its winning percentage drop by 9.9% on average, and these teams have collectively gone just 38.4% SU & 40.5% ATS. You’ll see below that there are nine programs qualifying on this angle for 2023.
Potential decline teams for 2023: Charlotte, Cincinnati, Colorado, Kent State, Purdue, Stanford, Texas State, Tulsa, UAB
· Clearly there is major room for improvement when a team wins 25% or fewer games in the prior season, but some of the biggest improvement is realized when these teams bring back their starting quarterback AND hire a new head coach AND coordinators. Over the last 10 seasons, the average winning percentage increases of the 54 teams that have done this have been 15.7% SU and 14.3% ATS. In fact, last year, Temple improved by 50% ATS year to year.
Potential improve team for 2023: South Florida
· Offensive coordinator changes when combined with little experience returning is also a trouble sign. Over the last 10 seasons, 61 teams have hired new offensive coordinators the same season they had five or fewer offensive starters returning and a new quarterback. These teams have declined by 13% on winning percentage and 3.8% ATS. They collectively have gone just 42.7% ATS, making them a strong play-against group. The average scoring output dropped about 4.6 PPG.
Potential decline teams for 2023: Alabama, Arkansas State, Charlotte, Cincinnati, Colorado, Fresno State, Georgia Tech, Houston, Kent State, Louisville, Notre Dame, Old Dominion, Stanford, Tennessee, Tulsa, UAB
· Defensive coordinator changes and inexperience is also a recipe for trouble. Of the 122 teams that have changed D-coordinators in a season and brought back five or fewer defensive starters, only 37 teams have improved their won-lost percentage. The average decline was 8.9% on winning percentage and 4.0% ATS. These teams have covered only 46.0% of their point spreads and allowed 2.9 PPG more.
Potential decline teams for 2023: Alabama, Appalachian State, Arizona State, Baylor, Bowling Green, Buffalo, Colorado, Georgia Southern, Kent State, Marshall, Mississippi State, New Mexico, Purdue, Stanford, Texas A&M, Tulsa, UAB, Utah State, Washington State
