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Barnes Betting Report: Deep Dive, College Football Playoffs, Rose Bowl, Alabama vs. Michigan
December 14, 2023
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Deep Dive: Alabama-Michigan Playoff, Rose Bowl, January 1, 2024

  • Predictive Role of Talent in the BCS. A team in a title-deciding post-season game with more than 20 NFL players on their roster has never lost to a team with less than 20 NFL players on their roster in modern college football history. Excluding Saban teams, the team with a definite big talent edge in the BCS era (such as a 10+ edge in recruiting rankings) is 10-0 straight up and 10-0 against the spread, with every victory by double digits and an average margin of victory of 21 points. Saban’s teams with a big talent edge in the BCS era is a perfect 7-0, and 6-1 against the spread, with every victory by double digits and an average margin of victory of 18 points.
  • Predictive Role of YPP in the BCS. More predictive has been performance against similarly ranked offenses and defenses than overall season numbers which can be inflated. That said, only 1 offense outside the top 35 has won the title, and that was Alabama’s run-heavy Derek Henry led offense in 2015. Michigan’s offense is currently ranked 43rd in yards per play. Equally, only 1 team won a national title without a top-30 defense in yards per play, the 2010 Auburn squad, whose 3rd ranked offense and favorable BCS matchups won the title, as title-game opponent Oregon also featured a defense outside the top 30. A team with top-30 rankings in both offense and defense against a team without those rankings in BCS play was undefeated until Michigan lost to TCU last year, 12-1 straight up and against the spread in the semi-final round.
  • Talent. Alabama, consensus #1 ranked team in recruited talent, features 50 NFL prospects according to consensus recruiting rankings, including 7 offensive lineman, 3-deep at QB, 5-deep at running back, 8-deep at wideout, 8-deep on defensive line, 12-deep at linebackers, and 7-deep at defensive back. Michigan, consensus 14th ranked team in recruited talent, features 15 NFL prospects on the roster, including QB, 3-deep at running back, 2 wideouts, 4 offensive lineman (1 who is hurt and out), 4 linebackers, and 2 defensive backs. According to PFF grades and mock draft boards, Alabama features a half-dozen consensus top-50 NFL draft prospects, and Michigan none. Michigan’s best NFL prospects (aside from an injured offensive lineman) are QB McCarthy, RB Corum, TE Barner, LB Colson, LB Barrett, and DB Johnson. Alabama’s best NFL prospects include QB Milroe, WR Burton, WR Bond, OL Latham, OL Roberts, OL Booker, OL Proctor, RB McClellan, RB Williams, DL/LB Turner, DL/LB Braswell, DL/LB Eboigbe, LB Campbell, CB McKinstry, CB Arnold, CB Amos, DB Moore & DB Downs. Alabama triples Michigan’s talent level at each level, and is better at every position room.

Season Comparisons

Yard Per Play

Michigan Offense: 6.1, 43rd

Michigan Defense: 4.3, 4th

Alabama Offense: 6.4, 30th

Alabama Defense: 4.9, 18th

  • Michigan’s offense finished outside the top-40 offensively, around 6.1 yards per play, averaging 4.7 yards per play against top-20 defenses. Alabama’s offense finished in the top-30, despite facing much better defenses across the season, with a 6.4 yard per play average, and only dropped slightly to 5.8 yards per play against top defenses. Michigan’s defense finished in the top-5, though it feasted on poor offenses, facing only 1 offense in the top-40 all season, to whom it gave up their season average of 6.5 yards per play. Alabama’s defense finished in the top-20, giving up 4.9 yards per play, despite facing many top-30 offenses, to whom it gave up 5.7 yards per play, almost a yard below those team’s season average. A yard per play projection of Michigan’s season would project a yard per play deficit of 2 yards per play, or 20 points. A yard per play projection of Alabama’s season would project a yard per play edge of 1 yard per play, or 10 points.
  • Michigan’s Season. Many computer-driven power ratings, which struggle with inter-conference comparisons and to measure the ability to scale, will have Michigan favored over Alabama, and this will drive the Vegas spread in favor of Michigan, despite knowing the public will bet heavy Alabama. Michigan only faced one more talented team this season: Ohio State at home, the only top-50 offense they faced all season. Michigan gave up 6.5 yards per play to the Buckeyes in Ann Arbor, allowing Ohio State 100% of their season average. Michigan faced 4 top-20 defenses, including Penn State, Iowa, Ohio State, and Maryland. Michigan’s yards-per-play in those 4 matches were 5.3, 4.3, 5.6, and 3.3 yards per play, for an average of 4.7 yards per play.
  • Michigan’s History under Harbaugh: Of note, both poor performances against top-20 offenses or defenses fit Michigan’s patterns offensively and defensively under Harbaugh when he scales up in competition. Under Harbaugh, Michigan faced 25 top-20 defenses; his offenses never exceeded 5.6 yards per play in any of those matches, averaging the same 4.7 yards per play his offense averaged this season. Equally, Harbaugh’s defenses struggle to scale up, as his defenses faced 15 top-30 offenses in his tenure, and those offenses bested 5.6 yards per play in every single matchup, averaging 6.7 yards per play, almost identical to what they gave up to the only top-50 offense they faced this year, in what was considered a down year for the Buckeye offense (so much so, the QB entered the transfer portal already). Michigan scales down very well; it scales up very poorly. (In this regard, it’s much like Oregon’s 2023 team, another team Vegas’ power ratings badly misread in the post-season). Michigan away from home against a more talented team is 1-6 under Harbaugh, with a median loss margin of 21 points, including bad losses to more talented SEC teams in post-season play, such as a 19-point loss to Alabama, a 26-point loss to Florida, and a 23-point loss to Georgia. Harbaugh at Michigan with extra time to prepare against a top-20 foe is 0-8 straight up and ATS, including two losses to Saban’s Bama squads by margins of 19 and 27.
  • Alabama’s Season: Alabama faced 4 top-30 defenses, including Georgia, Texas A&M, Tennessee, and Texas. Of note, 3 of the 4 featured more defensive talent than Michigan, and Tennessee’s defensive talent is closer than most would realize. Alabama exceeded 5.6 yards per play in 3 of the 4 matchups, averaging 5.8 yards per play. Alabama faced5 top-30 offenses, 3 of whom feature more recruited talent than Michigan, and two are quite comparable, in LSU, Texas, Georgia, Tennessee & Ole Miss. Alabama’ defense gave up 5.8, 5.4, 5.7, 7.3, and 4.8 yards per play, for an average of 5.7 yards per play.
  • Alabama’s History under Saban: Excluding the Sarkisian offenses, this fits the pattern of Saban’s teams at Alabama offensively, which average 6.4 yards per play historically. Last year, Alabama’s offenses also averaged 5.7 yards per play against top-30 defenses. Of note, against other top-20 defenses historically, Alabama averaged a comparable 5.6 yards per play offensively, excluding the explosive Sarkisian offenses. Against highly ranked non-conference less-talented defenses in 14 matchups under Saban excluding the Sarkisian offenses, Alabama averaged over 7 yards per play, including dominating offensive performances against highly ranked Big 10 defenses.  Saban’s Bama record against the Big Ten and Notre Dame, excluding equally talented Buckeye squads, is 9-0, with the closest margin 16 points, and the median margin of victory 21 points. Saban against a lesser talented top-20 ranked foe, with more than 2 weeks to prepare (excluding bowl games with major opt-outs), is 23-0, with every win by double digits, and a median margin of victory of 21.
  • Matchups. With points out of the passing game in modern high-end college football, we'll focus on that. Alabama’s 4th ranked passing offense from a yard-per-play perspective goes against a defense that only faced 1 passing offense in the top 50 all season using that same metric, Ohio State. Ohio State had the same yards per play passing against Michigan in Ann Arbor that was their season average, 9.0 yards per play. Alabama faced 2 top-30 pass defenses, Georgia and Texas, and averaged 8.8 yards per attempt in those matchups. Michigan’s 14th ranked yard per play passing offense will be the 6th top-35 passing offense it faced this year; Alabama gave up 8 yards per attempt in those matchups. Against top-30 pass defenses, Michigan averaged 7.5 yards per pass attempt.  Both teams feature good run offense and run defenses. Michigan faced 4 good run defenses, Penn State, Iowa, Ohio State and Maryland, averaging 3.5 yards per rush. Alabama equally faced four top-30 run defenses in Texas, Tennessee, Texas A&M, and Kentucky, averaging only 3 yards per rush. Bama squared off against six good run offenses in LSU, Tennessee, Georgia, Auburn, Kentucky, and Texas, conceding less than a 3 yards per rush. Michigan faced no run offenses in the top-40 in the country, with the closest being Penn State which managed 164 yards rushing on 4.7 yards per rush, as even QB Allar rushed for positive yards, a worrisome indicator for Wolverine backers against good runner QB Milroe. In terms of individual matchups, Alabama holds the edge at every single positional matchup as Milroe and McCarthy are comparble, Corum and Bama's backs are comparable, and Wilson and Burton are close, but the defenses are not, giving Bama a decisive individual matchup edge when comparing the two teams as units. This shows up in the comparable yards per play against comparable foes, where Alabama holds the edge up to 10 to 20 points over the course of a typical game. Whether the game will be typical is yet to be determined. 
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OFFICIAL PICKS: Monday, November 10, 2025

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2% GB -1.5 Eagles
*Note: pick is for the Packers to win by 2 or more; ok at any point below 3.

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Open until the end of the year, and pinned here.

Two Quick Draw Picks

1% Man City Vs Liverpool to draw at 25c (good to 28c)
1% Bologna Vs Napoli to draw at 30c (good to 32c)

Alright, here are two draws I'm on today. First is Man City Vs Liverpool. These two sides regularly played out crucial games for the top of the Premier League table in recent years and they often ended in draws. Liverpool have stumbled this year but I'm not convinced Man City should be heavy favourites in this fixture either. I got this down to below 23c with the synthetic draw.

The second fixture is Bologna Vs Napoli. 30c is getting into that territory where the edge is not going to be big but Serie A is a league which tends to have more draws than other top European leagues. I got this one down to 30c with the synthetic draw.

Although I recommended both picks at 1%, I personally took City Liverpool at 2% and I'll take Bologna Napoli at 2% if I can get filled at lower prices again. Let's see how these games go today!

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Thoughts on Last Night

Around around she goes; we she ends, nobody knows. Only truly beatable infinity, unless you believe in luck So The Good Thief lead character explains as he sees the ball chase around the roulette wheel. But it wasn't luck that lost me last night; it was failing to follow my own methodologies for the best decision making in the world of prediction markets.  

Many of my assumptions held (Mamdani bets cashed to a profit, the Democratic sweep happened, and Morris County flipped to Sherrill, while closest race was the Virginia Attorney General), but a big one didn't -- that 2025 would not bring a record-setting Democratic wave. The wave crested like a tsunami, felt coast to coast, from the northeast to the southwest, from the midatlantic to the mountains, from the industrial midwest to the southern countryside, effecting small town mayoral races in Pennsylvania to Public Service Commission statewide gigs in Georgia, from legislative districts with 36 year incumbents in ruby red Virginia heartland to the most revolutionary Mayor ever elected in New York City since Henry George's failed effort signaled the rise of Populism a century+ ago. Candidate quality did not matter. Candidate spending did not matter. Incumbency did not matter. Job approval did not matter. Scandals did not matter enough or did not matter at all. Get out the vote efforts did not matter. This was an angry electorate seeking vengance, and finding its expression wherever they could. 

That was my first mistake, and it was a mistake, rather than bad luck. I assessed the wave risk at 10%, when it was manifestly much higher. All I needed to do was listen to....myself. I went back and watched my last episode w/ Baris and an episode a few months ago with the Duran, the latter where I previewed a collapse in GOP support if Trump didn't escape the foreign focus & wars, delivering only to the donor class. I spoke often of the new MAGA that began to build in 2023 -- young, working class, often minority, deeply unhappy with the political direction of an elder class they are rebelling against, as easily tempted by left populism as right populism, and as easily susceptible to political apathy and agnosticism as engagement & activism. The shutdown was actually a negative tipping factor for these voters, as the SNAP issue played poorly with them, while enraging part of the Democratic base otherwise unenthused up to that point. I made two errors in methodology & one error in psychology I detail below. 

The second error was bankroll percentage. It was a single race in a single state; as such, keeping it closer to 5% made more sense than expending it to 34%, especially if more cognizant of the risk. It also shifted my stronger risk appetite onto others, and that was en error I usually well avoid. If I had listed every major election pick this year at 5%, we'd be in the black; even last night, splitting 5% bets amidst the 3 elections, would have only been a modest loss, given certain underdog bets hit with Mamdani. As I often say, but forgot here to practice -- bankroll discipline is the most important aspect of successful trading in the markets, sports or politics. 

The psychological error was getting attached to a pick, and not relooking at it from scratch anytime new information arives. A natural tendency is to stay committed to something merely because of prior committment rather than look at it completely anew, and being afraid of taking a loss when once vested in so much hope of a win. 

Areas to improve:

  • using the methodological approach of motivated reasoning -- you cannot make reason the master of motivation, but you can use motivation to master reasoning. The Elephant in the Brain. I needed to put myself in a position to take the opposite side of each pick, make the best argument possible for it, and then test it against the other side. In this respect, one way to best maximize this is to include substack-style articles on this site laying out the argument, and letting the community respond -- as several sagely warned in this case, which can dramatically improve the quality of reasoning;
  • tracking all data available -- for example, whether an off-year election could be a wave election that might have polls actually overstate the White House incumbent party that even the GOP the polls tend to be biased against & digger deep dives into possible explanation for a poll's results (for examply, Miyares surge was partly fog, by Democratic voters choosing undecided rather than voting against b/c they didn't want to admit they secretly supported the murderous texts of their Attorney General candidate; 
  • waiting until election eve and election day, especially in the US elections, as the volatility proffers the best opportunities, and the best information is then availabile if timely processed; 
  • finding a way to better track live-time data on election night by reemploying an older technique from my political campaign days -- prior to the election, predicting the expected % for each county (and key precincts when available) in terms of expected vote share & vote distribution, which can most accurately forecast where an election will go, to get ahead of the markets (the big models out there completely crashed last night, including the $250K new-and-improved Decision Desk model;
  • avoiding all bubbles & returning to getting into the head of a wide range of voting groups, something I long excelled in, but have to dedicate myself to these days due to inhabiting a political world more these days that can make me too responsive to criticism -- "hey Barnes, you're a panican; hey Barnes, your Barnes/Baris voter is mythical; you don't get it, Jack is a lock in New Jersey". I need to step into the minds of these independent voters, and keep listening to the independent podcasters who were a useful signal in 2024 and 2025 -- see how Andrew Stein, Tim Dhillon, Joe Rogan, Dave Smith, Theo Von -- all left Trump train in the summer of 2025;
  • staying within the 5% max recommendation on a single election in a single state unless extraordinary reason supported by extraordinary evidence recommends otherwise, and including the assumptions in those extraordinary picks such that the pick can be sold off quick if those assumptions show other signs in the data

Truth is, losses teach you more than wins. Despite as much as I try to track the underlying assumptions of winning picks, the stay-up-top-3-am reearching and obsessing motivation comes from tough losses. In addition, I learn the values of patience, forbearance, discipline, emotional equilibrium, self-belief, as well as better improving a sound methodological approach through "putting my money where mouth is" and sharing it with the world for public accountability and transparency improving decision-making skill over time, maintaining humility when the trap of hubris would otherwise ensnare.

After three decades of successful US elections, my setback in 2022 dramatically improved my analysis for 2024, proving fantastically profitable. Thanks to everyone for participating, hope you continue to partake in the community, and if I were a betting man, and I am, I would wager we will be profitable again, in matters of pocketbook, principle and politics very soon. 

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