Week 15 brings one of the strongest top-heavy slates of the season. Across all 16 matchups, several games graded with enormous model edges and overwhelming cover probabilities, while others required deeper EPA and yardage context from the CSV adjustments to separate lean from value.

This week brings 14 matchups, and while several favorites sit atop strong probability cushions, the middle tier is where things get tricky. We lean on the same process every week:
simulation cover percentages → model vs. market edges → CSV efficiency summaries.

Let’s get straight to the rankings.

Another NFL week, another deep dive into simulation outputs, market edges, and CSV-validated EPA/Yardage trends.
This week produced several monster mismatches—some obvious, some hidden beneath the surface—and a handful of underdogs who quietly profile far better than Vegas expects.

Week 12 brings one of the strongest top-tier slates of the season. Several matchups show massive gaps between the market numbers and modeled efficiency, and the bottom of the board gets extremely tight — exactly the type of week that separates contenders from pretenders in confidence pools.

Momentum defines November football. The model blends full-season EPA data, recent 3-week trends, and market deltas to produce a truer measure of value.

Week 10 is here, and the matchups are starting to separate pretenders from contenders. This week’s board brings a few heavy favorites with sneaky value, a handful of volatile lines worth treading carefully, and one underdog that jumps off the page. Below are the confidence rankings for every game, followed by my favorite upset pick and a 3-leg moneyline parlay built around stability and value.

Every week, I run my simulation model not just to test its accuracy — but to climb the leaderboard in my NFL pick’em league. The season’s long, the margins are thin, and the coffee is strong. This analysis breaks down every matchup against the spread (ATS), ranked by confidence, all grounded in EPA data, market adjustments, and the ever-humbling lessons of recent form.

Fresh week, fresh chaos. The slate’s wiped clean and the model’s recharged — fueled by Week 8 simulations, market swings, and a few late-night adjustments that definitely weren’t made after two cups of coffee. Below is the board, ranked by confidence (13 → 1), plus this week’s Underdog Pick and a 3-Leg Moneyline Parlay built purely on value and questionable self-control.

My picks are trending up. I am only a few points out of first place in my league. Stay with me folks, we are going to do this.

This week’s rankings blend model probabilities with real-world context — recent EPA swings, market corrections, and team momentum — to produce a truer reflection of confidence.

The simulations and market adjustment models are fully aligned heading into Week 6, giving a clear sense of which spreads carry real edge and which should be avoided. Below are the ATS confidence rankings (15–1) based solely on your document’s adjusted projections and summaries.

We’ve hit Week 5, and the simulations are now blending preseason expectations with in-season adjustments. That means the model is sharper, but I still keep my balance of 80% data and 20% instincts — factoring in efficiency trends, roster health, and locker room psychology.

Below are my ATS confidence picks for all 14 games this week, plus my favorite value moneyline parlay and the underdog to circle.

Three weeks into the season, we’re starting to see who’s for real and who’s headed for trouble. My process stays the same: lean on the simulation model (thousands of game iterations using minimax logic), then layer in real-world adjustments — offensive/defensive efficiency, injuries, roster stability, and the always underrated locker room toxicity factor.

For me, it’s still 80% data and 20% instincts. The sims narrow the board, but that last layer of context is what gives these picks real confidence.

Two weeks in, and we’re starting to see which teams are settling into form and which ones are still trying to figure out who they are. That’s why I keep leaning on my simulation model as the backbone of my pick strategy. It runs thousands of plays per matchup using minimax game theory, but I don’t stop there.

I layer in real-world adjustments based on Week 1 and Week 2 performance: efficiency metrics (EPA/play, yards per play), roster health, and even the “locker room toxicity” factor that doesn’t show up in spreadsheets but always shows up on the field. For me, it’s still that 80% data, 20% instincts mix that makes the difference.

Here’s how I see the Week 3 slate shaking out.

Week 1 of the NFL season gave us plenty of chaos — surprise performances, rookie jitters, and more than a few teams who already look like they need therapy sessions in the locker room. That’s why I take my simulation results and layer in real-world adjustments from the opening week.

My approach is still 80% data, 20% eye test. The data comes from a minimax game theory simulation that runs thousands of plays for each matchup. The eye test comes from me checking for roster health, coaching tendencies, and my favorite psychological factor: locker room toxicity. If a team looks fractured, I adjust their projection down regardless of how good the numbers look.

With that in mind, here’s how I’m attacking Week 2.

Every year, my friends and I play in a “pick ’em” league. It’s simple: you pick every NFL game against the spread, then assign confidence points (16 down to 1). If your pick hits, you earn that many points. Bragging rights and season-long glory are on the line.

This season, I’ve added a twist: I’m using a minimax game theory simulation (yes, the same kind you see in AI research) to model offensive/defensive strategies and simulate 2,000 games per matchup. It helps cut through noise, find the best ATS edges, and spot value on moneylines and totals.

College athletics was once defined by regional rivalries, underdog stories, and a sense that any program could rise to national prominence with the right mix of talent, grit, and coaching. Today, that balance is eroding. A small group of wealthy schools continues to surge ahead, while smaller programs struggle to remain relevant. The driving forces include massive media contracts, the transfer portal, and explosive NIL growth. These shifts reward the few at the expense of the many.

I’ve been working behind the scenes on a new way to analyze NFL games using game theory and data-driven strategy. Instead of just guessing, I’m applying the minimax principle — the idea that each coach calls plays to protect against the worst-case scenario — and combining it with EPA (Expected Points Added) from thousands of real plays (2022–2024).

This approach builds “matchup matrices” that show how offenses perform against specific defensive looks, then runs 2,000 full-game simulations to see how those tendencies scale up. The DAL vs PHI example? Both teams’ minimax move was to attack deep, but PHI’s deep passing proved far more consistent, leading to a 67% win probability in the sim.

In the mythology of the National Football League, nothing seems more important than winning the Super Bowl. A single championship can immortalize players and coaches. But from a business standpoint, a different truth emerges. The real winners—in terms of revenue and fan engagement—are often the franchises that consistently reach the postseason, even without frequent championships.

For small colleges, enrollment isn’t just a metric — it’s the scoreboard. When headcount drops, everything from tuition to team morale takes a hit. You can overhaul programs, rebrand your website, or hire a consultant. But one of the most direct and often overlooked strategies?

Athletics.

Not just as a recruiting tool — but as a full-on enrollment engine. If you're not leveraging sports strategically, you're missing one of the best opportunities to grow your campus and stabilize your bottom line.

I’ll be honest — when USC and UCLA announced they were heading to the Big Ten, my first thought wasn’t “tradition is dying.” It was:
“This is textbook game theory.”

College football has become a boardroom game. Universities are the players. The stakes? Media money, NIL power, and long-term survival.

We’re not just watching schools change conferences. We’re watching them make calculated, strategic moves in a system that now rewards consolidation over culture. And now that the Pac-12 has disbanded, it’s clear: the game isn’t regional anymore — it’s national, and it's ruthless.