When it comes to franchises, sometimes you get a sequel, and sometimes you need a reboot.

For the 2026 Michigan State football team, a reboot was certainly required. In fact, fans would probably prefer to have the past few timelines purged from their memories, as if by a strange magician’s spell.

Mel who? Jonathan who? Never heard of them.

Instead, there is a new sheriff in town. He is a gruff Chicago native, built like a linebacker, who looks vaguely familiar. Didn’t that guy used to wear purple? New head coach Pat Fitzgerald wears the only colors these days, and he brings an old-school Big Ten mentality to this particular origin story. It all feels both familiar and refreshing in the friendly neighborhoods around East Lansing.

But Fitzgerald is not the only new face in East Lansing. The Spartans added 32 transfers and 30 incoming freshmen, enough new characters to fill a prequel and at least one confusing Disney+ series. Keep the roster handy Friday night when this new cast makes its debut.

As with any reboot, the central question is whether this new group can recapture the magic of Michigan State’s peak years. Will the Spartans show progress and a spark right away, or will fans have to wait for another sequel to learn whether the program is finally on the right path?

Perhaps new heroes will rise in 2026. Or perhaps the opener will leave Spartan fans not feeling so good and unsure what is happening. One thing is certain: It is a brand-new day for Michigan State football, and that new day brings a multiverse of possibilities.

Can Michigan State Avoid a Week 1 Upset?

Friday night will mark only the second all-time meeting between Michigan State and the Toledo Rockets. The Spartans defeated the Rockets 58-0 in 1925. A lot has changed in the ensuing century.

This version of Toledo should provide a much stiffer test. The Rockets begin the season No. 93 in my consensus poll, 27 spots behind Michigan State. The media picked them to finish third in the Mid-American Conference, behind Western Michigan and Miami (Ohio), and my preseason simulation reached the same conclusion.

The Rockets opened as 12-point underdogs, but the line quickly tightened to about 10 points. Historically, that spread gives Michigan State roughly an 80% chance to open the Fitzgerald era with a victory.

So will the Spartans notch their 46th win against a MAC opponent, or will they stumble for the seventh time in history against a team from that conference?

My algorithm sets the line slightly above the current market and just below the opener. I project an 11.5-point Michigan State victory, which suggests a play on the Spartans to cover.

My projected final is Michigan State 34, Toledo 22. That score also points to the over on the current point total of 49.5.

What to Watch in the Big Ten This Week

Table 1 summarizes the Big Ten’s Week 1 schedule.

It includes my predicted scores, opening lines, algorithmic spreads, ESPN FPI and SP+ projections, projected totals, and recommended picks against the spread and straight up.

Table 1: Big Ten Week 1 games and projected scores. Green shading indicates a cover projected by my algorithm; red shading indicates a cover projected by FPI.

All 18 Big Ten teams are in action. Four face FCS opponents, and all but four conference teams are favored by at least 20 points.

In general, the Week 1 results are unlikely to tell Big Ten fans much about the season’s trajectory. However, they may offer early clues about whether Michigan State’s future opponents are better or worse than preseason expectations.

Rutgers (-30.5), Illinois (-27.5), Nebraska (-23.5), Oregon (-24.5), and Washington (-21.5) are all huge favorites at home. If any of them fails to cover by a significant margin, Michigan State’s path could be easier than expected.

Northwestern (-12.5) could be tested at home by FCS power South Dakota State. SP+ projects a game decided by fewer than seven points, so a Wildcats upset loss would not be shocking. Conversely, a convincing Northwestern win could make Michigan State’s mid-October trip to Evanston look tougher than expected.

The computers’ collective spider-sense is tingling: All three models have issued an upset alert for UCLA (-2) at California. If the machines are right, one future Michigan State opponent may be weaker than expected.

Naturally, most Spartan fans will monitor Michigan (-26.5) against MAC favorite Western Michigan. Will Michigan look like the Big Ten’s newest supervillain, or merely another bumbling henchman following a stolen storyline?

Michigan State fans will have a chance to scout both teams on Sunday night when Wisconsin faces Notre Dame (-20.5) at historic Lambeau Field.

From the broader perspective of the Big Ten race, I am curious to see how USC (-23.5) performs against Fresno State. The Trojans were somewhat underwhelming in their Week 0 win over San Jose State, and the computers punished them for it. Was that an opening-game anomaly or has trouble already entered the Trojans’ cinematic universe?

Other Notable National Action

Table 2 highlights the most notable games beyond the Big Ten during the opening weekend.

Table 2: Other notable Week 1 games and projected scores.

Much of the country opens against light competition, but several Power Four matchups warrant attention.

Two games pair potential SEC contenders with possible ACC contenders: Clemson visits LSU (-9), and Ole Miss (-6.5) hosts Louisville. Both project to be competitive, so either an upset or a blowout would be significant.

Elsewhere in the ACC, I am curious to see how SMU (-1.5) performs at Florida State. The Mustangs are a conference contender, but my preseason analysis suggested an early road loss in Tallahassee could leave their title hopes hanging by a thread.

The remaining games in Table 2 highlight early tests for potential Group of Six playoff candidates.

The loser of the matchup between James Madison (-6) from the Sun Belt and Liberty of Conference USA will have a tough time making the case for a playoff spot. Another C-USA contender, Western Kentucky (-3), is hoping to build early-season momentum at Nevada. UNLV (-1.5) is looking to right the ship at Hawaii after a damaging Week 0 home loss to Memphis.

In the American Conference, Tulane could earn an early resume boost with a win at Duke (-10), while Pac-12 favorite Boise State has the potential to make an even bigger (but also unlikely) statement at Oregon (-24.5).

Two MAC games are also worth watching this weekend. Future Michigan State opponent Eastern Michigan (-4.5) is expected to face a tough test against San Jose State, which might be better than expected.

Just for fun, Bowling Green (-2.5) is on upset alert at home against FCS opponent Tarleton State.

Picks of the Week

Each week, I will share my computer’s latest projected margins for every game involving an FBS team. Over time, I have developed methods that turn those calculations into educated recommendations for upsets, spreads, and point totals.

If you are wondering whom to bet on this weekend, or in the weeks ahead, I am here to help. With much data comes much responsibility.

Figure 1 compares my computer’s Week 1 projections with the opening market spreads.

Figure 1: Projected margins from my algorithm compared with opening Week 1 spreads.

Each point represents one game. The opening spread appears on the x-axis, and my algorithm’s projected margin appears on the y-axis.

The two data sets agree broadly, with points clustering around the solid diagonal line. A point on that line means my algorithm exactly matches the opening spread.

Points above the solid line indicate that my algorithm favors the market favorite to cover; points below it favor the underdog. The two dotted lines mark the model’s betting threshold.

Across 15 years of tracking, I found that when my projection differs from the spread by more than 15.75 points, the model selects the team that covers at a meaningful rate.

When a point falls beyond either dotted line, the model triggers a recommended bet. Over the past nine years, those selections are 360-321 against the spread, a 52.9% success rate.

The vertical red line marks a spread of zero. Any point to its left represents a game in which my model predicts an outright upset.

Historically, the algorithm has correctly identified 43.5% of these upsets, compared with a 36% success rate using a random number generator.

Over the past decade, I have run a similar analysis using predictions from ESPN’s Football Power Index (FPI). This year, I am also adding predictions from Bill Connelly’s SP+ model.

This offseason, I reanalyzed the historical results from all three models and made modest adjustments to the criteria used to identify high-value spread, upset, and point-total picks.

Figure 1 provides the broad overview, but the recommended plays are easier to identify in the tables below, beginning with the upset picks in Table 3.

Table 3: Week 1 upset picks.

In total, the three algorithms predict only three upsets in Week 1, and the largest spread among them is less than three points. 

My algorithm and FPI project Hawaii to upset UNLV. My algorithm and SP+ project Tarleton State to upset Bowling Green. All three models predict California to upset UCLA.

A simulation of all 91 Week 1 games involving FBS teams produces an expected 8.7 ± 2.5 upsets.

Table 4 summarizes the recommended Week 1 bets against the spread.

Table 4: Picks against the opening spread for Week One. The picks are listed in order of confidence score.

For the first time this year, I am making predictions on games involving FCS teams. I am also using SP+ data to make picks against the spread for the first time.

That combination produced 13 Week 1 spread picks, 10 from SP+ alone. Ten also involve FCS opponents. Because this is relatively uncharted territory, I am treating those recommendations cautiously.

Among games involving only FBS teams, SP+ suggests taking Ohio State (-49.5) to cover against Ball State and Memphis (-10.5) to cover against Arkansas State. FPI recommends UMass to cover the 30.5-point spread against Rutgers.

My algorithm’s only recommendation is for Georgia to cover the 46.5-point spread against FCS opponent Tennessee State.

Finally, Table 5 provides the recommended Week 1 point-total bets.

Table 5: Recommended Week 1 point-total bets. 

After four years of generally poor results, I am rebooting my point-total strategy. My picks showed no correlation with SP+ selections, but I identified parameter ranges in which each model independently cleared a 50% success rate.

The revised system produced 22 total recommendations in Week 1: 16 from my model and eight from SP+, with two games selected by both.

Of the 22 total recommendations, only five involve two FBS teams. All five come from my algorithm, and four involve Big Ten games in which the pick is the over.

Specifically, my model projects Ohio-Nebraska, Michigan-Western Michigan, and Wisconsin-Notre Dame to each exceed 47.5 points. It also projects USC-Fresno State to exceed 51.5 points.

That is all the advice I have for this week. It feels good to be back in the swing of things. Until next time, trust your spider-sense, respect the numbers, and enjoy the games.