Welcome to the first week of this analysis. If you haven’t read my analysis on the same topic for last year’s playoffs you can read that here: Who played the best in the FCS? – An analysis of the FCS Playoffs

I’ll be doing sort of a similar thing for this week of FCS but instead, I’ll be showing the charts first and then taking a few games and doing analysis. Any takes or overall analysis will be at the end.

Here are a couple of games that I feel deserve a look under the microscope:

Jacksonville @ Houston Baptist | 24-17 HBU

Yard difference: +118 Jacksonville

Point difference: +7 HBU

Average diff (HBU on offense): 419.7 (+44.7 away from 375)

Cumulative difference gap: +4069 (JU favor, 91 plays)

Of all the games to have a different actual winner from the diff winner, this one had the greatest gap. Both former Utah bois (AP and Jags) won their game but lost in diff, with AP narrowly topping the other Utah team in Dixie State. The HBU-JU game didn’t even finish, and 4069 is a miraculous diff to have someone accumulate against you yet still come up with a win. Jacksonville runs the spread and accumulated many more yards, which makes sense given the -1 TO margin. JU was able to chunk off consistent yardage to score (or TO once, or FG, or punt), but HBU got the big 40 or 45 yard gains. It brings up an interesting question, assuming the results don’t matter, who should be more proud? The person who overcomes the diff gap, or the person who consistently owned the opponent.

Duquesne @ South Dakota State | 40-37 SDSU

Yard difference: +54 SDSU

Point difference: +3 SDSU

Average diff (SDSU on offense): 376.3 (+1.3 away from 375)

Cumulative difference gap: +168 (DUQ favor, 133 plays)

This game was incredibly close both in diff and in score, and SDSU came back to score 22 in the final quarter. For it to be so close after 133 plays (on the way higher end of plays for a game) really speaks to the evenness of this match. SDSU was North Dakota last year so this is some much-deserved comeuppance for all the many, many close and unfortunate losses in his ND campaign. Duquesne was +2 in the TO margin but only had 61 of the 133 plays, it appears they didn’t risk it enough when they were in possession to take advantage of their slim diff lead.

Idaho State @ Northern Iowa | 34-21 UNI

Yard difference: +40 UNI

Point difference: +13 UNI

Average diff (UNI on offense): 364.4 (-10.6 away from 375)

Cumulative difference gap: -1252 (UNI favor, 118 plays)

I thought I would cover this game as it was technically Gameday (Gotta order more than just rings if you want your Gameday to be considered). 10.6 diff in your favor every play isn’t a massive advantage, that’s maybe the difference of a yard in smaller plays, and maybe 5 yards in larger ones. However, this game goes to show how and average like this can pile up. UNI also attempted a field goal at the end of regulation but was unable to tack on an extra 3. That UNI defense is almost as killer as the Hannen wifi.

Youngstown State @ Bryant | 114-49 Bryant

Yard difference: +103 YSU

Point difference: +65 Bryant

Average diff (Bryant on offense): 366.3 (-8.7 away from 375)

Cumulative difference gap: -1437 (YSU favor, 166 plays)

This game was Bryant’s first win, it’s just unfortunate that it was from a double dipper and against a double dipper. VFB has been known for massive scoring games so this wasn’t out of the ordinary, but the fact that YSU won the diff game alludes to the fact that if Joe (the YSU coach for the game) didn’t give in to VFB’s way of playing he could have actually won. The other thing is that it helps show why VFB was able to trounce teams in FBS, because he doesn’t need to win that diff game. YSU owned the yards, but he turned it over 10 times because of his 2-752 gameplay (high risk, high reward). The last thing that’s very interesting was that both teams had exactly 83 plays on offense, and they had similar ToP, it was close enough that YSU’s +103 yard differential was enough to win him the diff battle, but not the game.

Georgetown @ Bethune-Cookman | 53-17 BCU

Yard difference: +58 BCU

Point difference: +36 BCU

Average diff (BCU on offense): 332.0 (-43.0 away from 375)

Cumulative difference gap: -5120 (BCU favor, 119 plays)

This game had the second-largest cumulative diff gap behind the Montana-Dartmouth game, but this one was very large and it’s a good ASun story (the tendrils of ASun media influence continue to grow much like Atl. United’s did when they joined MLS). Anyway, given the playoff article, I said that (on average) every 140.1 diff gap would translate to +1 MoV. BCU did that almost exactly with their diff gap putting them on pace for +36.5 in the MoV. They didn’t destroy the yards game but the +3 in TO margin gives you enough reason to suspect why that is. You only need short fields every so often to cut down on your drive lengths. BCU had fewer offensive plays, but more ToP despite running the Pro to Georgetown’s Option. Everything points to BCU taking advantage of the opportunities they created, but also making those opportunities plentiful. An all-around domination of the brand new coach, Georgetown.

Analysis

So before I go into game specifics, here are some bullets for overall analysis.

About 30.3% of teams that lost the game ended up winning the diff battle (What I’ll be calling diff upsets). This is a stark difference from the playoffs last year where 4.3% of teams that lost the diff battle went on to win the game (Cal Poly v. Princeton).

7 games had the cumulative diff gap within 500. Of those seven, 5 of them were diff upsets.

Of all the teams that were diff upset (the teams that won the diff battle but lost the game), the CAA had the most teams with diff upsets (25%) and the Southland had the fewest (0%). CAA – 3 of 12 – 25.0%

Big Sky – 3 of 14 – 21.4%

AE – 2 of 12 – 16.7%

CFC – 2 of 12 – 16.7%

ASun – 2 of 14 – 14.3%

DIC – 2 of 16 – 12.5%

Ivy – 1 of 8 – 12.5%

MAAC – 1 of 12 – 8.3%

MVFC – 1 of 14 – 7.1%

Southland – 0 of 14 – 0%

You can notice a trend that the further down you go, the fewer games have a diff upset. That likely can be attributed to more teams completing their games near the bottom, and those teams are much quicker (as the list is from last to first completed).

Specific analysis on a per-team basis:

William & Mary was winning the diff battle after 21 plays by over 2000 diff gap. That’s a pretty great diff gap throughout an entire game, but over 21 plays it means that on average he was getting a 278 diff on offense and 472 diff on defense. And immediately afterward 3 DoGs for a forfeit. Since DoGs aren’t counted into diff, it means he won the diff gap by -2030 but lost 23 to 7.

South Dakota vs. Missouri State did count as both technically had a drive. The game was 7 plays total and that’s why it’s a 41 total diff gap. For this reason, if you’re looking for the games that were closest, you want to look at average diff gap, as that’s going to be the average based on how many plays went down.

Eastern Washington let up a 75 yard score just before the week deadline which put ACU ahead despite EWU leading that game overall.

Despite Drake crushing Howard to the tune of 29-0, Howard actually played relatively close and kept the average diff below 10 in Drake’s favor.

I’m hoping that analysis of this diff information can allow teams to recognize when they need to be riskier or play it safer. In a lot of ways, it can seem misguided because diff doesn’t occur in a vacuum and different plays have different meanings, but there’s already a way to quantify how you did in the plays that mattered most, and that’s the score. But that’s much more obvious and less nuanced than this diff analysis. I hope it can be of use to you, and if not, at least be entertaining! Have a great week and go FCS!