Stat Sandwich: Notre Dame/Rice Team Breakdown

It feels soooo good. Football’s back, and this weekend did the things from a pleasure standpoint that certain religious sects swear is a one way ticket to the bad lands. (side note: these same groups probably don’t like swearing, but whatevs). Catholics would at least feel the need to go to confessional. The lusting. The coveting. The want for more. If this is being bad, then I don’t want to be good.

Saturday did many a thing for the Notre Dame collective morale. Everett Golson began the process of changing ND fan vernacular from “Tommy, NO!” to “Tommy, who?” by flashing some sweet skills in a 48-17 dominating performance of Rice at Notre Dame Stadium. The modern-day (selective memory) version of the 4-Horsemen – Golson, Bryant, McDaniel, and Folston combined for 223 yards on 40 carries. Grantland Rice – You’re on the clock to get a new lede. I assume famine and pestilence will be replaced by Ebola and Miley Cyrus, but there’s still room there for creativity. The defense in an uneven but somewhat encouraging performance mandated that the Internet’s collective snark put their dumpster fire memes on hold for at least another week. All and all, it was a good week.

However, I’m not here to bludgeon you over the head with reminders of how awesome Saturday was. Your hangover Sunday should have done that. In addition to bringing shenanigans, tomfoolery, and a charming southern accent to the ladies, one thing I wanted to provide to Down the Tunnel was some fun (pronounced: “enjoyable” to “horribly tedious” depending on your particular lean) statistical breakdowns of the games just passed.

A couple of caveats: Yes, this is just Rice. No need to lose our damn minds over the performance. Lose your mind over something worthwhile, like how Greg Bryant packed two pythons who just ate a baker’s dozen of bowling balls into his arms. Secondly, in the stats world, one game is the proverbial “small sample size.” Percentages, usage patterns, [something] per [something else] are still subject to fairly large variances week-to-week. As the season progresses, things stabilize, benchmarks become more apparent, and we gain a more realistic picture of where the team stands compared to the sprawling array of college football. But don’t go joining reality yet. There’s plenty of time for shattered dreams and references to sipping on Clorox. For now, sit back, and have fun numerically recalling Saturday (Yes, I’m aware your ability to count was ahem “impaired” on Saturday.)

Let’s start with the team stats. Notre Dame’s Overall stat line looked like this:

Points:                       48

Plays:                          72

Points per Play:       .67

Passing Attempts:   22

Rushing Attempts:  42

Penalties:                   2

FG Attempts:            3

Punts:                         3

Total Yards:               576

Rushing Yards:          281

Passing Yards:           295

Yards per Point:         12

Penalty Yards:            10

Turnovers:                   0

Field Goals:                 2/3. Makes: 29, 36 yards. Misses: 39 yards

Punts:                         39 yards (fair catch), 50 yards (touchback), 55 yards (touchback).

Punt Average:            48

Net Punt Average:     35

1st Downs:                  23

3rd Down Converts:  6/13 for 46%

Red Zone Atts:           6

Red Zone TDs:             4

Red Zone FG’s:           2

RZ Score %:              100%

RZ TD %:                   67%

Notre Dame’s offense functioned at an obviously high level. The balance was there from the get go. The general trend is not uncommon for those that have watched Brian Kelly over the previous few years. Versus weaker opponents, the offense will typically skew run as BK attempts to exploit size/depth advantages. Think of Brian Kelly as Gumby. He can stretch himself as needed, but he does have a system he reverts to at the end of the day.

The offense, most importantly, was more efficient than years past. Points per play and yards per point are both rough measures of efficiency. Offenses are inevitably measured by how many points they can score. Points per play gives a rough measure of how explosive an offense is. More points on fewer plays being the natural ideal. Notre Dame’s 0.67 points per play would have ranked second in FBS last season (#1 – Florida State – 0.749). Notre Dame’s Points per play last three years: 2013 – 0.404; 2012 – 0.375; 2011 – 0.412, all middle of the pack.

Yards per point is an efficiency metric. Not perfect by any stretch, and much of the criticism is that it lacks predictive power. However, as a descriptive stat, it tells you how good the team was at converting offensive production to points. I find it to be generally superior to red zone stats in measuring efficiency. The fewer yards per point, the more efficient the offense. Notre Dame’s 12 yards per point would have been sixth in the FBS last season (#1 – Florida State – 10.1). Notre Dame’s yards per point the previous three years: 2013 – 14.9 (75th nationally), 2012 – 15.8 (88th nationally), 2011 – 14.1 (53rd nationally).

The point here is simple. What we think we saw on Saturday was an offense finally clicking, and the stats confirm that to be the case. From an explosion and efficiency standpoint, this is what a good collegiate offense looks like. It would also be a marked improvement from previous years if this continued week over week. The defenses will get tougher, no question about it. The framework is there for consistent performance. Quarterback and runningback are both deeper and more skilled than in recent years past. While the wide receiving corp is young, there is a lot of potential for development. More importantly from a schematic perspective, Brian Kelly has a multitude of options at his disposal to mix and match as he sees fit.

Notre Dame Offensive Play Breakdown by Quarter:

First Quarter Second Quarter Third Quarter Fourth Quarter
# Plays:


20 20




8 11




9 7




1 1


Punts/FG Att:


2 1




2 1


Rushing Yards:


70 47 126
Passing Yards:


124 45


Rush:Pass Ratio*

2.0 0.89 1.57


Rush Yds/Car.

3.8 8.75 4.27


  • Rush:Pass Ratio for Game = 1.91; 2013 Rush-Pass Ratio = 1.02

Nothing too exciting here. Notre Dame came out wanting to establish the run, and while it was their least effective quarter on the ground on a per play basis, the team still ended up with 2 touchdowns to show for their work. Everett Golson was so lethal in the first half through the air and on the ground that the Irish only attempted 8 passes in the second half of the game and only one pass in the fourth quarter. The fourth quarter’s rushing total and yards per carry were both aided by Malik Zaire’s flamboyant entry to the game. Excluding Zaire’s run, the team still averaged 5.8 yards a carry with a Greg Bryant touchdown.

The uptick in rushing average in both the second and fourth quarters are at least indicative of a situation where one team was just superior in terms of depth and conditioning. While many will clamor for Bryant to be the work horse, it should not be underestimated how important it can be to exploit the ability to send out a fresh back for any series without concern for performance fall off. Bryant, Folston, and McDaniel all averaged at least 5 yards a carry for the game. I have no issue with Brian Kelly continuing to spread the wealth so long as all three backs are effective. Over the course of a game, that advantage shows.

Notre Dame Performance by Down:

1st Down:

2nd Down:

3rd Down:

# Plays
















Avg. to go for 1st:




Efficiency %:*




Eff. 3 > 5yds to go




Eff. 3 <= 5 yds to go




* the folks at use a play efficiency metric to decide whether a play was efficient or not. It’s easy to think about in the context of third downs: Did the play result in 100% of the required yardage to get a first down/score? For first down, the metric is 50% of required yardage. Second down is 70% of required yardage. These are my calculations based on their formula.

** Notre Dame never faced a 2nd and >10 yards. Both offensive penalties occurred on 2nd and 3, resulting in 2nd and 8 effective situations.

*** A 46% third down conversion percentage would put you in the top 25 for FBS schools end of year rankings for each of the previous 3 seasons. Notre Dame’s last year? 42%….good for 47th Nationally.

Notre Dame Formation Usage:

The offense ended up using only two types of packages: A 11 (1 RB, 1 TE, 3 WR), and a 12 (1 RB, 2 TE, 2 WR). By my unofficial count, I only recall 2 plays where the back would shift out of the backfield into an “empty back” alignment. Both of these occurred out of the 11 personnel. Last season, ND shifted to the empty backfield alignment considerably more. It’ll be interesting to see whether the lack of use was just a matter of opponent or whether it’s a philosophy shift. Last year, I speculated that use of the 11 empty backfield was utilized to exploit arguably Tommy Rees’ best attribute, pre-snap reads. In 2012, the offense used the empty backfield more as the season went on to spread the field and create more potential running lanes for Golson. That was different personnel. With the increased skill level at the running back position, my early guess is we see the “empty back” set less this year.

Notre Dame exclusively used 11 in the first half. The first instance of 12 occurred early in the third quarter when the team was deep in Rice’s territory. The two plays leading up to the phantom handoff touchdown scramble were with 12 personnel. The Golson scramble itself came out of the 11. 50% of Zaire’s snaps were with 12 personnel at the end of the game when the Irish were simply looking to run out the clock.

Of the 63 plays in non-end of game/half situations, only 7 were in the 12. The remaining 56 came out of 11. Of the 56, 53 were run with the first team offense. Ben Koyack was the TE on all but one of those snaps. Tyler Luatua made a cameo in the first half deep in Irish territory when Luatua was lined up in H-Back position. That play resulted in a 13 yard run by Greg Bryant up the middle.

Offensive Player Usage:

At the beginning of each season, player usage is always a fun thing to track. The chart below shows how many snaps each offensive player was in the game for (regardless of whether they touched the ball on a given play). There were a total of 66 non-special teams snaps. The percentages will not necessarily add up to 100% for each position since multiple tight ends or receivers were used on the same play. This information is derived from my personal observation, re-watch of the game. My confidence level is about 95% in terms of accuracy overall. Very confident with respect to quarterback, running back, and tight end usage. However, I’m beholden to the game feed meaning there might be a receiver identification or two that is off. The general trends though I believe are entirely accurate.


QB Use % RB Use % TE Use % WR Use %


Golson 91 Folston 38 Koyack 89



Zaire 9 Bryant 33 Smythe 18 Brown


McDaniel 29 Luatua 8 Carlisle










Least Lee


While Tarean Folston actually saw the greatest usage of the three running backs, the timing of his use is more telling. Folston was in on 25 plays. Of those 25 plays, only 14 came with less than a 4 touchdown lead being held. In a game dictated by the Irish as much as this one, that may or may not mean anything.

At the wide receiver position, the loss of DaVaris Daniels (for the time being) as well as the hand injury to Corey Robinson, likely led to the high use rates for both Will Fuller and Chris Brown. It will be an interesting trend to watch Fuller’s usage. I expect it to go down as Robinson gets healthier and Justin Brent gets more used to the offense. However, as I noted on the Roughing the Passer vidcast, that Fuller received so much time suggests that he’s more versatile as both a route runner and blocker than perhaps the reports out of spring camp had led many to believe.

So, we’re closing on 2,000 words. So as to not blow your minds in one post, I’ll split up team trends into this post and be back later in the week with some player specific data. If there’s something in particular you’re curious about, please hit me up on Twitter at @IrishMoonJ. We can make this reality whatever we’d like it to be.


– Moons

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