This is intended as a high-level overview to advanced box scores, the work of Bill Connelly at ESPN. Interested in learning more? Check out Football Study Hall, and/or read some of our previous advanced stats-y works: here, here, and here.
The humble football box score has not changed in the better part of a century. We’ve developed newer, fancier, and more digital ways to display it, yes — but the content has been as bland and basic as a bowl of unflavored oatmeal. Don’t believe me? Here’s a clipping of the box score of the 1967 “Ice Bowl” between the Green Bay Packers and the Dallas Cowboys (h/t ProFootballDaly.com):
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Compare that to this one from 2018:
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See? There’s virtually no difference between the levels of information provided by both versions and one could even argue that the modern version actually provides less information upfront, instead hiding it behind various tabs, bells, and whistles. Suffice to say, there’s room for improvement.
The crux of the issue the (we?) nerds have with the basic box score is that it’s just that — basic. Aggregate numbers are good, but rarely do they ever tell the whole story. For example, let’s consider this: in 2019, a team put up 570 passing yards and 9 passing TDs in a single game. Did that team win that game?
No. No, they did not. Big numbers look great on the stat sheet and racking up yardage does help teams win games, but those two numbers tell us nothing beyond what happened. We want to know how it happened.
If the point of a box score is to tell the story of a football game, why not tell a better story? That’s what friend-of-the-blog-but-really-more-of-a-distant-statistical-mentor Bill Connelly poses in a chapter of his 2013 book Study Hall. Connelly’s “advanced box score” has evolved quite a bit in the intervening seven years, but the major focuses built into it have typically been centered around the “Five Factors of football”. Connelly (2018) explains them thusly (condensed slightly for readability):
1. Efficiency: ...examine(s) your efficiency and consistency in staying on schedule and putting yourself in position to move the chains. In terms of projection, it is by far the most important of the factors.
2. Explosiveness: Presented through Isolated Points Per Play (IsoPPP, which is unadjusted), IsoPPP+ (adjusted), and Marginal Explosiveness (see entry below). IsoPPP is the Equivalent Points Per Play (PPP) average on only successful plays. This allows us to look at offense in two steps: How consistently successful were you, and when you were successful, how potent were you?
3. Field Position: Presented through average starting field position (unadjusted) and FP+ (adjusted). This is mostly self-explanatory, with one important note: You should remember to measure an offense by its defense’s starting field position, and vice versa. Special teams obviously play a large role in field position, but so do the effectiveness of your offense and defense.
4. Finishing Drives: ...how frequently you create scoring opportunities, but how you finish the ones you create.
5. Turnovers: ...how many turnovers you should have committed (on offense) or forced (on defense) and how many you actually did. This tells us a little bit about quality and a lot about the Turnovers Luck idea defined above.
“That’s a lot of words to read”, one might complain. Well, fine — here’s an example instead:
The rest of the box scores will come tomorrow, but I couldn't wait on this one:
SC 20, UGA 17
— Bill Connelly (@ESPN_BillC) October 13, 2019
* 8% postgame win expectancy!
* SC had like one explosive play and still had better (less bad) explosiveness numbers
* It's hard to lose when you have 7 scoring opps to opponent's 4 pic.twitter.com/LP9kcSjLmN
The stats Connelly uses are associated with a Factor as follows (well, this is my best guess anyway):
- Efficiency: Plays/Drive, Yards/Play, Yards/Drive, Opps/Drive, Success Rate (by Quarter, Rushing/Passing, Standard/Passing Downs, Game)
- Explosiveness: IsoPPP, Yards/Play
- Field Position: Average Field Position
- Finishing Drives: Opportunities, Points/Opp, Opps/Drive
- Turnovers: Turnovers, Expected Turnovers, Expected Turnover Margin, Turnover Luck
He also likes to add a splash of color to certain metrics to compare team performances against national averages and throws in player stat lines to round things out.
“This is a lot of numbers,” one might complain again. “What makes this better than the other version?”
Well, two reasons come to mind:
- Meaningful information density: In a similar amount of space, you get a lot more information about a game and how it played out.
- Situational Rates over General Aggregates: Connelly provides aggregate measures, but pairs them with contextualized measures — typically rates — that have been filtered and contextualized based on some in-game situational criteria. ESPN’s basic box score gives us some rates (pass completion, third-down conversion, etc), but these numbers lack context. Situational rates give us a better idea of the nuances within a team’s performance.
Again, the focus is on how things happened, not what happened, but even if you only wanted to talk about what happened, you could do it pretty effectively with even just the first page (from the left) of Connelly’s box score. None of these concepts are particularly hard to grasp (other than Expected Turnovers and IsoPPP, which do involve some advanced math), and all are easy to communicate. Let’s try writing our own game story using the following box score:
LSU 37, GEORGIA 10
* UGA needed ball control and a huge game from Swift ... and got 2 carries. Injuries can ravage even ridiculous recruiters
— Bill Connelly (@ESPN_BillC) December 9, 2019
* Yds/att on SDs: Burrow 10.2, Fromm 4.3. I think that pretty much tells the tale
* Actually, pretty much everything here tells the tale pic.twitter.com/yejrA61gCV
It’s been quite a while since this game (2020 has been quite a ride so far, hasn’t it?) and I don’t exactly remember how it played out on the field, but here’s what I can tell you based on the advanced box score:
- One team struggled to find any consistency offensively throughout the game. Just look at the difference in success rate by quarter — one squad started off on the right foot, while it doesn’t seem like the other showed up to the arena until the fourth quarter. Even when the game was still within reach (AKA: non garbage time), this team was completely shut down offensively, based on its success rates for rushing and passing. Now, this could be overcome with a competent defense, but alas...
- One team’s defense could not stop a thing. Giving up 1.5x the yards per play of your opponent is not exactly what I’d call a stellar defensive performance. Giving up 10.2 yards per attempt in non-passing situations (AKA: standard downs) is...not good.
- Even in advantageous situations, one team still struggled to finish drives and score. Both teams started drives around the same average yard-line, ran around the same total number of plays, and had the same number of drives in the game, but one was able to generate more opportunities to score and capitalize more on said opportunities, given their higher points per scoring opportunity.
Seems like quite a recipe for disaster, no? We didn’t even have to go back to the tape to confirm that (spoiler alert: I did, and this was as much of a [Styx]show as you might remember it being). This is the power of the advanced box score: we’re able to contextualize statistics to discuss a game in a more educated manner, sometimes without even having to watch (or rewatch!) the game.
But can we go further? In that vein, I leave you for today with an interesting thought to ponder: baseball’s recent obsession has centered around the concept of a player’s WAR, or wins above replacement. Obviously, when compared to football, baseball’s rules make for a game in which it’s much easier to measure individual contributions, and as such, measuring a baseball player’s contributions to their team’s win total is a much less painful venture. Nevertheless, can we model this same concept in CFB? Can we quantify the idea of a “playmaker” and measure their impact on the final score of a game? Come back tomorrow and let’s find out!
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