Please allow me to introduce myself, I am a man without wealth or taste …
Seems like the audience here at Dawg Sports takes on musical references, but for real my name is Josh Hancher. I am a UGA ’97 graduate and affectionately known as Dawg_Stats on Twitter. I started blogging at the start of the 2019 season. Teamed up with Bulldawg Illustrated for the ’19 and ’20 seasons. Last year Graham Coffey, Nathan Lawrence and I launched an experimental video show called “The Battle Hymnal” which took the analytical approach of the Chapel Bell Curve and combined it with an X and O analysis to break down the UGA season. This offseason Graham and I launched “Dawg Sports Live” here and created content and analysis throughout the offseason.
I know a lot of readers supported and watched most of the shows (thanks for that). For those who have just returned to Georgia Football now that the pads are on, I wanted to introduce myself and offer some background information and a glossary of terms that I like to follow and share with Georgia fans.
If you’ve seen or read my previous efforts to explain football analysis, please feel free to click “back” now. Thanks for the click. For those who are still with me, I want to share with you the baseline and explain the terms and stats that I will be sharing here, on Twitter and on “Dawg Sports Live”. I often preface that using football analysis doesn’t try to reinvent the sport or convince anyone who wants to shout “RTDB” from level 600 is not fair and just. It’s just another way of looking at and analyzing sports. And for many of you who want to get into a small bet – all sports betting uses analytics to define lines. Many of those who offer advice on choices will reference or incorporate these statistics into their choices. That’s all to say, advanced analysis is becoming more and more common in football coverage.
There are three main ingredients to my analysis that I will share with you. In reality, it comes down to effectiveness and how to show it. How you score matters. How you prevent yourself from tagging questions. If you read what Bill Connelly writes, this is all part of his SP + nomenclature.
• Success rate
• EPA (expected points added)
The success rate is the basic formula for much of football analysis. It is the “Yes / No” calculation on the success of a play. It is tracked as a percentage. On offense, a higher success rate is good, and allowing a lower success rate on defense is good. In Bill Connelly’s “Five Factors” of 2014, his numbers indicate that winning the success rate in a game will lead that team to win 83% of the games. This is a binary formula for “keeping the offense on schedule”. Conversely, in defense, put the offensive “behind the sticks”.
The success of a play is
Gain 50% of the yards to be gained on the 1st try
Gain 70% of the yards to be gained on the 2nd try
100% yards to be gained on 3rd and 4th tries
Simple isn’t it? And that makes sense. A 2nd descent of 4 yards on 2nd and 5 is “successful” while a 4-yard run on 2nd and 8 is not. And a draw of 11 yards on the 3rd and 15th is again unsuccessful.
And while a high success rate speaks of efficiency in attack, defense wants to prevent and allow a lower success rate.
A quick glance allows you to see the games that were stressing us out. Arkansas were cover, but lousy with a 38% success rate on offense, but the defense was stifling, allowing only 25% for an offense that has been successful at 45% this season. Most UGA fans know how the Florida game went, but a 25% success rate at the season low is hammering it on for sure.
Hope you are still with me, and if you are, it might increase your patience with my stats. EPA stands for “Expected Points Added”. It is nothing more than a number assigned to a coin’s value for the game. Higher is better for offense and the opposite is true for defense. Think of it as a digital note for a play. The pass rate is a “pass / fail” while the EPA will give you a larger scale to judge a piece. Do you remember those bulletins?
The nerds who paved the way for advanced analysis analyzed a plethora of games in the history of the game and devised a number for each game based on
EPA takes the starting EPA of a set (1st and 10 of your own 25 has an added expected point of .922) then take the next set’s EPA and subtract it. This gives you that 1st Down’s play EPA.
Let’s take a game from 2020 – as tempting as it is to use Zamir’s 25-yard TD against Florida (6.077 EPA for that) – let’s use a 1st and 10 from UGA 26 in the 4e Florida quarter of the game.
This ground, remote, and field position has a starting EPA of
Mathis throws an incomplete pass intended for Tre McKitty. Spawns 2sd and 10 at UGA 26. This 2sd and 10 play has an EPA of
So the EPA is calculated for this set by subtracting the 1st and 10 .993 of 2sd and 10 0.259 giving this game an EPA of -0.734
Ok, this calculation is not done on the fly and it does not need to be memorized. It’s just a mathematical calculation. So when you see these numbers, you can understand some of the math behind it. This metric is really starting to shape the effectiveness analysis. The EPA is often presented as an average, but the sum is also an appropriate description of an offense and defense and their effectiveness.
It really starts to show mathematically what we saw once JT took over. Auburn’s game was about as good as one could hope for, but compared to what UGA did in attack against Mississippi State, Carolina and Missouri – he paled a bit.
Before we get to the explosiveness, let’s take a look at these two metrics and what they were for each team before WLOCP.
EPA SR offense
Florida 0.374 50.2%
Georgia 0.117 41.8%
Florida 0.194 44.7%
Georgia 0.077 36.3%
Arguably the Florida offensive was 3 times as effective as the UGA’s as judged by the EPA. And while the UGA’s defense was exceptional, it wasn’t 3 times as effective at compensating for ineffectiveness in attack – not at all considering the injuries clustered in defense. Interesting that UGA was the 2.5 point favorite. Most of the books online showed Florida and points accounted for the majority of bets.
I made a quick video watching two discs of the Alabama game that shows these stats in real time.
Explosiveness is a word that is often used in the media and in coaching speech. This can be a subjective measure. For example, I don’t think a triple option offense will judge offensive explosiveness the same way Todd Monken does. (During the 2020 preseason, he set the explosive play bar as a percentage of passing plays over 20 yards and rushing plays of 12 and over yards).
Well, the analytical community universally describes explosiveness as the EPA of successful one-team games. This particular statistic certainly needs more context than the previous ones in this article. Especially if I told you that UGA was second in the SEC in offensive explosiveness in 2020.
Think of it like “how good are your good games?” UGA had its share of big wins, but remember from the “success rate” section, UGA had 7e in SEC. So while their good plays were good – using explosive metrics – UGA needed more. If we add this statistic instead of the average, it shows a different picture.
UGA was near the top in terms of average yards per play on successful plays, but the fact that they had less than elite infractions underscored this Total EPA metric. (For reference, the James Coley experiment left UGA 11e in SEC in that stat on average, and 1.5 yards per game behind LSU’s 13.9 in 2019)
Graham and I did a show on these topics, and they’ll be part of the blackouts this season on “Dawg Sports Live”
Well, if you’ve made it this far, thank you. Hope you understand some of those joking numbers better. I will refer to it quite often. Granted, traditional stats using yardage, points and the like will be in the breakdowns here and on Dawg Sports Live. I really enjoy discussing this topic and questions are welcome here and on Twitter. Come on friends!