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A Guide to Modern Football Analytics for Beginners

Ever get confused about the new stat in an article you read? Here's an explanation of what the metrics mean.

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The term "analytics" might be the most polarizing word in all football amongst fans, pundits, and even NFL personnel as it's grown more popular across the league in recent years.

Many people chalk analytics up to nerds playing sports on a spreadsheet and scoff at the idea that NFL decision-makers could decide crucial in-game or player personnel decisions based on a math equation.

Analytics is a broad term that doesn't necessarily explain the differences between metrics becoming more common in football analysis these days. Most haters of "the math" take issue with predictive analytics or win probability models telling NFL head coaches that they should punt, go for it, or kick a field goal in certain situations.

However, there's another world in football statistics that I'll often use on results-based statistics. Like total yards, points, or passer rating, there aren't any predictive qualities to these stats that are contrived by what happened, past tense, on the field.

The goal of these metrics is to provide more context into ranking player and team efficiency than traditional raw stats you'll see in a box score. For example, there's a significant difference between an offense gaining two rushing yards on third-and-ten and two yards on third-and-one. One run led directly to fourth down (and likely a punt or field goal), while the other moved the chains for a new set of downs.

We've all heard TV broadcasts for years cite that Team X is 10-0 when they rush for over 100 yards as a team. Well, duh, when NFL teams have a lead late in games, they're going to run the football to milk the clock, thus accumulating rushing yards. In the same vein, we all remember back in Week 7 when the Seahawks blew out the Chargers 37-23, but you lost in fantasy football because Austin Ekeler scored a garbage-time touchdown. Was that just me? Oh well.

Not taking away anything from Ekeler, but those garbage time yards and touchdowns when the game is already decided should not count the same as yards and touchdowns in a close game.

Furthermore, scoring points or moving the ball against a top defense should be weighted more positively than scoring against the 32nd-ranked defense in the NFL and vice versa. If the ultimate goal is to analyze teams with the most information possible, raw numbers aren't it.

That's where modern football statistics and metrics, such as Football Outsiders' Defense-adjusted Value Over Average (DVOA) and expected points added (EPA), can help tell the whole story.

As you can find on Football Outsiders' website, "DVOA measures a team's efficiency by comparing success on every single play to a league average based on situation and opponent."

To go back to our examples, a traditional stat like yards per carry counts the two-yard run on third down the same. It's two yards, whether it's third-and-long or third-and-short. DVOA, on the other hand, accounts for the down and distance. It's also weighing the opponent, so if the Patriots rush for 200 yards against Buffalo's sixth-ranked run defense, it gives the Pats more credit than rushing for the same amount of yardage against Houston's last-place run defense.

Expected points added is similar by taking into account down and distance and field position to define how many points a player or play is worth to a team. Like DVOA, EPA uses a baseline average of how many yards are typically gained in a particular game situation to "measure how well a team performs relative to expectation."

Although they are slightly different, the idea behind them is the same, which is to provide context to each play based on the game situation to get a more accurate ranking of players and teams.

Just because these metrics are new and admittedly a bit nerdy doesn't mean they are bad. In fact, they're making us all smarter as football fans and analysts than the old-school stats.

Here are a few other metrics that we'll use here at with a quick explanation of each:

- Success rate: Like DVOA and EPA, success rate is calculating the result of a play based on down and distance. Typically, the thresholds are gaining 40% of needed yards on first down, 60% of needed yards on second down, or 100% of needed yards on third and fourth down (via Football Outsiders). This metric is a good way to calculate offensive or defensive efficiency on early downs (example: the Pats had an early-down success rate of just 37% against the Jets in Week 8. Due to their early-down struggles, New England lived in third-and-long with an average distance to go of 9.2 yards, leading to just a 31.6% third-down conversion rate).

- Completion Percentage Over Expected (CPOE): CPOE understands that not all completions by quarterbacks are created equal. The metric calculates the probability of a completed pass based on several factors such as field position, down, air yards, yards to go, pass location, and if the quarterback is under pressure. From there, we can separate the difficulty level for a completion in an NFL game (example: Mac Jones completes a five-yard check-down on first down versus a 15-yard crossing route on third-and-12).

- aDOT (Average Depth of Target): this one is pretty easy. It's the average air distance a pass travels divided by the number of pass attempts (example: Mac Jones did not push the ball downfield much against the Colts last week, with an aDOT of just 5.5 yards).

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