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NFL Analytics- DVOA, QBR, and EPA
Photo: Sep 7, 2024; Tuscaloosa, Alabama, USA; Alabama Crimson Tide quarterback Jalen Milroe (4) eyes a pass against the South Florida Bulls during the third quarter at Bryant-Denny Stadium. Mandatory Credit: William McLelland-Imagn Images

NFL Analytics- DVOA, QBR, and EPA

Football has slipped into the lives of billions of people worldwide to the point where many fans can’t imagine themselves without it.

It’s difficult to find a person who wouldn’t have watched at least a single match, so unsurprisingly, football-related topics always stir public interest.

The National Football League is an American professional organization that has 32 talented teams in it. Whenever they play, the crowds go wild with speculations and excitement. Some people look for a trusted online casino to place their bets on match outcomes. They try to predict which team will score first, who is going to win, if penalties will be involved, and so on. However, successful wagering depends on deep knowledge, and NFL analytics help deliver it.

What Is DVOA?

Definition

DVOA is an analytics metric that stands for Defense-adjusted Value Over Average. It helps measure the average efficiency of the team and every single player in it by taking all the context into account. 

Everything, from the results shown in a season’s matches to the field position of the footballers and the strength of their opponents, affects DVOA’s evaluations, which makes them nuanced and accurate.

How DVOA Is Calculated

DVOA is based on the following formula.

  • Game situation. Successful or failed comebacks affect the results of DVOA analysis; things like the score margin between the teams also play an important role. 
  • Down and distance. A 5-yard gain on a 3rd down means more than when the team that is already close to victory shows the same result. 
  • Context-based yardage stats. Since DVOA is a nuanced metric, it doesn’t simply focus on how many yards a team covered. It looks into how these gained yards helped the team progress, so a 2-yard gain on 1st & 10 will matter less than a 2-yard gain on 4th & 1.  
  • Strength of opponents. Getting many rushing yards is always great, but the impact differs based on what team someone is competing against. If it’s one of the leaders, then DVOA will evaluate such a result higher; if the opponents are weak, then yard success won’t matter much. 

As you see, DVOA considers many little details to calculate the absolute average.

How DVOA Is Used in the NFL

People love analyzing the NFL from every single side. They create depth charts for different teams and research player history to understand what they can expect in the upcoming matches. DVOA helps by:

  • Ranking team efficiency based on its offensive and defensive styles
  • Identifying strengths and weaknesses a team commonly experiences 
  • Evaluating individual players to show what they can contribute to the team

If you master DVOA, you’ll be able to anticipate how future matches might go with increased accuracy.

What Is QBR?

Definition

QBR is a Total Quarterback Rating. As you can see from its name, it’s a metric developed for quarterback assessment. With its help, you can evaluate the impact a specific quarterback has on the game. 

How QBR Is Calculated

QBR has a more complex algorithm, as it focuses on assessing all the nuances in a quarterback’s performance that increase or diminish the team’s chances of winning. Let’s make a quick overview of its key components:

  • Passing efficiency. When a quarterback is throwing a ball, QBR helps evaluate how many yards this player gains, whether they miss or score more, and their overall accuracy. 
  • Contributions in rushing. Doing scrambles, rushing touchdowns, and being effective at it increases the value of the player. 
  • Sack avoidance. Avoiding sacks and coping with intense pressure is a mark of a talented quarterback. 
  • Overall match context. A touchdown that happens in the crucial moment and pushes the team forward is valued higher than the one occurring in the middle or when the scoring margin is already large enough.  

If you’re interested in quarterbacks in particular, using QBR might come in handy. 

How QBR Is Used in the NFL   

This metric is used for comparing the performance of different NFL quarterbacks. For coaches, it’s a great indication of whether a specific player should remain in the game or if it’s better to replace them. 

What Is EPA?

Definition

EPA is an Expected Points Added metric. It analyzes each element of the game and quantifies their individual impact on the final match outcomes. 

How EPA Is Calculated

EPA takes all historical data into account. It presents the expected estimates before the match, compares them to the actual estimates recorded after the match ends, and adjusts its future conclusions accordingly. 

Here are the factors that play the biggest role in EPA assessments:

  • Position on the yard line 
  • Down and distance
  • Time remaining in the game
  • Total play result

By applying EPA to all games in a season, the analysts can better understand how different events and strategies contribute to the team’s success or failure. 

How EPA Is Used in the NFL

EPA is a great tool for both offensive and defensive analysis. It helps in fourth-down decisions, too, letting the coaches decide which approach to take to achieve the best results.  

Limitations of DVOA, QBR, and EPA

Being able to predict football results accurately is a dream of millions of fans. NFL is popular to the point where its revenue has been increasing annually for the last 20 years. Considering this fact, it’s not surprising that people apply many advanced metrics to evaluate how the teams are going to do in their next matches and understand the impact of individual players better.   

However, nothing is flawless, and the metrics we just discussed also have their limitations.

  • DVOA. Small sample sizes usually render DVOA useless, so its early-season data won’t tell you much. 
  • QBR. There are too many factors involved in QBR assessments: with no set formula, it’s not consistent and transparent enough. 
  • EPA. It focuses on general nuances more than on the players’ individual skills and characteristics, meaning that its predictions can easily crumble. 

All these metrics simplify predictive modeling, but the results they offer are never set in stone. Anything can happen during a match — this is what makes all the football games so exciting.