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    What is DVOA? | Football Outsiders

    the ultra-short version:

    dvoa measures a team’s efficiency by comparing each play’s success to the league average based on the situation and opponent.

    the short version:

    dvoa is a method to evaluate teams, units or players. It takes every play during the NFL season and compares each one to a league-average baseline based on the situation. dvoa measures not just yards, but yards to a first down: five yards on third and 4 are worth more than five yards on first and 10 and much more than five yards on third and 12. red zone plays are worth more than others plays. the performance is also adjusted to the quality of the opponent. dvoa is a percentage, so a team with a 10.0% dvoa is 10 percent better than the average team, and a quarterback with a -20.0% dvoa is 20 percent worse than the average team. the average quarterback. because dvoa measures scoring, defenses are better when they are negative. for more details, read below.

    Reading: What does dvoa stand for in football

    dvoa explained | about dvoa v7.3 | dyar explained | special teams statistics | Adjusted Line Yards and Other Offensive/Defensive Line Stats | driving statistics

    dvoa explained

    A runner runs three yards. another runner runs three yards. what is the best career? this sounds like a stupid question, but it’s not. in fact, this question is at the heart of almost all discussion of soccer outsiders.

    Several factors can differentiate one 3-yard run from another. what is the drop and distance? is it third and 2 or second and 15? where on the field is the ball? Does the player get only three yards because he gets to the goal line and scores? Is the player’s team up by two touchdowns in the fourth quarter and therefore time is running out? or down by two touchdowns, and thus face a defense that is playing purely against the pass? Does the runner play against the porous raiders defense or the stalwart bear defense?

    conventional nfl statistics rate plays based solely on their net yards. The NFL determines the best players by adding up all their yards regardless of what situations they entered or how many plays it took to get them. now why would they do that? football has one goal: get to the end zone, and two ways to do it: gain yards and get first downs. these two objectives must be balanced to determine the value of a player or the performance of a team. All the yards in the world won’t help a team win if they all come in six-yard portions on third-and-10.

    The popularity of fantasy football only exacerbates the problem. fans have gotten used to judging players based on how much they help fantasy teams win and lose, not how much they help real teams win and lose. typical fantasy scoring further distorts things by counting the yard from the one to the goal line as 61 times more important than all other yards on the field (each yard is worth 0.1 points, a touchdown is worth 6). let’s say larry fitzgerald catches a pass on third and 15 and goes 50 yards but gets tackled two yards from the goal line, and then andre ellington takes the ball on first and goal from the two yard line and dives for the score . Has elington done anything special? not really. when an offense gets the ball at first-and-goal at the two-yard line, he’s expected to score a touchdown five out of six times. ellington is getting credit for the work done by the passing game.

    Distributing credit for scoring points and winning games better is the goal of dvoa, or defense-adjusted value-over-average. dvoa breaks down every play of the nfl season, assigning each play a value based on both total yardage and yardage to first down, based on work done by pete palmer, bob carroll, and john thorn in their seminal book, the hidden soccer game. on first down, a play is considered successful if it gains 45 percent of the yardage required; on second down, a play needs to gain 60 percent of the yardage needed; on third or fourth chance, only getting a new first chance is considered success.

    We then expanded on that basic idea with a more complicated “success points” system, improved over the years with a lot of math and a bit of trial and error. a successful play is worth one point; a miss play, zero points with fractional points in between (e.g. eight yards on third and 10 is worth 0.54 “hit points”). additional points are awarded for big plays, gradually increasing to three points for 10 yards (assuming those yards result in a first down), four points for 20 yards, and five points for 40 yards or more. losing three or more yards is -1 point. interceptions that occur on fourth down during the last two minutes of a game incur no penalty, but all others average -6 points, with adjustment for length of pass and location of the interception (since a targeted interception down the line is more likely to produce a long return than an interception on a 40-yard pass). a fumble is worth between -1.7 and -4.0 points depending on how often the defense loses a fumble in that situation, no matter who gets it back. red zone plays get a bonus: 20 percent for team offense, 5 percent for team defense, and 10 percent for individual players. there is a bonus given for a touchdown, which recognizes that the goal line is significantly more difficult to cross than the previous 99 yards (although this bonus is not as great as the one used in fantasy football).

    (our system is a little more complex than the hidden game thanks to our later research, which added larger penalties for turnovers, fractional points, and a slightly higher baseline For success in the first the reason why all fumbles are counted, regardless of whether they are recovered by the offense or defense, is explained in the basics of fo.)

    Each individual play in the nfl gets a “success value” based on this system, and that number is then compared to the average play success values ​​in similar situations for all players, adjusted by a series of variables. these include down and distance, field location, time remaining in the game, and the team’s lead or deficit in the game score. teams are always compared to the overall offensive average, since the team made its own decision to pass or rush. however, when it comes to individual players, running plays are compared to other running plays, passing plays to other passing plays, tight ends to tight ends, wide receivers to wide receivers, etc.

    going back to our three-yard dash example, if player a gains three yards in a set of circumstances where the average nfl running back gains only one yard, then player a has a certain amount of value above others in his position. Likewise, if Player B gains three yards on a play in which, under similar circumstances, an average NFL running back gains four yards, Player B has a negative value relative to the others at his position. once we make all of our adjustments, we can assess the difference between this player’s hit rate and the expected hit rate of an average running back in the same situation (or between the opposing defense and the average defense in the same situation, etc.) .) . add up all the plays of a certain team or player, divide by the total of the different baselines* to succeed in all those situations and you will get voa, or value above average.

    The biggest variable in soccer is the fact that each team plays at a different time against teams of different quality. By adjusting each play based on the opposing defense’s average success in stopping that type of play over the course of a season, we get DVOA, or defense-adjusted value-over-average. rush and pass plays are adjusted based on down and location on the field; passing plays are also adjusted based on the defense’s performance against passes to running backs, tight ends, or wide receivers. defenses are adjusted based on the average success of the offenses they face. (yeah, technically defensive stats are actually “adjusted to offense”. If that sounds weird to you, think of the “d” in “dvoa” as being “opponent dependent” or something.)

    The last step in calculating the dvoa is to normalize the scores for each year. As you may know, offensive levels in the NFL have risen and fallen over the years. Right now, the overall level of offense in the league is probably at an all-time high. therefore we need to ensure that the dvoa in a given season is not biased by the league environment.

    For teams, the dvoa is normalized so that the league averages for offense and defense are 0%. (However, because passing plays are more efficient than running plays, the league averages for team passes and team runs are not zero.) for players, the dvoa is normalized separately for individual passes, individual runs, and the three individual receiver groups (wide receivers, tight ends, and running backs) so that the league average for each is 0%.

    Of course, one of the hardest parts of understanding a new stat is interpreting its scale. To use dvoa, you need to know which numbers represent good performance and which numbers represent poor performance. we have made it easy. in all cases, 0% represents the league average. a positive dvoa represents a situation that favors the offense, while a negative dvoa represents a situation that favors the defense. That’s why the best offenses have positive DVOA ratings and the best defenses have negative DVOA ratings. in most years, the best and worst offenses tend to rate around ±30%, while the best and worst defenses tend to rate around ±25%. for beginning players, the scale tends to reach about ±40% for passing and receiving, and ±30% for running. as you can imagine, some players with fewer tries will get past both extremes.

    DVOA has three main advantages over more traditional ways of judging NFL performance. First, by subtracting defensive dvoa from offensive dvoa (and adding special teams dvoa, described below), we can create a set of team ratings that is based on play-by-play efficiency rather than total yardage. because dvoa better explains past wins and predicts future wins than total yards, it gives a more accurate picture of how much better (or worse) a team really is relative to the rest of the league . .

    Because it compares each play only to plays under similar circumstances, this advantage also applies against team situational ratings. dvoa’s list of top third-down offenses, for example, is more accurate than the conventional nfl conversion statistic because it takes into account that converting third-down is more difficult than converting third-down, and that a loss of ball is worse than an incomplete pass because it eliminates the opportunity to drive the other team back with a fourth-down punt. the same could be said for fourth down or red zone plays.

    second, unlike formulas based on unit comparison rather than individual plays, dvoa can be broken down into a large number of divisions (e.g. per down, per week, per distance needed for a first down , etc.). therefore, we can break down teams and players to find strengths and weaknesses in a variety of situations. All of Pittsburgh’s third downs can be compared to an average team’s third down performance. Josh McCown and Mike Glennon can each be compared to an average quarterback’s performance in the red zone, or with a lead, or in the second half of the game. not only does this give us a better idea of ​​which team or player is better. More importantly, it helps us understand why they’re better, and therefore allows us to offer recipes for future improvement.

    Finally, a third advantage of dvoa is that normalization makes our comparisons of current teams and players with previous teams and players (since 1985) more accurate than those based on traditional statistics like wins or total yards, as well as those based on more sophisticated metrics that are not normalized (eg, expected points added, passer rating difference, etc.). For example, which Denver Broncos team had the better offense: the 2013 edition with Peyton Manning or the 1998 club led by Terrell Davis? Going by total yards (7,317 vs. 6,092) or even yards per play (6.3 vs. 5.9), it’s not even a contest. the 2013 team was clearly better. However, this ignores the fact that the average NFL offense was much more pass-oriented and therefore more efficient in 2013 than it was in 1998. If we account for the difference in offensive environment using dvoa, it turns out that The 1998 Broncos’ offense was slightly better relative to the rest of the league (34.5% to 33.5%).

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    *it should be noted that certain moves are included in dvoa for attack but not for defense. other plays are included for both, but are scored differently. this leads to separate baselines on each side of the ball. for example

    • only four total penalties are included. two penalties count as passing plays on both sides of the ball: intentional kicking and defensive pass interference. the other two penalties are included for infraction only: false starts and game delay. Because the inclusion of these penalties means a group of negative plays that do not count as passes or runs, the league averages for passing offense and running offense are higher than the league averages for passing defense and defense. of running.
    • Aborted plays and incomplete backside passes are only penalized on offense, not rewarded on defense.
    • adjustments for playing from behind or leading in the fourth quarter are different for offense and defense, as are adjustments for the last two minutes of the first half when the offense is nowhere near field goal range .
    • offense gets a slight penalty and defense gets a slight bonus for indoor games.

    about dvoa v7.3

    In September 2020, we introduced the latest version of the dvoa rating system, which is version 7.3. this version fixed some bugs that existed in various settings, and also changed team stats so that scrambles now count as passing plays instead of running plays. we are slowly updating our old database to change the numbers within the new version of dvoa.

    As of now, the years 1999-2020 have been updated to version 7.3 on both our free statistics pages and the fo+ dvoa database. (the exception is in the dvoa database under “dvoa as of a specific week” as it takes longer to re-run 17 individual weeks from each previous season. those numbers were only updated to the new version in 2005 -2020).

    Scrambles are listed play-by-play since the 2000 season, except for 2005. We have 2005 scrambles listed from our first year of game registration. for seasons prior to 2000, all quarterback runs are counted as scrambles by default, except for yards lost and quarterback sneak passes (third/fourth down with 1 or 2 yards to go).

    In individual player stats, scrambles are still counted in a quarterback’s career stats instead of his passing stats.

    dyar explained

    after using dvoa for a few months, we encountered a strange phenomenon: respected players, particularly those known for their durability, had dvoa ratings that were average. The reason is that dvoa, by virtue of being a percentage or rate stat, doesn’t take into account the cumulative value of having a player produce at the league-average level over the course of a higher-than-average number of snaps. By definition, an average level of performance is better than the middle of the league, and the ability to maintain that level of performance while carrying a heavy workload is invaluable. In addition, a player who participates in a large number of plays can divert the defense’s attention from other parts of the offense and, if that player is a running back, he can take time off the clock with repeated runs.

    Let’s say you have a running back who carries the ball 300 times in a season. what would happen if you took this player off his team’s offense? what would happen to those 300 plays? those plays do not go away with the player, although some may be lost to the defense due to the associated loss of first downs. rather, those snaps would have to be distributed among the remaining players on offense, with most of them going to a replacement running back. This is where we get to the replacement level concept, borrowed from our partners at Baseball Prospectus. when a player is removed from an infraction, he is usually not replaced by a player of similar ability. Almost every starting player in the NFL is a starter because they are better than the alternative. those 300 plays will usually be given to a significantly worse player, someone who is the backup because he doesn’t have as much experience and/or talent. The true value of a player can be measured by the level of performance he provides above the replacement level baseline, adding up all of his running or passing attempts.

    of course the actual replacement player is different for every team in the nfl. In 2013, Minnesota’s No. 2 running back (Jerick Mckinnon) had a higher DVOA than the presumed starter (Matt Asiata). Sometimes a player like Ryan Grant or Danny Woodhead will be eliminated by one team and become a star for another. on other teams, the drop from starter to backup may be even greater than the overall drop to replacement level. (The Indianapolis colts of 2011, the dark year between the endowment and luck eras, will be the hallmark of this until the end of time.) rests with the team, not with the incumbent being evaluated. therefore, we generalize the replacement level to the league as a whole, as the ultimate goal is to assess players regardless of the quality of their teammates.

    Our replacement level estimates were redone during the 2008 season and are calculated differently for each position. For quarterbacks, we analyzed situations in which two or more quarterbacks had played significant plays for a team in the same season, then compared the overall DVOA of original starters to the overall DVOA of replacements. we don’t include situations where the backup was actually a top prospect waiting for his turn on the bench, as a first-round pick is by no means a “replacement level” player.

    At other positions, there’s no easy way to separate players into “starters” and “replacements,” since, unlike the quarterback, being the starter doesn’t make you the only player in the game. play. instead, we use a simpler method, ranking the players at each position in each season by attempts. players who made up the bottom 10 percent of passes or runs were divided as “replacement players” and then compared to players who made up the other 90 percent of snaps at that position. this addressed the fact that not all non-starting running backs or wide receivers are freely available talent. (think jonathan stewart or randall cobb, for example).

    As noted above, the challenge with any new stat is to present it on a scale that is meaningful to those trying to use it. To say that tony romo’s passes were worth 40 hit value points over replacement in 2014 is of little value without context to tell us whether 40 is a good total or a bad one. therefore, we translate these success values ​​into a number called “defense-adjusted yards above replacement, or dyar.” Thus, Romo was fifth among quarterbacks with 1,187 Dyar passes. we estimate that a generic replacement-level quarterback, throwing in the same situations as blunt, would have been worth 1,187 fewer yards. note that this does not mean that the replacement-level quarterback would have gained exactly 1,187 fewer yards. first downs, touchdowns, and turnovers all have an estimated yardage value in this system, so what we’re saying is that a generic replacement-level quarterback would have fewer yards and touchdowns (and more turnovers) than would add the equivalent to the value of 1,187 yards.

    (note: prior to the 2008 season, dyar was translated in terms of points rather than yards, and old articles would refer to these stats as “dpar” instead).

    how can a 16 game season be meaningful?

    Football stats cannot be analyzed in the same way as baseball stats. after all, there are only 16 games in a season. Baseball has more than ten times as much, and even the NBA and NHL offer more than five times as much. the more games, the more events to analyze, and the more events to analyze, the more statistical significance.

    that’s true, but the trick is to consider each play in an nfl game as a separate event. For example, Draw Brees played only 16 games in 2014, but in those 16 games he had 692 passing plays (including sacks) and 16 running plays (including scrambles) for a total of 708 events. Ian Kinsler in 2014 played in 161 games and had 726 plate appearances. For the most part, a quarterback who plays a full season will get about the same number of snaps as a baseball batter who plays in most of his team’s games.

    A running back will get fewer snaps than a quarterback, and wide receivers and tight ends will get even fewer. but there should still be enough snaps with most of the starting running backs and receivers to allow analysis of any significance. As an example, DeMarco Murray ran the ball 392 times in 2014 and received 64 passes (including incomplete), for a total of 456 plays. generally, a starting running back will have between 375 and 450 snaps in 16 games. Receivers are used slightly less, and therefore their stats may not be as accurate. In general, starting wide receivers have between 75 and 150 passing targets during a full season.

    problems with dvoa/dyar

    dvoa is limited by what is included in the official nfl play-by-play or follow-up of the football outlanders game graphics project. Because we need to have all of a season’s play-by-play to calculate dvoa and dyar, these metrics aren’t quite ready yet to compare today’s players to players throughout league history. As of this writing, we have processed 36 seasons, from 1985 to 2020, and are adding seasons at a rate of about two per year (the most recent season, plus one previous season).

    Football is a game in which almost all actions require the work of two or more teammates; in fact, typically 11 teammates work in unison. Unfortunately, when it comes to individual player ratings, we’re still far from the point where we can determine a player’s value independently of the performance of his teammates. that means when we say, “in 2014, marshawn lynch had a 23.1% dvoa, what we’re really saying is” in 2014, marshawn lynch, playing darrell bevell’s offensive system with seattle’s offensive line blocking for him and russell wilson selling the goalie when needed had a dvoa of 23.1%.

    With fewer situations to measure, the numbers spread out a bit more, so you’ll see more extreme dvoa ratings for part-time players and for team measurements in more specific situations (eg third down passes). tables that list players in order of dvoa have limits to the number of tries, because players with only a handful of moves end up with absurd numbers of voa and dvoa. (In 2014, for example, Johnny Manziel had a -73.2% passing dvoa in 38 moves.)

    passing statistics include sacks and fumbles on aborted plays. receiving statistics include all passes intended for the receiver in question, including those that were incomplete or intercepted. At some point, we hope to be able to determine how much of an impact different receivers have on completed versus incomplete passes, but several regression analyzes make it clear that both the quarterback and the receiver have an impact on whether or not a pass is completed. . the word pass refers to both complete and incomplete pass attempts.

    Unless we say otherwise, all references to the third down also include the handful of running plays and passes that take place on the fourth down (mainly 4th and 1).

    dvoa for special teams

    The problem with a system based on measuring both yardage and yardage to a first down, of course, is what to do with plays that don’t have a first down chance. special teams are a big part of soccer and we needed a way to add that performance to the dvoa team rankings. our special teams metric includes five separate measures: field goals (and extra points), net punts, punt returns, net kickoffs, and kickoff returns.

    The basis of most of these special teams rankings is the concept that each yard line has a different value based on how the probability of scoring changes with better field position. in hidden play, the authors suggested that field position value for the offense existed on a straight line with its own goal line worth -2 points, the 50-yard line 2 points, and the opposite goal line 6 points. (-2 points isn’t just the value of a safety, it also reflects the fact that when he’s backed up in his own zone, he’s likely to see his momentum stop, and he’ll have to punt and give the ball to the other team in good field position, therefore the defense is more likely to score next). we use a more refined set of values ​​based on our research, but the idea is the same.

    Our special teams rankings compare each kick or punt to the league average based on field position point value at position for each kick, catch and return. we have determined a league average for the distance a kick travels as a function of the yard from which the kick is taken (almost always the 35-yard line for kickoffs, variable for punts) and a league average for the distance a return travels based on both the yard line where the ball is caught and the distance it traveled in the air.

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    The kicking or punting team is scored based on net points compared to average, taking into account both the kick and the return, if any. Because the average return is always positive, punts that cannot be returned (touchbacks, out-of-bounds, fair receptions, and punts knocked down by the coverage unit) will be rated higher than punts of the same distance. they can return. (this also applies to touchbacks on kickoffs). there are also separate individual ratings for kickers and punters that are based only on distance and whether the kick is returnable; otherwise, an average return is assumed to judge the kicker separately from coverage.

    For the returning team, the rating is based on how many points the return is worth compared to the average, based on the location of the catch and the distance the ball traveled in the air. returning teams are not judged by the distance of the shots, nor by the shots that cannot be returned. as explained below, blocked shots are so rare that they are statistically insignificant as predictors of future performance and are therefore ignored.

    Field goals are measured differently. measuring kickers by field goal percentage is a bit absurd, since it assumes all field goals are of equal difficulty. in our metric, each field goal is compared to the average number of points scored on all field goal attempts from that distance over the past 15 years. the value of a field goal increases as the distance from the goal line increases.

    kickoffs, punts, and field goals are adjusted for weather and altitude. No one will be surprised to learn that it’s easier to kick the ball in Denver or a dome than it is to kick the ball in Buffalo in December. Because we don’t yet have enough data to tailor our settings specifically to each stadium, each one is assigned to one of four categories: cold, warm, dome, and Denver. There’s also an additional setting that lowers the value of field goals in Florida (because warm temperatures allow the ball to be carried better) and increases the value of punts in San Francisco (because of those infamous winds).

    baselines for special teams are adjusted each year due to rule changes, such as the introduction of the exclusive “k-ball” for special teams use in 1999, as well as the changing of the kickoff line from 35 to 30 in 1994 and then back to 35 in 2011. The baselines have also been adjusted each year to account for the gradual improvement in kickers over the past two decades.

    once we add up the total points above or below average that can be attributed to special teams, we translate those points to dvoa so ratings can be added to offense and defense to get the total dvoa of the team. as a final step, we then normalize the dvoa special teams to reflect the league environment in a given year. however, it should be noted that we do not yet have a method to perfectly normalize each special teams year, so the league average for special teams deviates from 0.0% in certain years, though no more than 0.5%.

    There are three aspects of special teams that have an impact on wins and losses, but don’t appear in the standard special teams rating because a team has little or no influence on them. the first is the duration of the opposing team’s kick-offs, with an asterisk. obviously, there are no defenders standing on the 35-yard line, ready to block a kickoff after the whistle blows. However, in recent years, some teams have deliberately fallen short to avoid certain top performers, such as Devin Hester and Josh Cribbs. the special teams formula now includes adjustments to give teams extra credit for field position on kick returns if kickers deliberately try to avoid a return.

    The other two elements that special teams have little control over are field goals against their team and punt distance against their team. research shows no indication that teams can influence the accuracy or strength of field goal kickers and punts, except for blocks. As mentioned above, although blocked field goals and punts are definitely skill plays, they are so rare that they have no correlation to how well teams have played in the past or will play in the future, therefore they are included here as if they were anyone another missed field goal or a missed punt, without giving the defense additional credit for their efforts. the value of these three elements is listed separately as a “hidden” value.

    Special teams ratings also do not include 2-point conversions or onside kick attempts, which, like blocks, are so infrequent as to be statistically insignificant in judging future performance.

    adjusted linear yards explained

    An exception to the use of dvoa/dyar, and the use of “game hit” instead of gross yards, is the scoring system for offensive and defensive lines. these are actually just measurements of running plays, and of course the defensive numbers don’t measure just the defensive line, but all seven forwards against the run.

    One of the most difficult goals of statistical analysis in football is to somehow isolate how much responsibility for a play falls to each of the 22 men on the field. Nowhere is this more obvious than in the running game, where one player runs while up to nine other players, including wide receivers, tight ends and fullbacks, block in different directions. none of the stats we use to measure running — yards, touchdowns, yards per carry — differentiate between the contribution of the running back and the contribution of the offensive line. Neither do our advanced dvoa and dyar metrics.

    We have enough data accumulated that we can try to separate the effect the running back has on a particular play from the effect of the offensive line (and other offensive blockers) and the effect of the defense. A team may have two running backs in its stable: RB A, who averages 3.0 yards per carry, and RB B, who averages 3.5 yards per carry. who is better from behind imagine that rb a not only averages 3.0 yards per carry, but gets exactly 3 yards on each carry, while rb b has a highly variable yard production: sometimes 5 yards, sometimes -2 yards, sometimes 20 yards. the difference in variability between running backs can be used to not only determine the difference between running backs, but also the effect the offensive line has on each running play.

    We know that at some point during each long play, the running back has gotten past all of his offensive line’s blocks. from here on out, the rest of the game depends on the running back’s own speed and elusiveness, combined with the speed and tackling ability of the defensive players. If Frank Gore runs 50 yards down the line, fending off tacklers to the goal line, his offensive line has done a great job, but they’re not responsible for most of that run. How much are they responsible for?

    For each running back carry, we calculate the probability that the running back involved ran for the specified yards on that play, based on that running back’s average yards per carry and the variability of his yards on each play. We also calculated the probability that the offense would gain the number of yards based on the team’s average rushing yards and variability without the running back participating in the play, and the probability that the defense would give up the specific number of yards. based on his average rushing yards allowed per carry and variability. for example, based on their running average and variability, the probability in 2004 of the tiki barber having a positive run was 80%, while the probability of the giants having a positive carry with no barber running was only 73 %.

    Yards end up falling in roughly the following combinations: turnovers, 0-4 yards, 5-10 yards, and 11+ yards. In general, the offensive line is 20% more responsible for yards lost than yards gained up to 4 yards, but 50% less responsible for yards gained from 5 to 10 yards, and not responsible for yards passed. thus, creating tight line yardage.

    adjusted rushing yards take each rush from a running back and apply those percentages. (We’re not including runs by receivers, which are typically based on deception rather than straight blocking, or runs by quarterbacks, which are almost always deflected pass plays unless they involve someone like colin kaepernick or Cam Newton). then those numbers are adjusted. based on down, distance, situation, opponent and whether or not a team is on the shotgun. (Because defenses typically play the pass when the quarterback is on shotgun, the running back’s average shotgun carry last year gained 5.36 yards, compared to just 4.16 yards on other carries.) linear yards per carry is the same as the league average for rb yards per carry (in 2013, 4.10 yards).

    The NFL lists runs in seven different directions: left/right end, left/right tackle, left/right guard, and middle. Further investigation showed no statistically significant difference between how well a team performed in the runs indicated at center, left guard, and right guard, so we also listed the runs separately in five different directions. note that there may not be a statistically significant difference between right tackle and midfielder/guard either, but until we can investigate further (and for the sake of symmetry), we’ll continue to split runs behind right tackle separately.

    These divisions allow us to assess subsections of a team’s offensive line, but not necessarily individual linemen, as we cannot account for blocking assignments. we don’t know when a guard is shooting and when a guard is blocking forward. we know that some runners are inherently better going down the middle, and some are better going side to side, and we can’t gauge how much that affects these numbers. we have no way of knowing the blocking contribution made by fullbacks, tight ends, or wide receivers.

    Other numbers we use to measure the running game:

    • Outfield Yards gives the portion of the team’s running average gained after the first 10 yards of each run. so for a 10-yard dash, yardage is not counted; for a 15-yard dash, five yards are counted; for an 80-yard dash, 70 yards are counted. this number gives you an idea of ​​how much of a team’s running game was based on the escape velocity of running backs. a team that ranks low in adjusted rushing yards but ranks high in open field yards relies heavily on its running back breaking up long runs for the running game to work. this number is not adjusted in any way.
    • second level yards gives the portion of the team’s average run gained 5-10 yards beyond the line of scrimmage. so, for a five-yard run, the yards are not counted; for a 10-yard dash, five yards are counted; for an 80-yard dash, only five yards are counted. this number represents the midpoint between the contributions of a team’s offensive line and its running back. a low outfield yardage rating coupled with a high second-tier yardage rating indicates that the team’s offensive line is opening holes, but its running backs are not good outfield runners. this number is not adjusted in any way.
    • power success measures the success of specific running plays rather than distance. this number represents how often a third- or fourth-down rushing attempt, with two yards or less to go, scored a first down or touchdown. Since sneak quarterbacks, unlike scrambles, rely heavily on the offensive line, this percentage includes runs by all players, not just running backs. this is the only stat given that includes quarterback runs. it does not adjust based on the game situation or the opponent.
    • padding measures the percentage of runs that are stopped on or before the line of scrimmage.

    driving statistics

    The statistics section of our website also includes driving statistics. These stats are calculated from NFL driving charts and are not adjusted based on the strength of the schedule or the situation. knee strikes at the end of halves are discarded. driving stats are generally self-explanatory, providing the total number of drives for each team, as well as average yards per drive, points per drive, touchdowns per drive, punts per drive, and turnovers per drive, interceptions per unit and fumbles lost per unit. los/drive represents the average starting field position (line of scrimmage) per drive from an offensive standpoint. driving stats are given for offense and defense, with net simply representing offense minus defense.

    a note on play-by-play data

    Our data may differ slightly from the official NFL figures due to discrepancies in different play-by-play reports. Additionally, we have adjusted the clock plays as knees no longer count as run attempts and spikes no longer count as pass attempts. Prior to 2020, we also counted aborted plays as passing plays, not rush plays, unless the play-by-play specifies that the play was an aborted handoff. Beginning in 2020, we will count aborted plays as rush plays in the same manner as official NFL stats.

    See also: The Pop Warner Offense That Confounded Sean Payton, and What It Says About Offensive Innovation in the NFL

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