-
Mike Clay, ESPN Writer
If you want to dominate your fantasy football league, it’s important to cut out the noise and prioritize actionable statistics and information.
Football is a game with infinite variables, so sorting through a seemingly endless wilderness of data can seem overwhelming. Below is a breakdown of the statistical categories I focus on when making decisions for my fantasy teams. Some are basic and others more advanced, but understanding the importance of each will help you take your game to the next level.
Opportunity
Fantasy football has been around for a long time, and yet the massive importance of volume remains grossly understated. In a nutshell, the greatest football player in the world can’t accrue fantasy points if he’s standing on the sideline or not touching the football. On the flip side, even a pedestrian athlete can achieve fantasy viability simply because he has a significant role.
This is especially the case for running backs, who struggle to stay healthy and are less reliant on the splash plays we see often from quarterbacks and wide receivers. One easy way to see this in practice is by considering the value added by a big role in the passing game. For example, last season, Leonard Fournette had an ugly-looking 189-668-3 rushing line. His 3.5 yards per carry was dead-last among 38 RBs with at least 120 carries. On the other hand, Jamaal Williams posted a 262-1,066-17 rushing line and that TD total was tops in the NFL.
Which of those two backs scored more fantasy points in 2022? Believe it or not, it was Fournette. The Tampa Bay tailback had a 73-523-3 receiving line on 84 targets, compared to a 12-73-0 line on 16 targets for Williams. That’s a difference of 124 fantasy points, or 7.3 per game over 17 weeks.
Is that an extreme example? Sure, but there’s a reason why superstar Nick Chubb has never finished a season outside the top 10 in rushing yards but has yet to produce a top-five fantasy campaign. He’s simply not much of a factor in the passing game, and that matters in fantasy football.
It’s for that reason we should be wary about the fantasy upside of players like J.K. Dobbins (1.0 targets per game last season), Rashaad Penny (1.0), Miles Sanders (1.5) and Isiah Pacheco (0.8), but perhaps feel better about the likes of Rhamondre Stevenson (5.3), D’Andre Swift (5.0), James Conner (4.5) and Antonio Gibson (4.1).
I should point out that carry volume is important, too, but considering that the average RB target is worth 2.5 times as many fantasy points as the average RB carry, it’s extremely important to not overlook each back’s involvement in the passing game.
For quarterbacks, rushing production can’t be understated. Daniel Jones scored 112.8 points with his legs last season (7.1 per game), which helped him post the position’s ninth-highest point total even though he ranked 15th in passing yards (3,205) and 21st in passing TDs (15). He scored more fantasy points than three quarterbacks who posted 4,400-plus passing yards and five who tossed 25-plus touchdowns.
One final thought here: We are often tricked by big plays and short spurts of dominance (usually fueled by touchdowns), and that leads to poor starting-lineup decisions. Yes, I know, there are exceptions. Diontae Johnson defied the odds last season when he failed to score a single touchdown despite 86 receptions (a dubious NFL record) and 10 end zone targets. George Kittle, meanwhile, scored on 11 of his 86 targets last season. These things always regress to the mean eventually, but in a 17-week season, it’s possible for the occasional outlier to sustain itself longer than expected. Of course, the exception is not the rule. Focusing your attention on players who consistently rack up pass attempts, carries and targets (raw totals and team shares), especially of the high-value nature, is Step 1 in improving your team’s odds for victory.
Team stats
Once you have a general idea of each player’s opportunity, you can take the next step and look at how the player’s team will impact his production. This includes, but is not limited to, touchdown scoring, playcalling and coaching trends.
Offensive schemes matter, and the head coach/playcaller turnover in this league is absurd. (Fun fact: Only three active offensive coordinators were hired to their post prior to 2021.) Keeping tabs on coaching changes is important because a scheme adjustment could cause a swing of hundreds of snaps (and in turn, hundreds of fantasy points).
Here’s an example: Last season, the Buccaneers operated the fastest offense (fewest seconds between plays), which helped them post a league-high 1,159 snaps. The Panthers, meanwhile, ran the seventh-slowest offense and ended up with a league-low 976 snaps. That’s a difference of 10.8 plays per game, which is obviously a huge disparity in opportunity to score fantasy points.
Looking forward, Arizona’s offense is one likely to be severely impacted by scheme change this season. Kliff Kingsbury is out as playcaller (Arizona ranked fourth or better in pace of play during each of his four seasons) and in is Drew Petzing, who comes from a Kevin Stefanski coaching tree built around a run-first/slow-moving offense. We should expect less volume for Arizona’s skill players this season. The same goes for aforementioned Tampa Bay, though this is one more player driven. With Tom Brady gone, the Buccaneers are unlikely to call as fast-paced or pass-heavy an offense.
Another piece of this is game-script-adjusted playcalling. The Eagles called pass 56.5% of the time last regular season, which was the league’s 11th-lowest mark. So they’re a run-first team, right? Wrong. A deeper look shows that Philadelphia was ahead on the scoreboard on a league-high 55% of its offensive plays last season. If we adjust for game script, the Eagles actually called pass at the 11th-highest rate in the league. Philadelphia called pass 63% of the time during the first three quarters of games, but 38% of time in the fourth quarter. This is something to consider as teams improve (or get worse) during the offseason.
Fantasy points
Historical fantasy points are another good resource for projecting future production, and although that might seem obvious, it’s important that you absorb the totals with proper context.
Though there is a lot of value in durability, a player like Najee Harris is a good example of raw fantasy point totals not aligning perfectly with fantasy value. Harris appeared in all 17 games and was fantasy’s No. 14 running back last season. Of course, if you used him all 17 weeks, you didn’t get quite that level of production. Harris produced one weekly finish better than ninth all season and was outside the top 20 RB scorers in nine of his first 12 games prior to a solid finish to the campaign. Mike Evans, meanwhile, finished 17th among WRs in fantasy points, but scored 22% of his points in one game (Week 17) and averaged 8.9 points per game the prior seven outings. Daniel Jones was an interesting case at quarterback, as he finished ninth in fantasy points but registered only five top-10 weeks (13 QBs had more). Despite where he finished, Jones didn’t give you a weekly edge in most formats and was more of a high-floor QB2.
In addition to “startable weeks,” points per game can also be useful. Just be sure to consider factors such as games in which a player left early because of injury or was playing a different role. For example, Christian Watson averaged 11.7 fantasy points per game last season. That’s far from top-end production (it checks in 32nd among qualified WRs), but consider that he wasn’t an every-down player until Week 10. From that point on, he averaged a more impressive 17.2 points per game (10th best).
By the way, I’ve probably gone too far without mentioning the importance of reviewing and understanding your league scoring. Is it PPR? Do quarterbacks get four or six points for a passing touchdown? Do they get one point for every 20 or 25 passing yards? What’s the punishment for turnovers? Are return yards or touchdowns involved? You don’t need to factor every little category into your rankings, but some of these can have significant implications on a player’s potential output.
Rate stats
We’ve focused primarily on the basics thus far, but you’ll need to take an even deeper dive if you want to ensure you’re competitive each and every year. This is where the sustainability of rate stats and regression to the mean come into play. As noted earlier, volume is king in fantasy football. There is no better predictor of fantasy points over large samples. Of course, there are always those players who do their best to break the system. Jamaal Williams, Diontae Johnson and Taysom Hill come to mind from last season. Even these players can’t be expected to sustain obscene efficiency (or inefficiency) over long spans. Williams and Kittle are two players we can expect to score substantially fewer TDs in 2023, whereas Johnson and DK Metcalf are candidates for a boost (more on this in my upcoming annual set of TD regression to the mean articles).
And this doesn’t apply only to touchdowns. From 2011 to ’21, there were 24 instances of a quarterback finishing a season with 300-plus pass attempts and a YPA of at least 8.25. All 24 QBs saw a decrease in YPA in their next season, with the combined average falling from 8.57 to 7.52. This is most notable for Tua Tagovailoa, who was the only QB in the league with a YPA above 8.10 last season. Tagovailoa’s 8.87 YPA is the fifth-highest single-season mark since 2011, but you’ll notice his projection checks in a full yard lower for 2023. That’s not an accident.
This might seem a little overwhelming, especially if you’re new to the game, but just keep in mind that you don’t need to be a data scientist to figure some of this stuff out. If you notice a player’s touchdowns aren’t aligning with his usage, or a veteran quarterback is well off his career efficiency numbers, it’s time to consider a buy-low or sell-high opportunity. If something seems wacky and unsustainable, it probably is.
Next-level stats
If you’re a stat nerd like myself, it’s a good time to be alive. Thanks to a new age in game charting, we have more game information than ever before. In most cases, it’s data that can be applied to fantasy football.
Snaps and routes: This is the next step in our earlier discussion about carries and targets. If a player is racking up touches but is rarely in the game, that’s a red flag that needs to be explored before you invest in said player. Similarly, if a player is in the game often but is spending a lot of time blocking instead of running routes, he’s unlikely to post consistent fantasy production. Understanding a player’s role is key to projecting future output.
Expected fantasy points (xFP) and expected touchdowns (xTD): Red zone carries and targets are referenced often in this industry, but they are grossly distorted. A carry from the opponent’s 1-yard line, for example, is not equal in value to a carry at the 19-yard line. These days, red zone stats are outdated thanks to xTD (formerly called OTD), which weighs each carry/target and converts the data into one number that indicates a player’s scoring opportunity. Taking it even further, we can dive into end zone targets (balls thrown to the player while he’s already inside the confines of the end zone) and carries from any threshold (for example, inside the 5-yard line). This is your best avenue to discovering players likely to improve or see a dip in their touchdown totals. Expected fantasy points (xFP) is the same concept but also considers expected outcomes in all fantasy categories, including receptions and yards. Some of the stats referenced in this piece are easier to find than others, but I post weekly leaderboards on the site throughout the regular season. Here are the final xTD and xFP leaderboards from 2022.
Expected points added (EPA): The ESPN Stats & Info team does an excellent job creating innovative data to help us better understand the game. This includes metrics like pass and run block win rate to help us analyze offensive line play, as well as the counter to that, pass rush win rate, which helps analyze defenders. Another metric that can be very valuable in understanding overall offensive and defensive play is EPA, which shows us — at a team or player level — how much value is added on each play. We can use this to properly rate teams and players, as well as to identify teams whose record could be misleading. An example of this is the 2022 Pittsburgh Steelers, which finished 29th in offensive TDs (28) but 18th in offensive EPA (1.2). This suggests the Pittsburgh offense was better than it may have seemed last season and, perhaps with a leap forward from second-year QB Kenny Pickett, could surprise in 2023.
Offensive personnel packages: One way to predict snaps and targets is to look at each coach’s and team’s historical personnel usage. For example, last season the Vikings had three or more wide receivers on the field for 73% percent of their offensive plays, which was sixth highest in the league. Even if first-round rookie Jordan Addison doesn’t immediately beat out K.J. Osborn for No. 2 duties opposite Justin Jefferson, it may not matter in this scheme, as the rookie will still be on the field a ton. It’s also a way to see through nonsensical noise such as “I bet they’ll use a lot of two-running-back sets” or “they’ll go with two tight ends more.” Personnel usage shows us that the 2022 league-wide average for two-plus-RB sets when passing was 8% (mostly fullback driven, as 25 teams were under 10%) and the average for two-plus-TE sets was 20%.
Average depth of target (aDOT): Also referred to as “air yards,” aDOT has now been around for a little more than a decade and has quickly proved to be a better way of understanding and projecting the future production of receivers. “Yards per reception” and “yards per target” are referenced most often, but both can be distorted by the variance that comes with small samples and the deep ball. As a result, neither are as predictive as aDOT. Of course, aDOT also counts all targets, whereas YPR and YPT can use only receptions in the sample. During the 2022 season, that meant an additional 5,728 plays that could be factored in. DJ Chark Jr. (15.6) posted the highest aDOT and Deebo Samuel (4.0) the lowest among wide receivers last season (minimum 50 targets).
On-target throws: Improved game charting allows us to break down pass attempts even further than in the past. Was the ball tipped at the line? Was the passer hit while throwing? Did the defender knock away a well-thrown ball, or was it overthrown or underthrown? By looking at the percentage of each pass attempt that is “off target,” we can better assign blame and improve our future prognostication, especially for players who change teams. For example, last season, Garrett Wilson ranked sixth among WRs in targets, but 16th in receptions due to a 56% catch rate (78th among 85 qualified receivers). The issue? Poor QB play, as 22% of balls thrown his way were charted as “off target.” Enter Aaron Rodgers, who even in a down year in 2022 was better than average in completion rate (65%) and off-target rate (15%).
Wide receiver vs. cornerback matchups: By charting where each player lines up, we can better project matchups between wide receivers and corners. Knowing that Patrick Surtain II will shadow on the perimeter but Sauce Gardner simply stays at home is extremely valuable data as we evaluate each wide receiver’s weekly fantasy value. To make your life easier, I’ve been tracking and projecting every WR/CB matchup since 2015 and will continue to do so in 2023.
Sponsored Content
Juega en grande con cryptomonedas
