If you want to dominate your fantasy football league, it’s important to cut out the noise and prioritize the correct 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. For quarterbacks, rushing production can’t be understated. Tyrod Taylor scored 94 points with his legs last year (6.3 per game), which helped him to the position’s eighth-highest point total even though he barely eclipsed 3,000 passing yards and threw 17 touchdowns. He scored more fantasy points than six quarterbacks who posted 4,000-plus passing yards and 20-plus touchdowns.
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. Hakeem Nicks defied the odds in 2013 when he failed to score a single touchdown on 102 targets, including nine end zone targets. Jordy Nelson, meanwhile, scored on 15 of his 102 targets (seven in the end zone) in 2011. These things always regress to the mean eventually, but in a 16-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 one 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, play-calling and coaching trends. Last year, the Falcons’ offense scored an NFL-high 58 touchdowns (3.6 per game) during the regular season. The Rams and Texans tied with a league-worst 23 scores (1.4 per game). That’s a difference of 35 touchdowns, or a whopping 210 fantasy points to pass-catchers. It might seem obvious to adjust the value of players working in great offenses (New Orleans, Green Bay, New England) and poor ones (New York Jets, Los Angeles Rams, Cleveland Browns), but digging deeper can help you find values. Consider the Arizona Cardinals, who by most accounts had a disappointing 2016 season. The Cardinals still produced 3.0 offensive touchdowns per game, which was sixth-highest in the league. The Giants have Odell Beckham Jr. and went 11-5 last year, but they still struggled to 1.9 offensive scores per game (23rd).
Understanding a team’s play-calling and offensive style is also important. The Patriots called pass 57 percent of the time during the 2016 regular season (fourth-lowest). So they’re a run-heavy team, right? Wrong. A deeper look shows that New England was ahead on the scoreboard for an astounding 68 percent of its offensive plays last year, the highest in the league. If we adjust for game script, the Patriots were actually the eighth pass-heaviest team in the league. This is something to consider as teams improve (or get worse) during the offseason.
Taking a look at total offensive snaps can also be valuable. The Saints averaged a league-high 69.1 offensive plays per game last year, whereas the Dolphins averaged an NFL-low 57.0. That’s a difference of more than 12 potential touches per game and 194 per season.
Each year, I take a thorough look at historical coaching trends in order to best project team and player projections. In fact, many of the most notable observations I made this offseason can be found in this piece. One of the most intriguing nuggets from that article has led me to select Vikings TE Kyle Rudolph in as many leagues as possible this year. Rudolph was fantasy’s No. 2 scoring tight end and posted a position-high 11 top-10 fantasy weeks last season. History shows that teams led by Minnesota head coach Mike Zimmer and offensive coordinator Pat Shurmur have kept their tight ends very involved in the passing game.
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 Frank Gore is a good example of raw fantasy point totals not aligning perfectly with fantasy value. Gore appeared in 16 games and was fantasy’s No. 12-scoring running back last year. Of course, if you used him all 16 weeks, you didn’t get quite that level of production. Gore’s best fantasy week was a seventh-place finish, which accounted for one of his two top-10 finishes. That 12.5 percent rate ranked 33rd at the position. Blake Bortles, Andy Dalton and Tyrod Taylor each finished 2016 as top-12 fantasy quarterbacks, but none of them posted more than five top-10 fantasy weeks. The likes of Brian Hoyer, Colin Kaepernick and even Blaine Gabbert finished in the top 10 at a higher rate and were thus the more savvy start during weeks they were under center.
In addition to “startable weeks,” points per game can also be useful. Just be sure to consider factors such as games where a player left early because of injury or was playing a different role. For example, Jay Ajayi averaged 14.3 fantasy points per game last year. That’s far from top-end production, but consider that he was a backup until Week 5. From that point on, he averaged a more impressive 16.1 points per game.
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 categories 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. Tyreek Hill, Kenny Stills and the Falcons’ offense come to mind from last season. Even these players can’t be expected to sustain obscene efficiency over long spans. Stills is a terrific example of a player whom you should expect to score fewer touchdowns this season. He scored on nine of his 47 receptions last year. That touchdown rate (19.1 percent) ranks 22nd among all players who have recorded at least 40 catches in a season over the past decade (including playoffs). Of the 70 players scored a touchdown on at least 15 percent of their receptions during the span, 65 (or 92.9 percent) scored fewer touchdowns and 62 (88.6 percent) posted a lower touchdown rate the next season. The average change in touchdown total was a dip of 6.1 scores.
The Falcons’ offense is notable especially as it pertains to Matt Ryan. Ryan averaged 9.26 yards per attempt last season, which is the highest we’ve seen since Kurt Warner posted a 9.88 mark in 2000. Common sense suggests Ryan won’t sustain that absurd level of efficiency in 2017, but a deeper look at his efficiency helps explain the career year. Ryan’s receivers dropped only 10 passes, which works out to a 1.9 percent rate (the league average of 3.8 percent would’ve doubled his drop total). His receivers also generated 6.2 yards after catch (the league average of 5.1 would’ve cost him 410 yards). A bit of math shows that normalizing his drop and RAC would’ve resulted in a more reasonable, albeit still good, 8.3 YPA. This might seem like a lot to take in, 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 unique 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 of 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.
Opportunity-adjusted Touchdowns (OTD) — Red zone carries/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. Now, the stats are outdated thanks to 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). This is your best avenue to discovering players likely to improve or see a dip in their touchdown totals. Some of the stats referenced in this piece are easier to find than others, but I post a weekly OTD leaderboard on the site throughout the regular season. Here is the final 2016 OTD leaderboard.
Offensive personnel packages — One way to predict snaps and targets is to look at each coach and team’s historical personnel usage. For example, last year the Lions had three or more wide receivers on the field for 91 percent of their pass plays, which was third-highest in the league. Should Kenny Golladay nail down the team’s No. 3 receiver job, he’ll be positioned for a massive rookie-season role in this scheme. It’s also a way to see through nonsensical noise such as “I bet they use a lot of two running back sets” or “they’ll go with two tight ends more.” Personnel usage shows us that the league-wide average for two-plus running back sets was 7 percent (the Falcons were first at 20 percent) and the average for two-plus tight end sets was 20 percent (the Eagles were first at 38 percent) when teams were passing last season. Keep this in mind when considering the fantasy value of players in units like the Saints’ backfield and the Buccaneers’ tight ends.
Average Depth of Target (aDOT) — Also referred to as “Air Yards,” aDOT has been around for only five years but has 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 YPR can only use receptions in the sample. During the 2016 season, that meant an additional 6,130 plays that could be factored in. J.J. Nelson (16.9) posted the highest and Cordarrelle Patterson (4.7) the lowest aDOT among wide receivers last season (minimum 50 targets).
On-target throws — This is a relatively new concept, but improved game charting now allows us to break down pass attempts even further. 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, Brandon Marshall‘s catch rate dropped to 47 percent from 63 percent in 2015. That was despite the fact that his aDOT and drop rate changed only slightly. The huge dip can almost be blamed solely on poor quarterback play. In 2015, 13 percent of balls directed at Marshall were off target. That mark jumped to 31 percent (second-highest) in 2016. Marshall now heads to the Giants, and Eli Manning has ranked near the league average in off-target throws each of the past five years.
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 Peterson shadows all over the field (including the slot) but Marcus Peters simply stays at home is extremely valuable data as we evaluate each wide receiver’s weekly fantasy value. To make your life easier, I projected every WR/CB matchup and analyzed the key showdowns throughout the 2016 regular season and will do the same in 2017.