Fantasy Composting: Digging Into Garbage Time
As fantasy enthusiasts, we recognize that production is mainly a function of talent and opportunity. Thankfully, resources that aid in differentiating players along those lines abound. Yet once we digest 40-times, size, snaps, routes, and targets, to name just a handful, we remain hungry for further differentiators.
The idea of “garbage time” sometimes seeps into this discussion and typically is discarded. But should it be? For an especially sick segment of degenerates who, if given the opportunity, may or may not be above sifting through a player’s trash just to get an infinitesimal edge on the competition, delving into the phenomenon known as garbage time seems far less distasteful.
Before deciding if we care enough to examine how individual players perform during garbage time, we need to weigh whether or not it is even a dumpster worth diving into. Do teams actually take advantage of “prevent defenses,” and, if so, to what degree? If performance spikes do exist, can we capitalize on them in a meaningful way? Grab your rubber gloves, because we are going to pick through these questions and more, as we attempt to salvage some usable fantasy items from a heaping statistical landfill.
Like last summer, we are again defining garbage time as any play that occurs in the second half of a game in which one team is losing by at least 15 points. While such a deficit is not completely insurmountable, the goal is to identify game situations during which defenses begin to shift focus toward preventing chunk plays and quick scores, more so than contesting every last yard. Defensive and special teams statistics have been omitted from all data.
10.5 Pounds of Garbage in an 8 Pound Bag
In 2013, there were 2,675 plays that took place during garbage time as defined above, or 8 percent of all offensive snaps (33,302). Teams that were trailing during garbage time scored 105 touchdowns, or 8.6 percent of all offensive touchdowns (1214).
Losing teams hit paydirt on 3.9 percent of their 2013 garbage time snaps, while the overall league-wide scoring rate was 3.6 percent. That may not seem eye-popping, but it is the difference between a touchdown on every 25.6 snaps versus one for every 27.4 snaps. In other words, if the league had scored at the same pace that losing teams did during garbage time, there would have been more than 85 additional touchdowns scored in 2013.
The Oakland Raiders ran 16.9 percent of their plays while down at least 15 points in the second half of games and scored 27.3 percent of their touchdowns during those snaps. If they had scored at the same rate as they did while losing during garbage time (one per 18.8 snaps), their 53 offensive touchdowns would have ranked second only to Denver. Instead they placed 22nd with 33 scores.
Touchdowns are not the only area in which garbage time gives offenses a boost on what they usually accomplish, and the worst teams in the league are not the only ones taking advantage. The Indianapolis Colts ran 11.1 percent of their plays while trailing more than two touchdowns during the second half of games and compiled 15 percent of their total offensive yards during that time.
Not surprisingly, that figure is buoyed by passing totals, as the Colts gained 19.7 percent of their air yards during the 11.1 percent of plays spent in garbage time. They gained 3.6 passing yards for every offensive snap during the 2013 season, but 6.5 per play during garbage time. At that rate, the Colts would have thrown for 6,650 yards, or nearly 3,000 more than they actually did.
Obviously that is an unrealistic total — Denver led the league with 5,444 passing yards — but it tells us two things. The first is not news, and if the whole “working with Andrew Luck” thing fails, Pep Hamilton can always fall back on a career as a 1920s high school coach. The second is that, like touchdowns, a lot of passing yards are packed into a representatively smaller segment of plays during garbage time. To be exact, 10.5 percent of the NFL’s passing yards were gained by teams losing in garbage time, which encompassed 8 percent of 2013 offensive snaps.
The tricky part is finding a way to harness the runoff from what clearly are game situations that produce touchdowns and passing yards at a higher than usual rate.
What’s In This Garbage?
As can probably be gleaned from the details above or even a loosely educated guess, there is not an enormous amount of running being done by teams that are trailing during garbage time. The fact that even Pep Hamilton was airing it out tells us everything we need to know, but for the sake of math it should be mentioned that losing teams passed on 76 percent of their garbage time snaps in 2013. That number was up from 54.4 percent overall.
What may not be entirely intuitive is the fact that teams did not pass particularly well when defenses “relaxed” during garbage time. Volume was up, but efficiency was largely down.
|Situation||Yard/Play||Comp %||TD %||INT %||Sack %||Yard/Att.||QBR|
Yards per play is the only category listed in which garbage time outperformed the league norm. That has a lot to do with the fact that while runs gained 4.2 yards overall, they went for 4.8 yards per attempt during garbage time when losing teams were handing off.
With teams throwing like crazy to catch up against defenses that were pinning their ears back to get to the passer while defending against big plays, it makes sense that sack rates were up and yards per attempt were down. Throw in the fact that teams who often trail in garbage time tend to not be very good to begin with, and it hammers home the point that statistical gains come mainly via volume.
Listed below are the teams that ran at least 10 percent of their plays while down 15 or more points in the second half of their games. Also detailed is the percentage of their total yards, passing yards, and touchdowns that were accrued during garbage time. Next to each of those is a column (Diff.) in which it is compared to their overall garbage time percentage. This allows us to see which teams took advantage of garbage time and which did not.
|Team||GT Plays||GT %||GT Yard %||Diff.||GT Pass Yard %||Diff.||GT TD %||Diff.|
The first thing that jumps out is the fact that a vast majority of the teams who spent the most time losing in garbage time were among the worst in the league. This is not shocking and can be viewed as a positive as far as predictability is concerned.
It is far less encouraging that the offenses of the Texans and Buccaneers not only gained zero boost from trailing in garbage time but actually produced at a weaker rate. The Vikings’ and Jets’ offenses did not exactly set the world on fire either. It appears that simply being a bad team and destined for a large portion of snaps while trailing in garbage time does not automatically equate to greater production while in those situations.
Incidentally, the five teams that spent the most time getting blown out late in games did not fire their head coaches. However, the five teams on the list whose coaches were canned fared poorly during garbage time relative to the other squads listed, with the possible exception of Washington. It may be coincidental, or it may mean that if your team cannot even muster better production against defenses that are backing off during garbage time, you might want to brush up the resume.
One Man’s Trash …
We now know that touchdowns and passing yards occur at a noticeably higher rate during garbage time. It is also obvious that bad teams are trailing by at least two touchdowns in the second half more than other squads. However, since we cannot be certain which of those offenses will best capitalize on more accommodating situations or take any advantage at all, making concrete recommendations based on anticipated garbage time is difficult. While this is somewhat discouraging, it does not require us to throw the baby out with the bathwater.
Since we know that juicing offensive statistics during garbage time is relatively unpredictable, it stands to reason that individual players who are positive outliers are due for some degree of regression. To search out those who derived a disproportionate amount of their fantasy production during garbage time, I examined 200 players, most of whom led the league in garbage time statistics.
I added a handful of other notable names to the sample for comparison sake, and simply because it is interesting to note that Jamaal Charles’ 39 garbage time rushing yards represented just 1.03% of his PPR league points total. Considering Kansas City spent 2.82% of their snaps trailing in garbage time, we can confidently say that Charles earned his title as 2013’s best fantasy running back. Not that this was a question.
The key figure by which these players will be ranked is what we will call “adjusted Garbage Time percentage” (aGT%). It is simply the difference between the percentage of points that a player accumulated while trailing during garbage time, minus the percentage of time his team spent in garbage time. In Charles’ case, his aGT% would be -1.79 because he accrued a smaller percentage of his stats during garbage time than the Chiefs spent there.
While examining a stud like Charles is interesting, we are actually seeking players on the opposite end of the spectrum so we can identify performers who derived a disproportionately large percentage of their fantasy points during garbage time.
An example would be Da’Rick Rogers of the Colts. He put up 86 yards and two touchdowns on four catches while Indy was losing in garbage time. His 24.6 garbage time points represent 55.4 percent of Rogers’ PPR league total of 45.2 points. The Colts only spent 11.1 percent of their snaps losing in garbage time, so Rogers’ aGT% is 43.4 percent. That is a huge number, and second only to Buffalo’s Chris Gragg, who scored so few points this season (16.3) that the results are not significant.
There were 33 players who had an aGT% of at least 5 percent and scored at least 100 fantasy points, including a pair who finished 2013 ranked in the overall top 20. Just because a player appears on this list does not necessarily mean they are due for a statistical decline, but it undeniably means that they enjoyed a disproportionate amount of production during garbage time in 2013.
|Player||Team||PPR Pts||GT Pts||GT%||Team GT%||aGT%|
The issue with adjusting a player’s production percentage with the amount of time their entire offense spends in garbage time is that it does not account for the exact snaps that the player was on the field. They may be spending time on the bench during a blowout, for example. Alas, we do not have that precise information available and are forced to utilize a still useful, if somewhat blunter, tool.
We will wrap up with a look at several individual players and what their inclusion may mean for the 2014 season.
Josh Gordon – Because there is precious little not to like about Gordon’s game, it sticks out like a sore thumb that he feasted so deeply during garbage time that Jared Lorenzen’s mouth watered. Cleveland spent the 11th-most time trailing by more than two touchdowns in the second halves of their games, and the bet here is that will not be repeated in 2014 despite their front office disarray. Improved quarterback play, and a seemingly inevitable increase on his single red zone score, will need to make up for what he is unlikely to repeat in garbage time production (17 catches, 338 yards and two touchdowns).
Brandon Myers – Proclaimed the Garbage Man before last season, somehow the Giants’ tight end managed to weasel his way inside the top 20 at his position. Of course he was unusable in fantasy for all but a small handful of weeks, and only reached the heights of TE19 due to an unnatural talent for stat padding. Assumed to be in for fewer garbage time opportunities with his move to New York, their disappointing season allowed Myers to again catch half of his touchdowns and over 20 percent of his yards while games were out of hand. His pathetic blocking skills will work against him on the free agent market, yet it seems unwise to completely disregard fantasy’s top garbage man.
Indianapolis Colts (3) – Luck, Coby Fleener, and T.Y. Hilton are among the highest scoring players on the list and it is a strong bet that they will not be making a return appearance. Anticipated upgrades to the offensive line and defense should have Indy spending less time trailing big late in 2014 games, not to mention afford their smash-mouth offensive coordinator extra opportunities to have Luck hand the ball off. We have yet to see Pep willingly choose to go pass-heavy on a consistent basis, and until we do, it is hard to expect otherwise.
Chad Henne – Both he and his top target, Cecil Shorts, were forecast to be premiere garbage time stat padders and that was one of the few areas in which they delivered. Ace Sanders also was touted and wound up accruing 27 percent of his stats during garbage time and posting a 4.1 aGT% in the process. This is a well that will likely run dry as the Jaguars seem to be moving in the right direction, especially on defense. Many moving parts must be accounted for before training camp, but it would be a surprise if Jacksonville again led the NFL in total garbage time percentage.
Jake Locker – The Titans only spent the 20th-most time trailing big in the second half, but Locker managed to show up on the aGT% leaders anyway. He just made the 100 fantasy point cutoff and might be an example of a blind spot in the aGT% metric due to his missing so many of Tennessee’s snaps in 2013. Still, the fact that nearly 18 percent of his production came during the rare window that his team was losing in garbage time does not help his case that he should pilot the Titans under new coach Ken Whisenhunt.
The last chart below details the same thing as the one above, only these are the players that took disproportionately little advantage of their opportunities while trailing in garbage time. It does not automatically mean that next season will be different, especially as a number of these players are on quality teams and probably will spend little time losing big late in games. I cut it off at an aGT% of -3 percent to keep the number of players listed more manageable.
|Player||Team||PPR Pts||GT Pts||GT%||Team GT%||aGT%|
It is nice to see one of the receivers forecast last August as a probable leading garbage time stat padder, Jeremy Kerley, in the bottom 10 in aGT% (no, it’s not). Yet it is another example of the unpredictability of garbage time, where betting on positive production feels like herding rabid, catnipped felines.
While we can definitely declare that garbage time possesses a higher-octane statistical output, the rub has always been translating that into usable fantasy methods. Forecasting regression is likely to prove true among the positive outliers, but is by no means a universal rule. It is best looked at as a stern warning. However, aGT% did tell us one thing for certain. The Garbage Man’s unnatural talent is going to cost fellow free agent Hakeem Nicks some money.
In addition to Pro Football Focus data, statistics for this article came courtesy of Pro Football Reference and its invaluable Game Play Finder.
Pat Thorman is a Lead Writer for PFF Fantasy and was named 2013 Newcomer of the Year by the Fantasy Sports Writers Association. You can follow him on Twitter at @Pat_Thorman