How Well Did High-Ownership Players Perform for Daily Fantasy Football in 2018?
"If your friends jumped off a cliff, would you do it, too?"
This is usually something a random joker will say to chastise you for not thinking for yourself. After all, who doesn't love condescension from strangers?
We'd all love to have original thoughts. It's hard to be innovative in any field if you're simply going with the flow and following a path set forth by others.
But if my cliff-jumping compadres also were swallowing chalk on high-salaried running backs in daily fantasy football tournaments, I'd at least take a peek over the edge.
As we saw earlier in our investigation of 2018's perfect FanDuel lineups, popular running backs went bananas this year. Going the popular route at that position paid off handsomely, and those who faded these heavily rostered backs likely wished they had followed the public in swan-diving to the valley of fantasy goodness.
Even in a game like daily fantasy football -- where the upsides of being different are immense -- there are certain situations where thinking for yourself is overrated. At times, people are going to be good at identifying which players are worthy of our attention, and it's all right to be in lock step with them in those instances.
We just have to figure out when that's the case and when we're better suited stepping away from the ledge.
The best method for doing so is looking back at 2018 and seeing which popular plays panned out and which fell flat. If we can spot a trend for either -- whether it be a position or a specific characteristic within that position -- we can have a better idea of when we need to look elsewhere with highly rostered players.
As such, let's take a look back at these popular players from this past season. We'll be digging into how often each player was rostered in the FanDuel Sunday Million each week, something you can find each Monday on numberFire, and seeing what may have caused popular players to bust.
What can we learn from looking back at these chalky plays from 2018? Let's take a look, starting with a broad overview before going in-depth at each position.
Positional Bust Rates
Before we get to the fun stuff, we've got to do a bit of housekeeping so that what's classified as a "bust" is transparent.
So as to account for differences in each player's salary, we'll be looking at their "value" generated. This is simply the player's fantasy points divided by their salary and multiplied by 1,000. For example, a player who scores 18 FanDuel points at a salary of $9,000 would have generated 2x value.
But "value" is also wildly different at quarterback than it is at defense and special teams due to the nature of the respective positions. This requires us to have varying value thresholds for each position so that we're not being unfair to tight ends and too lenient on signal-callers.
To get this -- what we'll call -- "baseline" value, we'll look at all players at that specific position who were on at least 1% of rosters in the FanDuel Sunday Million in a given week. This allows us to see most of the relevant available players while filtering out players who had no role in the offense or who were injured entering the game. Here are those baseline values.
As you can see, it doesn't take a whole lot for a tight end to hit our baseline value. More on that in a second.
First, though, we have to decide what constitutes being "popular" in DFS. Again, that's going to depend on the position.
With FanDuel offering a flex spot this year, people were able to roster up to three running backs or four wide receivers. As such, we'll deem the "popular" plays at those positions to be the six running backs on the most rosters and the eight most popular wide receivers. For the (largely) single-player positions at quarterback, tight end, and defense, we'll look at just the top three at each slot in roster rate.
With those ground rules established, we can start to dig into the data. The best place to start is by looking at the hit rates of each position to see if certain players are worthy of extra skepticism when they're destined to be on a bunch of rosters.
|Position||Baseline Value||Percentage to Hit Value|
Tight ends had a low baseline value to hit, and it allowed them to almost lead the pack in this department. Running backs got no such allowances, and yet they still posted the top number, hitting more than 60% of the time.
In general, this means you should have felt pretty comfortable with using popular running backs during the 2018 season. This becomes even more true once we look deeper at the position and see that certain types of running backs were basically can't-miss options.
Wide receivers were not quite as rosy.
Even with a reasonably low baseline at 1.60x value, receivers still hit just 47.45% of the time. That's lower than every other position on the board.
Let's take quarterbacks out of the equation for just a second because their value scale is so different than the other positions. This chart looks at how often each position hit certain value thresholds while popular this year. In general, you're hoping to get between 2x and 3x value out of a player on a tournament roster. Wide receivers were lucky to top 1x.
Running backs and defenses provided a good number of high-upside days, topping 3x value 35.29% and 25.49% of the time, respectively. Popular wide receivers, meanwhile, managed to top 2x value just 36.76% of the time.
This gives us a good little foundation for our understanding of popular options in DFS. At running back and defense, it's acceptable to ride with the flow as we're generally pretty decent at predicting which assets will blow up at those positions. The bust rate there is also fairly low.
For wide receivers, it's the opposite. There were a couple of monster games (Amari Cooper's 217-yard, 3-touchdown day came while on 16.07% of rosters), but in general, you wanted to avoid the players destined to be popular. The upside days were rare, and the bust potential was absolutely immense. We'll chat about the exceptions to this in the section on wide receivers, but in general, you wanted to avoid the consensus here.
Tight ends are a bit of a mixed bag. Although they did hit their baseline value at the highest rate, and they did have a good number of days exceeding 2x value, you generally weren't dead in the water if you didn't have a popular tight end on your roster. Only four popular tight ends scored more than 20 FanDuel points, and Travis Kelce in Week 13 was the only guy with more than 26 FanDuel points. As such, the risk of fading a popular tight end seems low, and the less-than-1x-value rate at the position was still higher than any other.
As mentioned, we'll dig into the specific situations that may have caused certain players to bust in a second. There was, though, one ailment that hurt us at every single position: point-chasing.
When a player pops off in Week 12, it almost ensures they'll be popular in Week 13, regardless of whether their situation has actually improved or not. When both a player's popularity and salary increase without some sort of legitimate shift in their role, it can lead to heartbreak in a hurry.
This was a common refrain among heavily rostered players this year. The table below shows a couple of different data points: the average FanDuel points a player scored when popular and the average they produced the week before they were popular. It also shows how often players at each position exceeded the point total they put forth the previous week. In general, players were worse when popular than they were the week before.
|Average FD Points||When Popular||Previous Week||Percentage to Exceed Previous Week|
In line with our previous discussion, it does seem like we did a pretty decent job with defenses and special teams this year. At every other position, though, players saw their average point totals go down when they wound up on a bunch of rosters.
This requires us to do a bit of thinking before we take the plunge on a player who did well the previous week. We have to take a step back and ask ourselves if the conditions the player will have in the coming week are on par with or better than what they had when they blew up. If something changed to trigger the explosion, and that alteration is still in place for the upcoming game, it's very possible we should still be interested in the player despite the increased salary and popularity. If not, then it seems likely that we should look elsewhere.
This is also just a good general check to have in our minds. If we're planning on using a player who did well the previous week, we should look at their score and realize there's a hefty chance -- especially at wide receiver -- that they score fewer points this upcoming week. As long as that's a reality we're willing to accept, then it may still make sense to plug them onto our rosters.
This gives us three very broad starting points when it comes to players we think will be popular in a given week. First, running backs and defenses are generally acceptable regardless of how many rosters they'll be on. Second, wide receivers are a position we want to avoid if we know the player will be getting abundant attention. Third, all players -- outside of defenses and special teams -- are likely to see a scoring regression the week after they have a big game.
With those baselines established, let's break down each position and see under which conditions players were more likely to succeed, giving us better context for knowing when a popular player is truly a risky bet. We'll start off with quarterbacks and work from there.
Before we can deploy the fruits of this exercise and judge when we want to use popular players, we first must know who will be popular in a given week. Sites like FanShare can help us see who is generating buzz, and other sites will have their own ownership projections within a given week. But overall, it helps to know what a heavily rostered player at each position looks like.
As such, for each position, we'll start with the average composition of a popular play there before delving into bust rates in certain situations. Here's what the average popular quarterback looked like in 2018.
The first number that should jump out at you here is the salary. As noted in our aforementioned study of perfect lineups, it was often profitable to save salary at the position in order to splurge on high-salary running backs. But the $7,996 average salary of popular quarterbacks was a decent amount higher than the $7,647 average salary of perfect quarterbacks.
Part of this is due to the nature of perfect lineups, where the hit rate on volatile, cheaper quarterbacks is going to be 100%. We're always getting players on the high end of their range of outcomes in that setting. However, that doesn't explain all of the gap.
In looking at our 51 popular quarterbacks this year, 24 of them had salaries of $8,000 or higher. That leaves 27 who had salaries lower than that. The cheaper quarterbacks hit their baseline value of 2.49x far more often.
|Salary||Percentage to Hit Value|
|$8,000 or Higher||45.83%|
|Lower than $8,000||62.96%|
If the perfect lineup piece didn't convince you to pay down at quarterback, this likely should.
This is obviously far from being a universal truth. In Week 13, Patrick Mahomes had a salary of $9,500, and he still wound up wiggling into the perfect lineup because the dude is a cyborg. Those instances, though, where a high-salaried quarterback fully came through were more the exception than the rule.
A 62.96% hit rate for quarterbacks with salaries below $8,000 is higher than we saw at any single position in our original chart. Conversely, the 45.83% hit rate for more cost-prohibitive quarterbacks would rank last among all positions. We should be willing to follow the public when it comes to quarterbacks with lower salaries, and their costly counterparts are the exact opposite.
Another thread that popped up when investigating perfect lineups was that we wanted our quarterbacks to be in projected tight games. Seven of 17 perfect quarterbacks were on teams that were slight underdogs, and an additional three were slight favorites. Not shockingly, quarterbacks in these tight game scripts also did well when they were popular.
|Spread||Percentage to Hit Value|
|Favored by 10 or More||33.33%|
|Favored by 5 to 9.5 Points||53.85%|
|Favored by Fewer Than 5 Points||80.00%|
|Underdogs by Fewer Than 5 Points||60.00%|
|Underdogs by 5 or More Points||33.33%|
If we combine the two middle categories together, 15 of 20 popular quarterbacks in games with a spread of less than five points wound up hitting their baseline value. The hit rate slid to 41.94% for quarterbacks in games that were projected to be less competitive.
Once again, the key spot here is the quarterbacks on teams that were slight underdogs. Only 5 of our 51 popular quarterbacks were on teams that were underdogs by fewer than five points, meaning that there were more perfect quarterbacks in that script despite the sample being just one-third the size.
Heading into 2019, we need to make sure we're conscious of the value of close games. If a quarterback figures to be popular in a game that could be a blowout in either direction, we need to pump the brakes, even if they do provide a steady floor. The bust rate in these blowouts is way too high for us to tolerate.
It is fully acceptable, though, to swallow chalk at quarterback in the right conditions. Specifically, we want a quarterback whose salary is below $8,000 and who is projected to be in a close game. Of 14 popular quarterbacks who checked both those boxes this year, only 3 failed to hit baseline value. This is the archetype of player we want to target most aggressively going forward.
As mentioned at the beginning, running backs were phenomenal for DFS this year. This was especially true when they came with a high price tag.
Before we dig deeper into that, let's get our broad overview of the position. Popular running backs were generally costly, on teams that were favored, and in projected high-scoring games.
That's basically in line with what you would expect, so our instincts in pinpointing heavily rostered running backs are likely correct.
Now, let's get to the fun part. As with quarterbacks, there was a difference in the hit rate at running back based on a player's salary. It was just flipped here with the high-salaried backs absolutely beasting out.
|Salary||Percentage to Hit Value|
|$9,000 or Higher||69.23%|
|$8,500 to $8,900||72.73%|
|$8,000 to $8,400||71.43%|
|$7,500 to $7,900||58.33%|
|$7,000 to $7,400||20.00%|
|$6,500 to $6,900||50.00%|
|Lower than $6,500||68.42%|
Running backs with salaries of $8,000 or higher hit their baseline value 71.43% of the time compared to a hit rate of 52.83% for the cheaper options. Things were especially bloody in the middle tier.
It's not overly difficult to figure out why this would happen. The mid-tier running backs are likely not bellcows within their offense, which keeps their salaries in check. This makes the risk of a bust higher, especially if the jump in popularity is due to a big performance the previous week. The more expensive running backs don't carry those risks, allowing them to come through more frequently.
The big exception to this is the true value options, who hit 68.42% of the time. This wasn't as high as the top-end options, but it's still a fully respectable number.
There was a pretty simple explanation for why this happened. For a running back to be popular in that salary tier, they usually need some sort of role change to occur. Cheap volume is always a welcome sight, and it was a profitable investment this year.
Overall, there were 19 popular running backs who had salaries below $6,500. Of those, 12 underwent a role change (an injury, suspension, trade, or something else for another piece in the backfield), and 7 were still in their previous roles. Of the 12 backs in new roles, 10 hit their baseline value compared to only 3 of 7 for the backs who didn't get a role change.
Based around this, we can see two different scenarios in which we should be fully willing to dive in on popular running backs. The first is when they are their team's bellcow, projected to get work as both a rusher and a receiver, a role that generally carries a lofty salary. The other is when they're a cheaper option who is in line to receive more work than usual, something their salary will not fully account for. Most other backs are worthy of some solid skepticism even if the position is generally better than others.
The other data point that featured a big split came from bookmaker info; it's just likely not the info you'd expect.
We tend to associate running backs most heavily with spreads because a team can run the ball when they're ahead. That's why we saw the popular backs being favored more often than not, and it may lead you to think that favored running backs would hit more often.
There wasn't much of a split there, though. In fact, underdog running backs hit 64.29% of the time compared to 60.81% of the favored running backs. Instead, the big deviation came from looking at the total.
Game environment was a crucial factor in DFS processes for 2018. Because there were so many high-scoring affairs, it made the disadvantages associated with low-scoring slugfests greater than they had been in years past. In theory, you'd think this would have a greater impact on quarterbacks and receivers, but it was the running backs who got a major kick in the pants when the points were flying.
|Total||Percentage to Hit Value|
|55 or Higher||75.00%|
|50 to 54.5||80.65%|
|45 to 49.5||57.14%|
|Lower than 45||42.86%|
A running back didn't necessarily have to be in a shootout to come through. They just had to not be in a dud.
Combining the data on spreads and over/unders should influence the way we view implied team totals. Plenty of the running backs in games with low totals were on teams that were heavily favored (13 of 28 entered as at least five-point favorites, and six were double-digit favorites). Although those favored backs did hit a higher rate than the general population in lower-scoring games (53.85% among those favored by at least five points), it was still much lower than the backs in higher-scoring games, regardless of the spread.
Those favored backs likely had implied team totals that were on par with or higher than those for backs in higher-scoring games who didn't have the spread as heavily in their team's favor. And yet, those games with higher totals -- regardless of spread -- still produced more trustworthy running backs. This means an implied team total doesn't tell us much without additional context.
Let's say there are two running backs who are projected to be popular in a given week. They're both on teams that have the same implied team total. Based on the data, we should be more skeptical of the one in the game with the lower over/under.
This inherently means that we prefer the back on the team with the spread less heavily in his team's favor. That could change if both games are projected to be high-scoring, but with running backs getting more work in the passing game, totals are the piece of bookmaker info that we need to weigh most heavily.
Above all, though, it's going to come down to a running back's role. If he's a workhorse or one gaining a larger share of his team's touches, then we can trust him even when he's on a bunch of rosters. If he doesn't fall into either of those categories, we'll want to be wary of following the public and investing in these ball-carriers.
Finding optimism at running back was pretty easy given the high hit rate at the position. We're going to have to try a bit harder if we want to justify buying into a popular wide receiver.
Overall, we need to be wary of wide receivers who are going to be on a bunch of rosters. Here's what those wide receivers looked like this year.
The totals for popular receivers were higher than for running backs. If there's an involved receiver in a projected shootout -- especially one coming off a big game -- you can bet that they'll be popular. That's generally not something we should want.
It's possible there is an exception to that rule, and it's likely not one that would sit high on your list of priorities. But wide receivers playing in games with little or no wind were actually decently dependable.
In our sample of 136 chalky receivers, 58 played in games with wind speeds lower than five miles per hour. Their hit rate towered above those in higher winds.
|Wind Speed||Percentage to Hit Value|
|10 mph or Higher||39.13%|
|5 to 9 mph||40.00%|
|Lower than 5 mph||56.90%|
This was true both among wide receivers attempting to hit baseline value and when we were searching for blow-up games.
Of the six receivers who hit at least 4x value, four of them were in wind speeds below five miles per hour. If we expand that to the 33 wide receivers who hit 2.5x value, 17 played in games with wind speeds lower than five miles per hour, and only one had wind speeds exceeding nine miles per hour. Wind speed is a major factor for wide receivers in DFS.
If a receiver who is projected to be chalky is playing in wind speeds higher than 10 miles per hour, they're an easy cross-off. We should be willing to do the same when the winds are above five miles per hour, but 10 is where things get extra shaky.
It's a bit of a different discussion if the wind speeds are lower than five miles per hour. But even there, receivers had a lower hit rate than running backs and tight ends, and they still averaged just 1.94x value. Even the bright spots have their warts at this position.
The hunt for other signs of hope also proves largely unsuccessful. There was a slight skew in favor of receivers in games with totals of 50 or higher (50.72% compared to 44.78% in totals below that). But the second-best marker seemed to be using wide receivers on teams that were favored.
Overall, popular receivers who were favored hit baseline value 54.17% of the time. That was up from 40.63% among underdog receivers. Again, it's not as good as we saw at other positions, but it is at least something.
If we combine all of these together, we can get a bit of an archetype for a wide receiver who actually is worthy of our trust when popular. We need them to be favored, in a game with a lofty total, and playing in low wind speeds. It's a narrow range of circumstances, but with the low hit rate of receivers, that's necessary.
Of our chalky receivers, 37 checked all of these boxes (with the total set at 50 and wind speeds lower than 10 miles per hour). In that group, 62.16% hit the baseline value, and 12 of 17 hit value when the wind speeds were lowered to beneath five miles per hour. Wide receivers can be trustworthy; you just have to be picky with them.
All of this is not to override the point that -- in general -- popular wide receivers are going to break your heart. That's just how the nature of the position works. There are conditions in which that heartbreak is less likely, but those are very much the exceptions rather than the rule. Unless a receiver meets that strict set of criteria, it seems most wise to just let other people ride those death trains to destruction.
Tight ends are likely the hardest position to dissect in this exercise. On the one hand, they tend to perform better than their colleagues, hitting baseline value fairly often. On the other, they rarely generate monster outings. So what should we do when a tight end is bound to be chalky?
First, let's get a glimpse at what these popular tight ends looked like in 2018.
The average value here is just 1.72, which is lower than any other position, including wide receivers. You do expect that given the ills of tight end in general, but it's still not necessarily a glowing review.
When a position is particularly putrid, there's a solid incentive to spend as little there as possible so that you're not wasting precious resources. But with the average salary of a chalky tight end being $6,241, it doesn't seem we did this in 2018.
On one hand, this salary distribution is easy to understand. If you want the few reliable players at the position, you're going to have to fork over some serious dough, and those players all carry salaries higher than that average. There were, though, instances in which we waded into the waters of mid-tier tight ends, and it was firmly not great, Bob.
|Salary||Percentage to Hit Value|
|$7,000 or Higher||64.29%|
|$6,000 to $6,900||38.46%|
|$5,000 to $5,900||73.68%|
|Lower than $5,000||60.00%|
This is very much in line with what we found in looking at perfect lineups. If you didn't pay for a stud, you had better have been punting.
There were 14 popular tight ends who had a salary between $6,000 and $6,900. Only six of those players managed to score more than 6.5 FanDuel points, and half of them failed to top 4.3 points. There was even a donut from Eric Ebron mixed in there. Mid-tier tight ends are not you friend.
Outside of salaries, there weren't many major splits for tight ends that we could exploit. Chalky tight ends in games with a total of 50 or higher hit 62.50% of the time compared to 59.26% for those with totals below 50. Underdog tight ends hit at a slightly higher rate than the favorites, which goes counter to what we saw in looking at perfect lineups. The one minor positive was similar to what we saw with wide receivers in low winds.
|Wind Speed||Percentage to Hit Value|
|10 mph or Higher||53.85%|
|5 to 9 mph||58.33%|
|Lower than 5 mph||61.54%|
As such, instead of looking at these splits, maybe we should look at the average composition of a bust and see how it compares to a tight end that did well while popular.
In our sample of 51 tight ends, 12 of them recorded at least 2.5x value, which is generally what we would love to get at the position. On the other end of the spectrum, there were 14 tight ends who failed to reach even 1x value, which would generally force you to draw dead even if the rest of your lineup was spicy.
Here's the average composition of each of those groups as we lop off the more middling performances.
|Popular TEs||Less Than 1x Value||More Than 2.5x Value|
The biggest difference here is the wind speed, and that number goes counter to what we've found elsewhere. Because of course.
There was a minor split in both the totals and salaries for each side, favoring cheaper tight ends in higher-scoring games. It's not hard to figure out why that would be the case. This should likely make us a bit more skeptical when we spot a potentially popular tight end in either the middle or upper tiers of salary who is in a game that could be a bit short on points.
Perhaps the biggest takeaway at the position comes from looking back to the piece on perfect lineups. There, we saw that a lot of tight ends who flew under the radar had big days. Seven of 20 tight ends in perfect lineups were on less than 1.5% of all rosters in the FanDuel Sunday Million, and only four were on more than 10%.
This means we can get high-upside days while deviating from the pack at tight end. As we saw earlier, there weren't a ton of blow-up performances from our popular options this year, but that doesn't mean they didn't happen.
Because of this, the go-to strategy at tight end seems to be avoiding the options we expect to be popular. Yes, they have a good shot of hitting their baseline value, but they're still not likely to provide a truly lid-lifting performance. It can be difficult at such a thin position to find contrarian choices, but if there's a lower-salaried tight end in a projected high-scoring game who may go overlooked, we've got plenty of incentive to turn their direction.
Defense and Special Teams
As you'll recall from the beginning, we were pretty good at pinpointing solid defenses this year with most defenses outscoring what they had done the previous week. There are still some things we can learn by looking at the data, though.
First, here's the average composition of a chalky defense. In general, they were pretty heavy favorites in projected low-scoring games.
It's pretty much exactly as you'd expect. A favored defense is more likely to get chances at sacks, interceptions, and turnovers, so it makes sense that we'd largely invest when this is the case.
It's possible, though, that we didn't put a heavy enough emphasis on the spread. Here's the breakdown of the hit rate among popular defenses based on the spread entering the game. The larger the spread in the offense's favor, the better things worked out.
|Spread||Percentage to Hit Value|
|Favored by 10 or More||61.54%|
|Favored by 5 to 9.5 Points||64.71%|
|Favored by Fewer Than 5 Points||50.00%|
|Underdogs by Fewer Than 5 Points||50.00%|
|Underdogs by 5 or More Points||0.00%|
The sample on the teams that were underdogs by five or more points was just three teams, but all three flopped. This was even though all three had salaries of $3,400 or lower. Don't use defenses that are heavy underdogs.
The hit rate doesn't really get impressive until teams are favored by five or more points. There, defenses hit their baseline value 63.33% of the time compared to 42.86% of the time for defenses with lesser spreads. This lines up with what we'd expect anecdotally, so if there's a potential popular defense that isn't heavily favored, it's wise to be skeptical at best.
Let's circle back to the salary discussion for a second. As mentioned, the three major underdogs who wound up being chalky were all value options, and all three flopped. At that reduced salary, it's easier to hit value than it is when you're a higher-priced option. That didn't help the hit rate of cheaper defenses, though. Instead, they were the worst range on the board.
|Salary||Percentage to Hit Value|
|$5,000 or Higher||60.00%|
|$4,500 to $4,900||50.00%|
|$4,000 to $4,400||58.33%|
|$3,500 to $3,900||72.73%|
|$3,000 to $3,400||36.36%|
Part of this comes down to spreads. Cheaper teams are less likely to be heavily favored, and as we saw before, that's largely a prerequisite for success at this position. Of the 11 chalky defenses with a salary below $3,500, only five entered the game as favorites, and only one was favored by more than five points.
But even the one team that was heavily favored managed to flop. There are lots of incentives to pay down at defense, especially when you're looking to load up on volume at running back and wide receiver in a cash game. But for tournaments, cheaper defenses are likely cheap for a reason, and it makes them mighty risky investments.
When we turn our attention to the totals, you'll see that the difference in hit rate based on the total wasn't very big.
|Total||Percentage to Hit Value|
|47 or Higher||50.00%|
|44 to 46.5||57.14%|
|41 to 43.5||57.14%|
|Lower than 41||53.33%|
A quick look at this data would tell you that we'd want to avoid popular defenses playing in games with lofty totals. But a deeper look shows that likely shouldn't be the case.
The sample on heavily-rostered defenses in games with a total of 47 points or higher was just eight games. Conversely, of 17 defenses in perfect lineups, 4 of them had totals of 51 or higher. There was only one chalky defense in that range, and it paid off at 2.2x value.
This means that -- although games with a higher total technically led to a lower hit rate -- we're likely overvaluing total, especially in comparison to something like the spread. A lot of defenses put up big fantasy totals in games with heavy totals, and the public isn't generally investing in those games. As such, we should be willing to dabble in those waters this upcoming year in order to snag some contrarian, high-upside plays.
That's likely the only tweak we need to make at this position as we get set for 2019. Our thoughts on spreads were largely correct (though we should skew even more toward heavy favorites), and our trust in higher-salaried defenses tended to pay dividends. As long as we're not excluding defenses because they're tied to a game with a high total, we should be set to succeed here going forward.