Analyzing the Top 10 Lineups From 2018 DraftKings NFL Millionaire Makers
With the 2019 NFL season about to start, I figured I would attempt to give you one of the most comprehensive reviews possible of top lineups from last season’s Millionaire Makers on DraftKings.
Last year I had my weekly review articles of the Top 10 lineups that tracked what was going on in season which many of you responded positively to, so I figured I would run it all back for you with some new data mixed in so that we can all have a better understanding of what these lineups look like and how we can attempt to re-create them ourselves either by hand or in LineupHQ. Many of the topics discussed here can be applied to all of the 100,000+ entry fields you will find on DraftKings this season.
One of the keys to making large field GPP NFL lineups is to start your lineup with a stack based around your quarterback, which generally involves putting skill position players from his team/game into the same lineup with him. Of the 170 lineups that made it into the Top 10 last season, 152 or nearly 90% of them contained some form of a stack based around the QB. This is a basic correlation for most players to start off their lineups nowadays, but it still remains one of the most important aspects of making a lineup that has a chance of success when playing in 200,000+ entry fields.
The next decision is then how many players to stack from the same team/game if we want to attempt to replicate what the top lineups did in 2018. So, let’s take a look at that data and have a discussion.
Most of you will know the difference between a team or game stack, but in case you don’t, a team stack is using only players from the quarterback’s team, while a game stack will include at least one player from the team opposite of your quarterback in the same game. If you need further clarification on what a “stack” is, a team stack of two is the QB + one skill position player from his team. A game stack of three is a QB + one skill position player from his team + a skill position player from the opposite team in the same game and so on. Of the 152 stacks last year we can see that 140 of them came from four specific stack types. To give you an idea of what it takes to hit the outliers of a game stack of 5, it requires a 48-40 Week 1 game between the Saints and the Buccaneers when Mark Ingram was out and Ryan Fitzpatrick was a low-owned monster, putting up 45+ DK points. I’m generally not going to aim for that in my lineups this year outside of certain games and instead will focus on the group of lineups that 140 of the 170 top 10 lineups came from. Stacking a QB with one or two play-makers from his team or making a game stack with two or three skill position players from the same game accounted for 82% of all top 10 lineups last season and looks to be one of the stronger correlations you will find as we enter 2019. I want to note that when the 5 or 6 man game stacks hit, they hit hard with $1,000,000 lineup potential if the game scores 35-40+ on both sides.
Now that we talked about how the top lineups started, we have to start rounding out the rest of the team. One of the most discussed aspects of NFL Large Field GPP construction is what position should we use in the Flex spot. Here is how the Top 10 lineups from 2018 allocated their flex spot.
— 64.7% of Top 10 Lineups used a RB in Flex
— 27.7% of Top 10 Lineups used a WR in Flex
— 7.6% of Top 10 Lineups used a TE in Flex
One of the undeniable keys to success in daily fantasy football last season was using a RB in your flex spot. Not just any RB either, as many of the lineups I looked through contained multiple highly owned workhorse RBs that we expected to have good games. They provided a high floor/ceiling combo with implied large workloads in both the run and pass game and generally performed well throughout the year. Let’s take a look at the Week 3 Millionaire Maker team from ResultsDB and I’ll show you what I mean.
We already talked about the game stack applied here up above, but when mixed with some top RB talent with all three of Kamara/Saquan/Zeke, it’s no wonder this lineup hit for $1,000,000 (Is it really this easy?). I won’t show you every team like this, but trust me there were a lot of them in the top 10 lineups last year and likely something I will try to incorporate into my lineups when possible this season. I’ll also note that I still think using a WR in the flex is perfectly acceptable if used the right way, which I will talk about later on in the article. I really don’t see myself making many lineups with a TE in the flex this year if any at all.
The Ownership Game
When you compete in a field of 20 people, ownership isn’t something that is near the top of the list of things to account for. When you play in a field of 200,000+ people, ownership is something you really should be factoring into your lineups. That 5% owned player you had to yourself in the 20 man field is now in 10,000 other lineups in the 200,000 person contest. Of a possible 1,530 roster spots across all top 10 lineups in 2018, 383 or 25% of them contained a player that was 5% owned or less (this includes D/ST). That breaks down to 2.39 5% owned or less players per top 10 lineup in 2018. Based off this Twitter poll, it seems that the public is underestimating the importance of low ownership.
Some lineups have four or five low-owned plays; others like the Week 3 winner up above have none, so while having low-owned plays isn’t a must, I believe it’s an important factor in helping you jump up the standings if your low-owned play has a nice game. Let’s take a look at where these low-owned plays came from in 2018.
After explaining why and how the RBs dominated the flex spot, it should be no surprise that low owned RBs generally are not the way to go, as just 50 5% owned or less RBs appeared in top 10 lineups. The good majority of these low-owned RBs were also players I would consider to be good like Tarik Cohen or Marlon Mack that just happened to go under the radar for the week. Let’s take a look at the Week 15 winner as an example from ResultsDB and start tying some concepts together.
Here we have an ATL 2-man team stack of Matt Ryan + Julio Jones. I did not count the defense here in the stack as this really was a one-off situation since the Falcons hosted one of the worst offensive teams of all time in the Cardinals that week. This makes sense as a roster construction as we knew by Week 15 that the Cardinals were historically bad, so the addition of the D/ST makes sense to me. Mbonson then added in 2 highly owned workhorse RBs and then went with a low-owned Marlon Mack at home against the Cowboys whom Mack proceeded to run wild against for a huge day. We knew Mack was good at this point in the season, and while no one expected a 29-0 Colts win, this is a perfect illustration of how to utilize a low-owned good RB talent if you were to attempt it. You combine one of them with two others you expect to have huge days. One of the other trends to note is that everyone in this lineup is what we would consider a “good” player. There aren’t that many head-scratching plays overall that end up winning.
Wide receivers are the most volatile position in NFL DFS as they generally rely on targets and game script to provide favorable outcomes. There are a variety of ways for WRs to have a sub-optimal day, which is shown by them having the highest “bust rate” of any position last year. (We will talk bust rates later). With us having to roster three or four of these volatile WRs on every lineup, it should come as no surprise that low-owned WRs are the highest low-owned position by a large margin. If nobody used WRs in the flex, 32.5% of WR roster spots would have been taken up by a 5% owned or less WR. If everyone used a WR in the flex, almost 25% of all WR roster spots would have been taken up by a 5% owned or less WR. The real answer lies somewhere in the middle, so let’s call it 28.5% of all WR spots had a 5% owned or less WR in top 10 lineups in 2018. Let’s take a look at a few lineups from ResultsDB and see how it’s done.
Here is the Week 5 winning lineup. We have one of the more powerful ownership combos possible of a sub 5% owned QB paired with his sub 5% owned WR powering this team stack by Slaystations. First off what on earth are we doing allowing Aaron Rodgers and Davante Adams to go this low owned? Odell Beckham is just 3%! WHAT IS HAPPENING AND WHY ARE WE SO BAD AT THIS? Sometimes when we look back at these teams that win, it’s obvious why they win. They play low-owned good players when the rest of us might be scared by the dreaded WR/CB matchup chart or the DVOA might not look good after 4 weeks of play, or the price is $200 too high for the algorithms to put them into lineups. Here’s the thing…Aaron Rodgers is good at football, Davante Adams is good at football, Odell Beckham is good at football. Maybe we should play guys that are good at football even if they have a point per dollar projection less than the guy that is 25% owned. Great lineup here from Slaystations with some possibly even more important things going on that we will talk about later.
Here is the Week 2 winning lineup. Let’s see how bad we as a whole are at DFS large field GPPs yet again. JEREMYHEIN puts together a great lineup here and hits one of the outlier 5-man game stacks. Notice which games these huge 5-man game stacks come from. Week 1 it was TB/NO, and here in Week 2, it’s KC/PIT. Don’t go 5-man game stacking SEA vs JAX. Back to the lineup: To understand how Sammy Watkins was just 2.46% owned Week 2 we have to look back to Week 1 where the Chiefs beat the Chargers 38-28 while Tyreek Hill had 169 yards and 2 TDs and Watkins had just 3 receptions for 21 yards. WHAT HAPPENS WEEK ONE IS ALWAYS WHAT HAPPENS WEEK 2. Like I said, as a whole we are all very bad at this. Hill has a good game with 5/90 and a TD, but was 19% owned compared to Watkins at 2.5%, and Watkins beats him out by 2.1 FPTS. Add in Diggs at 3% ownership after a mediocre Week 1 and some other low-owned plays and you have a great lineup that won $1,000,000. Hopefully you are starting to catch onto some themes on how to use low-owned WRs both in stacks and on their own.
I probably should have counted low-owned QBs as 3 or 4% instead of 5%, as ownership gets so spread out among them that they really do deserve their own tier for labeling what really is low-owned. Nevertheless, we can still draw some good conclusions, as 67 (or 39.4%) of all top 10 lineups had a QB that was 5% owned or less. There is plenty of variety here among the low-owned QBs, as we have a few naked (No stack involved) Lamar Jackson lineups, some naked Cam Newton lineups, some Nick Foles going off for 40+ FPTS naked lineups along with plenty of stack lineups, including one where none other than Brock Osweiler won someone $1,000,000. Yes, you read that correctly: Brock Osweiler was in a million dollar lineup in 2018. I mentioned above with the Aaron Rodgers lineup that stacking a low-owned QB with his low-owned WR is one of the more powerful combinations you can have, so let’s take a look at another one like that.
Here is the 8th place lineup for Week 10. I can’t just give you winners all the time!
ScottN beat a lot of us that day with what I would consider to be an elite lineup construction all around. He paired low-owned Jared Goff with low-owned Brandin Cooks as a two man team stack while adding in two additional correlations not attached to his QB stack (this is the important thing I have been hinting at that we will discuss in depth later) of Aaron Jones + GB D/ST along with the Workhorse RB/Opposing pass catcher game stack of Leonard Fournette + Eric Ebron. ScottN might not know this, but this is one of the best lineups I encountered while looking through all 170 top 10 lineups when factoring in what I feel a great large field GPP lineup should look like in concept. For maximum upside, if you use a low-owned QB, you should be attempting to pair him with his low-owned good receiving option(s).
This is simple: When no one is playing Kelce/Ertz/Kittle/Howard/Engram…play them. There are some random TEs mixed in among the 42 5% or less owned TEs, but they are nearly impossible to hit on or score 0-6 FPTS (Rhett Ellison scoring 5.7 FPTS in Week 5 at 1.7% owned wasn’t the reason you had a top 10 lineup). Playing George Kittle at 5.3% ownership when he gets you 37 FPTS in Week 14 which isn’t even included in the low-owned TE data is what gets you into the top 10. As a whole, we like to think we can pick out which $4,000 or less TE is the must-have, can’t-miss play of the week guaranteed to get us 15+ FPTS. In reality, we are all horrible at predicting that, which allows the high priced stud TEs to post big games at low ownership.
I went into ResultsDB and randomly picked a week in the NFL and I really couldn’t have landed on a better example of what TEs looked like last year.
This shows the 19 highest owned TEs on this particular week. As you can see, the reason we are all horrible at picking a TE that scores well is due to the fact that hardly any of them gives us scores that can win a GPP in a given week. This particular week you needed to have either Eric Ebron or Austin Hooper to set yourself apart from the field. Two out of the top 19 owned TEs were difference-makers, and both of them are names that we could have landed on with one of them being a low-owned gem in Ebron. If you think you can predict who the cheap TE that goes off is, I have some bad news for you.
Defense is another spot where I am willing to mix it up. 50 of 170 lineups (34%) had a D/ST that was 5% owned or less. 5% owned or less D/STs ended up in the winning lineup 5 of 17 weeks, which is the same rate as 14%+ owned D/ST. When you factor in a 50% bust rate of the Top 3 highest owned D/ST each week over the course of the season, I can make a reasonable case that we should be underweight or fading the highest owned D/ST nearly every week in a large field GPP like the Millionaire Maker.
If you ever see anything like the ownership of the Bears on the road against the Dolphins with a backup QB starting on a slate with 24 teams playing like in Week 6 last year, you should be running away from that ownership as fast as possible. I don’t care what is going on, that type of ownership is a clear fade in GPPs. Like I’ve said multiple times, we are all generally bad at DFS in these 200,000+ entry field tournaments.
Now go back and read the ownership parts again. Look at the photographs (Go Nickelback!), and try to understand the topics. This is one of the more important processes to understand how and why top 10 lineups end up as top 10 lineups.
I’ve talked about some bust rates already, but let’s spend a little more time on the topic. The bust rates are subjective on my part every week. Did the player have a reasonable chance at landing in a good/great lineup based on his performance? There is no set fantasy point or target score for these, but rather my own subjective thoughts on if a player was a bust or not. Here are my bust rates by position for 2018 for the three highest owned players at each week.
QB Bust Rate
Quarterbacks are tied with RBs as having the lowest bust rates, but for a variety of reasons, I would generally favor a lower-owned QB over a lower-owned RB. One of the main reasons is that when the high owned QB busts, his generally high-owned targets are likely to bust alongside him. This is not always the case but holds true a large percentage of the time. Another reason is that when a high-owned QB does have a good game, his highest-owned WR can also have a bad game. Let’s take a look at Week 8 ownership to go over this.
Here are some thoughts:
— Andrew Luck has a good game, but his top option and highest-owned WR on the slate performs badly.
— Jared Goff has a good game, but his highest-owned WR and the second highest-owned WR on the slate busts.
— Aaron Rodgers has a bad game but his top option has a good game.
— Winston stinks and none of his targets are in the Top 10 in ownership.
So by fading the two highest owned QBs this week who had good games, we are still knocking out a good portion of the field that used them with stacks of their top targets. Goff actually landed in the winning lineup this week with Gurley/Reynolds, but he still was the 4th highest scoring QB on the week. I don’t think I would fade the highest-owned QB of the week, but ideally, I intend to be underweight on them as a whole throughout my large field GPP lineups, as that also leads me to being underweight on the high owned WRs we will talk about soon.
RB Bust Rate
Running backs are tied with the same percentage of bust rates as QBs, but when you consider we have to roster two or three of them every week, the high owned RBs were generally one of the best players to use last year. There is week after week after week of Gurley/Kamara/CMC/Zeke/Hunt pre-injury/Saquan appearing in Top 10 lineups as these players had high implied workloads in both the run and pass game, which allowed them to hit peak production week in and week out. Most of the bust rates come from when we try to get cute with Dion Lewis or Spencer Ware chalk, and not from when we roster the stud high priced GOOD RBs. Using the bad players that became chalk for one reason or another was the wrong move last year, while using the elite RB talent even when highly owned was the correct play. If you see a Corey Clement type as the highest owned RB appearing in 31% of lineups in Week 3 last season, I would generally try to be on the opposite side of that this year.
WR Bust Rate
The top 3 highest-owned wide receivers busted a nice 69% of the time last year, with the highest-owned WR only appearing on the winning lineup twice all season. One of the stronger trends from last season was fading or being underweight on the highest-owned players at the position.
You can go to just about any week in ResultsDB and find WR performances that look like this from Week 11. One of the top three WRs has a good game, a few others below him have good games, some guys get a zero or next to nothing, and a few have GPP winning performances. It’s a total crapshoot as the NFL is spreading out receiver production at a higher rate than ever. I am intending to be underweight on the highest-owned WRs nearly every week in 2019.
TE Bust Rate
Tight ends busted nearly 50% of the time last season, and of all the positions, when they bust, they can REALLY bust. George Kittle was 32% owned in Week 2 and scored 4.2 FPTS, David Njoku was 10% owned in Week 8 and we took a zero, while 10% of us also took a zero in Week 13 with Matt LaCosse. In Week 15 we spent 58% of the ownership on the top 3 owned TEs and none gave us more than 5 FPTS. If we are going to willingly roster players that gets us 0-5 FPTS at high ownership, we might as well try to roster some lower-owned TEs and jump large portions of the field if they hit. I want to stress again the TEs you should be targeting at low ownership should be the Kelce/Ertz/Howard/Engram/Kittle/Ebron/Hoopers of the world, as when these guys go off at low ownership, you can have a massive edge over the field.
D/ST Bust Rate
With the top 3 owned D/ST busting just over 50% of the time and likely not allowing us to have a top score, I stand by my case made earlier that you should generally be underweight on the top D/STs in your large field GPP lineups. It’s hard to get an enormous edge at D/ST, as that usually requires a near shutout or a few turnovers and a defensive score, but if you can avoid the 20% owned D/STs that score 6 points and instead use the 3-5% owned ones that get 10 points, you really are jumping a large portion of the field, and if you get to the top, every point matters, as some of the top scores are separated by less than a point.
Congratulations on making it this far!
So now that we have covered some of the basics along with more advanced topics, it’s time to reveal one of my new data tracking points I added in the offseason. I haven’t really heard much talk on this subject over the years, and after combing through the top 10 lineups from last season, I found the results so strong that we need to start a conversation about it. So let’s start talking about secondary correlations.
We all know that using your QB in a team or game stack creates correlation within your lineup. Correlation helps you move up the standings quickly if you are correct on your assumptions of a certain game being high scoring. If you think Drew Brees is going to throw for 350 yards and 3 TDs in a high scoring game, it makes sense to use one or two of his pass catchers and one or two players from the other side of that game. By getting just one game script correct, you now have 3-5 of your nine roster spots all theoretically doing well and now only have to get a few other things to fall your way to be on the path towards a great lineup.
Secondary Correlations are adding similar strategies from other games into that same lineup that has a team/game stack centered around your QB. Think of it like adding a 3-man stack to your 5-man stack in baseball. Let’s take a look at a few examples below.
Here is a lineup with a naked Lamar Jackson at QB with no skill position players around him. Lineups like this will be viable this season with a few QBs, but ONLY if you pay attention. With no skill position players around his running QB, Pajamadaddy needed to “correlate” his lineup somehow. First he added in the Ravens D/ST in an assumption that the Ravens could control this game and his running QB might not be needed to throw as much and get a few extra rushes in at some point. Lamar Jackson doesn’t even have an amazing day and the strategy pays off. Not only does he correlate that way, but he also adds in what we are going to call the RB/ Opposing pass catcher combination with McCaffery and David Moore from the CAR/SEA game. But wait…there’s more! Seeking even more upside, he then adds in the WR/Opposing WR combination from the PIT/DEN game with Juju and Sanders. By getting three game scripts correct, there are only a few more things that needed to fall his way to have a great lineup, and when it all came together with strong correlations, he won the Millionaire Maker by 6 points.
Let’s look at another lineup by Markgenorex from Week 5 that finished 8th, someone that I would consider to be a good DFS player. I included two views of it as DK was not showing the ownership for me.
Mark starts off with a standard three-man game stack of NYJ/DEN with Darnold/Anderson/Sutton. Sutton bombs out, but the 30 FPTS from the 0.5% owned Robby Anderson rockets his lineup up the standings. A simple three-man game stack is not enough for Mark, as he then adds in the RB/Opposing pass catcher stack of Gurley/Lockett from the LAR/SEA game as well as adding in the WR/ Opposing TE stack of Thielen/Ertz from the MIN/PHI game. By getting just three game outcomes correct, he has 7 of his 9 roster spots correlated and now just needs a few more balls to bounce his way to cash in. Hopefully you are paying attention, as using secondary and tertiary stacks to surround your main stack based around your QB is something that was ALL OVER top 10 lineups last season.
Let’s look at one more lineup from another good DFS player in giantsquid, who had the winning lineup Week 17 and is ranked in the Top 10 overall here on the RotoGrinders rankings.
He starts off with a 4-man and reasonably low-owned ATL/TB game stack of Ryan/Julio/Sanu/Godwin. Nothing about that stack screams chalk and presented itself with a ton of upside. He then adds the secondary correlation of RB/Opposing pass catcher stack of C.J. Anderson and Kittle from the LAR/SF game. He uses a lowish owned RB with two stud RBs expected to get a large workload, and rounds it out with a low-owned D/ST. Is it any wonder that giantsquid won $1,000,000 with this and is one of the better GPP players out there? It incorporates nearly everything I have talked about so far into one lineup. A great lineup from one of the best players to close out the season.
The Numbers Behind Secondary Correlations
Now that we understand what a secondary correlation is for NFL DFS and have looked at some examples, let’s take a look at how many secondary correlations appeared in the top 10 lineups. Remember there are 17 weeks of Top 10 lineups, which equals 170 total lineups.
I bet you didn’t think it was that many! If we combine the RB/Opposing WR with the RB/Opposing TE we have 58 occurrences of a RB/Opposing Pass Catcher being added as a secondary stack to Top 10 lineups last year. That’s 34% of all top 10 lineups.
Outside of a few occurrences, most of these RBs involved in secondary stacks were good players like Zeke/CMC/Gurley/Connor or players like C.J Anderson who was expected to handle a major workload for a very good offense. These are not LeSean McCoy and an opposing Jaguars pass catcher added as a secondary stack. It’s good RBs that we expected to have big games that are from good offenses that dominate this trend. If we think the continued DFS dominance of the Bellcow RB will continue into 2019, I would expect many of my large field GPP lineups this year to include this trend of adding a secondary correlation of RB/Opposing pass catcher.
Some other secondary stacks that worked well last season include:
— RB/Pass Catcher from Same Team
— WR/Opposing Pass Catcher
How to Use Secondary Correlations
If you are 5-man+ game stacking the Rams at Carolina Week 1 and hoping for that game to be 45-40 in a specific lineup, the need for secondary correlations is much less than if you are doing a 2-man Goff/Cooks stack. This is because the 5-man game stack is already highly correlated over 5 of 9 roster spots that you would generally be better off filling the other four roster spots with “good” players. You could add one additional correlation into a lineup like this if you wanted, but it’s fine if you can’t make it work.
If you start a lineup with that Goff/Cooks combo, or even add in a 3-man game stack with Goff/Cooks/CMC, these are the lineups where you should really be trying to add some secondary correlations into the mix. With the 3-man game stack you still have six other roster spots you need to get right, which is a very tough task to pull off on its own. Adding in one or two secondary correlations to the smaller stacking groups can increase your chances of having a good lineup if your assumptions on how 2-3 games play out are correct.
Also note from the chart that the large majority of secondary correlations in top 10 lineups are two positions. The RB/Def stack was added to 18 top 10 lineups, while the WR/Def stack that is not shown here was added to 13 lineups. The RB/WR/Def stack was added to just two lineups. Keeping your secondary correlations to just two positions per game was what worked consistently in 2018.
A Final Summary
It’s very hard and nearly impossible to win these extremely large field NFL GPPs. I’m unlikely to win, you are unlikely to win, everyone is unlikely to win. You need nearly everything in your lineup to work out as expected and even then your odds of winning are slim. What you can do is incorporate some of the tactics discussed here from the top 10 lineups last year into your own teams this year to give yourself a fighting chance. Many of the same ideas discussed for the Millionaire Maker will also work for other large-field contests like The Slant and The Play-Action on DraftKings as well.
Two and three-man team stacks along with three and four-man game stacks should be priority builds most weeks for consistency in making solid lineups. In addition to those, you can use four-man team or five-man game stacks of the highest projected scoring games of the week, as these games are typically the ones that have the ability to produce 42-40 type scoring environments that allow those lineups to work. Only 10 of 256 games last season had both teams scoring 35+ points, which is what is generally needed for the mega game stacks to be viable.
Flex Spot Usage
If we think the trend of the elite/good talent RBs continuing to have success in 2019 is going to happen, I would suggest prioritizing these type of RBs as your flex position players. It’s still fine to use WRs in the flex, and if doing so, I would use the elite/good talent at the position that happens to be coming in low-owned for one reason or another. I don’t see many reasons to attempt using a TE in the flex.
You should generally incorporate some form of low ownership into your lineups in these NFL mega field contests. A lineup full of chalk players will hardly ever come out on top due to the sheer size of the contest. Here are some ways that low-owned players worked last year.
— Pairing a low-owned QB with his low-owned WR
— Using a low-owned stud WR
— Pairing a low-owned Elite/Good RB with two other top talent RBs that are highly owned
— Using a low-owned stud TE
— Staying away from the mega chalky D/ST
— Being underweight or fading the highly owned WRs
— Using a highly-owned QB’s lower-owned targets instead of the highest-owned option
I will be trying to add at least one secondary correlation onto every team I make this season. The elite/good talent RB paired with an opposing pass catcher from the same game was what worked very well last year. Mixing in two separate secondary correlations if you use two- or three-man stacks also seemed to work very well in top 10 lineups last season.
Well, that about does it for the 2018 Millionaire Maker Review. I spent a lot of time combing through all the top 10 lineups by hand to really dig into them and understand what was actually occurring on them. I do want to note that since this was a fairly manual process on my end and my Excel skills aren’t amazing, there may be a number or a percentage that is off by a small amount. By small amount, I mean that if I said something happened 60% of the time, it might have happened 59.2% of the time. I stand by the results and trends and wouldn’t put my name on this if I didn’t think everything stated was meaningful. I just wanted to point this out in case anyone decided to look into this on their own and the numbers weren’t exact matches.
Hopefully we can apply some of the 2018 trends to our 2019 lineups, and if we notice anything changing in the NFL DFS landscape early in 2019, we can adjust and attempt to take advantage of any new meaningful lineup trends that start to form.
I’ll close this out with what I view as some other elite builds for a 200,000+ field from last years top 10.
Good luck everyone!