Week 1 Player Pool Radar — Building the Watch List Through the SmashTracker Lens

Before we start building DraftKings lineups, there's a more important question to answer:

Who deserves to be in the player-pool conversation in the first place?

That's what the Player Pool Radar is designed to figure out.

We're not trying to solve the entire Week 1 Main Slate today. We're not handing out locks. And we're definitely not jumping straight to lineup construction before the week has fully developed.

We're starting earlier.

First, we'll identify selected games worth investigating.

Then we'll find interesting players inside those games.

And finally, we'll use smash history to determine whether those players have actually shown the ability to produce the tournament-level score their Week 1 salary demands.

Think of this as the beginning of the investigation.

By Friday's Strategy Session, we'll have more information. Projections will have moved. Ownership will be taking shape. Injuries may have changed roles. New value may have appeared.

That's when we'll cover every game on the Main Slate and start turning these early signals into the actual Week 1 Core Player Pool.

And for Week 1, you can follow the entire process for free.

The SmashTracker position boards, the Friday Strategy Session, and all of the premium Week 1 articles are open to everyone this week at thesmashtracker.com.

But before we start digging into games, you need to understand exactly what we're looking for.

What Does Smash History Actually Tell Us?

Every player on SmashTracker has his current DraftKings salary.

That salary determines the score we're asking him to produce.

If a player costs $6,000:

• 2.5x is 15 DraftKings points.
• 3x is 18.
• 4x is 24.
• 5x is 30.

SmashTracker then looks backward at that player's actual DraftKings performances and asks one simple question:

How often has this player produced the score we're asking him to produce at today's salary?

That's smash history.

One important note for Week 1:

The historical sample we're using is limited to the 2025 season.

That's intentional.

More history isn't always better history. At some point, you're measuring a player who no longer exists in the same role, offense or environment.

NFL depth charts change. Coaches change. Teammates change. Usage changes. Players themselves change.

Going further back might give us a bigger sample, but it doesn't necessarily give us a more relevant one.

So for Week 1, we're keeping the historical window recent and asking how these players performed during 2025 when measured against their current Week 1 salary requirements.

For our Player Pool Radar, the number I'm most interested in is 4x.

I'm using 4x as our tournament-level benchmark, a way to identify players who have historically demonstrated the type of scoring performance that deserves further investigation.

You've probably heard DFS analysts say something like:

"This player needs to be able to hit 4x."

Or:

"You have to envision how he gets to 4x."

Okay.

But what does that actually mean?

I can envision almost anything.

I want some evidence.

Has he done it?
How often?
And is his hit rate actually strong compared with other players at his position?

That's why we're also using positional medians.

Among players with at least eight games in the current 2025 SmashTracker sample, the 4x medians are:

Those numbers give us context.

A 20% hit rate doesn't mean much by itself. But if the positional median is 10%, now we've learned something.

And one thing needs to remain clear throughout this article:

Smash history is not a prediction.

It isn't telling us what will happen Sunday.

It's evidence.

It's one more piece of information we can use to decide whether a player deserves to survive the research process and eventually make the tournament player pool.

With that established, let's start where I believe DFS research should begin:

With the games.

Baltimore at Indianapolis

Baltimore–Indianapolis immediately caught my attention because Indianapolis gives us multiple strong 4x signals while Baltimore gives us a very different quarterback story.

Let's start with Daniel Jones.

Daniel Jones (IND)

Jones costs $5,400.

That gives him a 4x target of 21.6 DraftKings points.

He's reached that score six times in 13 games.

That's a 46% 4x hit rate.

Remember, the quarterback median is only 21%.

So Jones is sitting at more than twice the positional median.

That doesn't make Daniel Jones an automatic Week 1 play.

But it absolutely earns him a spot on the radar.

At this salary, history tells us that the tournament-level score we're asking him to produce has shown up with some regularity.

That's worth investigating.

Jonathan Taylor (IND)

Then we get Jonathan Taylor.

Taylor costs $7,300 and currently projects for 19.55 DraftKings points.

His 4x target is 29.2 points.

He's reached that score six times in 17 games.

That's a 35% 4x rate.

The running back median?

Just 6%.

That is an enormous gap.

Now Indianapolis has given us two players with unusually strong salary-adjusted tournament histories.

Different positions.

Different salary levels.

Same result:

Keep digging.

Lamar Jackson (BAL)

Now look at the quarterback on the other side.

Lamar Jackson costs $6,800, putting his 4x target at 27.2 points.

He's reached that score once in 13 games.

That's an 8% 4x rate.

The quarterback median is 21%.

Does that mean Lamar Jackson doesn't have tournament-winning upside?

Of course not.

We're asking a much narrower question.

How often has Lamar historically reached the score required by this particular Week 1 price?

So far, the answer looks dramatically different from Daniel Jones.

And that's exactly why salary matters so much.

Baltimore–Indianapolis has officially earned a place near the top of the Week 1 research list.

Arizona at Los Angeles Chargers

Arizona–Los Angeles gives us something different:

A quarterback with projection and history working together, a fascinating receiver comparison, and an underdog quarterback whose smash history is impossible to ignore.

Justin Herbert (LAC)

Justin Herbert costs $6,100.

His current projection has climbed to 20.88 DraftKings points.

His 4x target is 24.4 points, and he's reached that five times in 17 games.

That's a 29% 4x hit rate, comfortably above the 21% quarterback median.

So Herbert gives us two signals pointing in the same direction:

Strong current projection.

Above-median 4x history.

That's exactly what we're looking for at this stage.

It doesn't put Herbert into the final pool.

It tells us he deserves another round of investigation.

Quentin Johnston (LAC) vs. Ladd McConkey (LAC)

Now things get more interesting.

Quentin Johnston costs $4,700 and currently projects for 11.3 points.

His 4x target is 18.8.

He's reached it three times in 13 games.

That's a 23% 4x hit rate compared with a receiver median of only 10%.

More than double.

Now compare that with Ladd McConkey.

McConkey costs $5,900 and carries the stronger projection at 15.63 points.

But the higher salary pushes his 4x target to 23.6 points.

He's reached it twice in 17 games.

That's a 12% 4x rate.

Still slightly above the wide receiver median, but nowhere near Johnston's historical rate.

And now we have exactly the kind of DFS decision SmashTracker is supposed to uncover.

McConkey has the better projection.

Johnston has the stronger salary-adjusted 4x history.

So which one do we want?

We don't know yet.

And that's the point.

This isn't the stage where we force an answer.

It's the stage where we identify the question.

Jacoby Brissett (ARI)

Then we have Jacoby Brissett on the Arizona side.

Brissett costs $5,100 and currently projects for 15.18 points.

His 4x target is only 20.4.

He's reached that score eight times in 13 games.

That's a staggering 62% 4x rate.

The quarterback median is 21%.

We're talking about nearly three times the positional median.

Now there's an obvious complication.

Arizona is a sizable underdog.

But I'm not ready to immediately label that a negative for a tournament quarterback.

If Arizona falls behind, Brissett may be forced to throw more simply to keep the offense moving.

Extra passing volume creates extra opportunities.

That doesn't remove the risk.

But combined with the historical 4x signal, it gives us plenty of reason to keep Brissett on the radar.

Tampa Bay at Cincinnati

This is one of those Week 1 games DFS players are probably going to find quickly.

The environment is attractive.

But being in a good game doesn't automatically mean every player carries the same salary-adjusted tournament upside.

That's where SmashTracker can help us separate things.

Ja'Marr Chase (CIN)

Ja'Marr Chase costs $7,800.

He's projected for 22.8 DraftKings points, the highest wide receiver projection on the board.

His 4x target is a demanding 31.2 points.

He's reached that score three times in 16 games.

That's a 19% 4x hit rate.

The receiver median is 10%.

So even at one of the highest salaries on the slate, Chase has produced his current tournament-level requirement at nearly twice the positional median.

That's important.

The projection likes him.

The game environment likes him.

And his historical production tells us that the ceiling we're paying for has actually existed.

That's a very clean early signal.

Joe Burrow (CIN)

But his quarterback gives us a more complicated story.

Joe Burrow currently carries the highest quarterback projection on the board at 21.91 points.

He's $6,900.

That puts his 4x target at 27.6 points.

He's reached it once in eight games.

That's only a 13% 4x hit rate, below the 21% quarterback median.

And this is where the process gets interesting.

Projection?

Strong.

Game environment?

Strong.

Receiver stack?

Obviously appealing.

Historical 4x signal?

Not nearly as impressive.

That doesn't make Burrow a bad play.

It tells us the evidence is conflicted.

And conflicted evidence is exactly what we need to revisit later in the week when ownership and the rest of the slate context arrive.

New Orleans at Detroit

Now we get to one of the most interesting environments on the board.

Not because of one player.

Because multiple players on both sides of this game are showing us something worth investigating.

Jahmyr Gibbs (DET)

Jahmyr Gibbs costs $8,000.

His projection has climbed to 24.78 points, the highest running back projection on the board.

His 4x target is 32 points.

He's reached that four times in 17 games.

That's a 24% 4x hit rate compared with a running back median of only 6%.

That's four times the positional median.

So we've got an expensive running back with both an elite projection and a very strong historical ceiling signal.

That's hard to ignore.

Amon-Ra St. Brown (DET)

Amon-Ra St. Brown costs $7,500 and projects for 19.34 points.

His 4x target is 30.

He's reached that score three times in 16 games.

That's a 19% 4x rate, nearly double the 10% receiver median.

Once again, Detroit gives us a premium player whose history still holds up even after accounting for the demanding salary.

Chris Olave (NO)

Now let's cross to New Orleans.

Chris Olave's projection has climbed to 16.7 points.

He's $6,700.

His 4x target is 26.8 points.

He's reached it three times in 16 games.

That's another 19% 4x rate.

The receiver median is 10%.

So Olave's projection is moving in the right direction and his historical ceiling already sits comfortably above the positional baseline.

That makes the New Orleans side much harder to ignore.

Juwan Johnson (NO)

Then we get a completely different salary point with Juwan Johnson.

Johnson costs just $3,700.

His current projection is 10.43 points.

His 4x target?

Only 14.8.

He's reached that score four times in 17 games, producing a 23.5% 4x hit rate.

The tight end median is approximately 11.5%.

So Johnson is sitting at more than twice the positional median.

Now we've got strong signals on both sides of this game and at multiple salary levels.

That's exactly the kind of environment that needs to stay near the top of our Week 1 radar.

Buffalo at Houston

Buffalo–Houston gives us one of the cleanest examples of why salary-adjusted analysis matters.

And the comparison happens inside the same Houston offense.

Nico Collins (HOU)

Nico Collins costs $7,000 and projects for 17.5 points.

His opportunity and route grades are strong.

There are plenty of football reasons to like him.

But his $7,000 salary requires 28 points for 4x.

Across 16 games in the SmashTracker sample, Collins hasn't reached that score.

That's a 0% 4x hit rate.

The receiver median is 10%.

Again:

That does not mean Nico Collins can't score 28 DraftKings points this week.

It doesn't mean he's a fade.

It means that at this salary, we don't have historical evidence of him clearing the specific tournament-level bar we're asking him to clear.

That matters.

Dalton Schultz (HOU)

Now drop down the salary scale.

Dalton Schultz costs $3,400.

His 4x target is only 13.6 points.

He's reached that five times in 19 games.

That's a 26.3% 4x hit rate compared with a tight end median of about 11.5%.

This isn't an argument that Dalton Schultz is a better football player than Nico Collins.

That would be ridiculous.

They're being asked to do completely different things.

Collins needs 28 points.

Schultz needs 13.6.

SmashTracker simply shows us how often each player has historically cleared the scoring bar created by this week's salary.

That's the value of the approach.

Two Players Outside the Featured Games We Can't Ignore

Starting with games doesn't mean we're going to become prisoners of game totals.

Sometimes an individual player flashes such a strong historical signal that he forces his way into the conversation anyway.

Two receivers do that this week.

Drake London (ATL)

Drake London costs $6,500.

His projection sits at 16.71 points.

His 4x target is 26.

He's reached that score four times in 12 games.

That's a 33% 4x hit rate compared with a receiver median of only 10%.

More than three times the positional median.

That's too strong a historical ceiling signal to dismiss simply because his game wasn't one of our featured environments.

London belongs on the radar.

Wan'Dale Robinson (TEN)

Wan'Dale Robinson gives us another interesting case.

He's $4,800 and projects for 10.97 points.

His 4x target is 19.2.

He's reached that score four times in 16 games.

That's a 25% 4x hit rate.

Again, the wide receiver median is 10%.

The history is interesting.

But his game is also one of the lower-total environments on the slate.

And that's exactly the kind of tension we're looking for right now.

History says investigate.

Game environment says proceed carefully.

Friday can help us figure out which side wins.

The Week 1 Player Pool Radar

We've got enough information now to organize our starting watch list.

But remember:

This is not the final Core Player Pool.

Nobody has earned a lineup spot.

Nobody has been eliminated.

These are simply players who have given us a reason to keep investigating.

Three Questions We Need Answered by Friday

Rather than pretending we know everything on Wednesday, let's narrow the research down to three major questions.

The Investigation Has Started. The Player Pool Hasn't.

This is the point where DFS players can make a mistake.

You find something you like early in the week and spend the next three days trying to prove yourself right.

That's not the goal.

We're not trying to defend Wednesday's opinions.

We're trying to make the best decisions possible by Sunday.

Today we've done three things:

We started with the games.

We found players inside those games who deserve attention.

And we asked whether their historical production gives us evidence that the tournament-level score we're paying for actually exists.

Sometimes smash history confirms what we already thought.

Sometimes it points us toward somebody we might have overlooked.

And sometimes it forces us to ask a tougher question about one of the biggest names on the slate.

That's exactly what the Player Pool Radar is supposed to do.

Start the process.

Find the interesting spots.

Build the watch list.

Then let the rest of the week give us the evidence we need to make the final decisions.