Every draft cycle, the NFL media machine finds a handful of stats it can turn into a personality trait. Contested catch percentage is one of the favorites because it’s simple, it’s punchy, and it sounds like scouting. And I’m not talking about random Twitter accounts with an egg avatar. I’m talking about real platforms with real audiences (NFL Stock Exchange Podcast, the PFF NFL Show, and NFL on ESPN) leaning on contested catch percentage like it’s a stable, transferable “catch-point skill” without spending much time on the unglamorous parts: where the number comes from, how “contested” is defined, how it’s charted, and whether it actually translates from college to the NFL.
That’s the part that drives me insane about draft discourse: we act like we’re doing science while skipping the part where you actually test the claim. A stat becomes a label (“he’s a contested-catch guy”), the label becomes a conclusion (“he’ll win at the next level”), and that conclusion gets copy-pasted across an entire ecosystem of takes until it’s treated like a law of nature.
The only issue? College contested catches are not the same event as NFL contested catches. There's different coverage quality, different windows, different throw placement, different route trees, and (often) a completely different job description for the receiver.
So rather than echoing the same recycled take, I put it to the test and checked whether it actually translates.
Methodology: How To Test Contested Catch Percentage
I went through every wide receiver that had a combine or pro-day measurement over the past eight years, filtered out the receivers that had less than five contested catch opportunities per season, and sorted them into three height buckets:
- Short Wide Receivers (<5'11")
- Average-Sized Wide Receivers (5'11" - 6'2")
- Tall Wide Receivers (>6'2")
Then I charted variables built to capture both contested-catch efficiency and contested-catch environment using PFF’s advanced stats.
- Breakout College Contested Catch % (the year(s) used to evaluate a prospect's potential)
- College Contested Catch Opportunities
- SEC Indicator (a proxy for the densest weekly talent environment we can approximate in the CFB)
- No Rookie Season (NRS) NFL Contested Catch %
- No Rookie Season (NRS) NFL Contested Catch Opportunities
I use the "NRS" versions because rookie seasons are a chaos tax. If we’re trying to evaluate whether something translates, it’s fair to give players one year to adjust to the league’s speed and coverage quality.
Finally, I ran a reliability/correlation analysis (heatmaps) for both the entire sample and each height bucket separately.
The Big Misconception: What People Think CC% Proves
Here’s the “draft analyst shortcut” in one sentence: High college contested catch % = “wins at the catch point” = NFL translatable trait.
That conclusion feels intuitive because it’s visual, but contested catch percentage is not a clean skill isolate. It’s an outcome that depends on the types of targets, the quality of coverage, the QB’s timing/placement, and the definition of “contested” in the charting process.
So the only responsible question is: does it translate?
Findings: What The Heatmaps Actually Show
Before we get into the charts, a quick preface for anyone who hasn’t lived in Spreadsheet World: a correlation heatmap shows how strongly two variables move together. Each square compares two metrics (for example, NRS NFL Contested Catch % and Breakout College Contested Catch %) and assigns a correlation value on a scale from -1.0 to +1.0, which is also represented by color. (Red is negative, green is positive.)
In general, a correlation of +0.80 or higher suggests the two variables are highly correlated (they tend to rise and fall together). Values in the +0.40 to +0.70 range are moderately correlated, while anything below about +0.20 is so weak that it’s effectively noise for prediction purposes. The same logic applies in the negative direction: a correlation of -0.80 or lower indicates a strong inverse relationship, meaning when one goes up, the other tends to go down.
For example, if Metric A and Metric B had a correlation of +0.85, that would imply players who score high in A also tend to score high in B. On the flip side, if a pair of metrics came in at -0.85, that would imply that as A increases, B tends to decrease (an inverse relationship rather than a matching one).
Figure 1: All Wide Receivers (overall sample)
Breakout College Contested Catch % shows essentially no meaningful relationship with NRS NFL Contested Catch % (r ≈ 0.03). In other words, the “contested-catch guy” label based on college efficiency has weak predictive value once we remove rookie-season noise.
The big headline: Breakout College CC% does not meaningfully track with NRS NFL CC% in the overall sample. NFL Draft pundits who claim this is the case are incorrect or misinformed (or even negligent) of the data available.
Figure 2: Tall Wide Receivers (>6’2”)
For receivers taller than 6'2", Breakout College CC% trends negative versus NRS NFL CC% (r ≈ −0.14). That doesn’t prove “tall WRs can’t win,” but it does show the college efficiency percentage is not a stable projection tool for NFL contested efficiency.
This matters because tall receivers are the easiest group for the internet to anoint as “catch-point monsters.” If CC% were a clean translatable trait, this is where you’d expect it to pop. Instead, it doesn’t.
Figure 3: Average Size Wide Receivers (5’11”–6’2”)
The most “normal NFL body type” group still shows no meaningful relationship between Breakout College CC% and NRS NFL CC% (r ≈ 0.10). If you were waiting for the ‘safe’ archetype where the stat finally translates, this isn’t it.
This is the section that really undercuts the mainstream narrative. Even in the height range where most NFL starters live, the relationship is still weak. That means contested catch % is not behaving like a clean, portable trait; it’s behaving like a noisy outcome.
Figure 4: Short Wide Receivers (<5’11”)
For <5’11” receivers, Breakout College CC% still has almost no relationship with NRS NFL CC% (r ≈ 0.08). Meanwhile, NRS NFL contested opportunities skew negative relative to NRS efficiency (r ≈ −0.48), suggesting volume/role and difficulty can swamp the percentage. This does not imply that shorter WRs are worse at making contested catches, but when short WRs are put into high-contest roles, the average contest quality/difficulty tends to be worse, and the percentage reflects that.
This is the bucket where “contested catch %” gets used as a character trait most often. And the heatmap says: be careful. The college percentage is not reliably telling you what you think it’s telling you.
Why Contested Catch Stats Don't Translate Cleanly
If you want the simple version: the event changes. A “contested catch” in college can be a very different play than a “contested catch” in the NFL. Here are a few reasons why the translation breaks:
1) Percentages swing with denominator quirks: A breakout year can produce a high contested catch percentage off a relatively small number of true contested opportunities. That doesn’t mean the player is fraudulent. It means the stat is volatile.
2) NFL contests are higher difficulty by default: Even the SEC isn’t the NFL. The windows are tighter, the technique is better, and the timing is more punishing. “Open” gets redefined.
3) The role changes: College roles don’t always survive the jump. A guy who got fed 50/50 chances can become a separator, a motion piece, a decoy, or a schematic outlet.
4) “Contested” isn’t one type of play: A red-zone fade, a back-shoulder throw, and a slant that gets jarred late all count as “contested,” but they don’t test the same skills.
So when analysts talk like contested catch % is a stable trait (like it’s a vertical leap number) they’re flattening a complicated event into a single output.
What To Do With Contested Catch Data Instead
If contested catch percentage isn’t a reliable projection tool, that doesn’t make contested-catch data worthless; it just means we’ve been using the wrong part of it for the wrong job. Let’s act like smarter analysts and put the data to work where it actually tells us something: Use contested opportunities to contextualize play style.
NRS NFL contested opportunities can hint at:
- Usage: How often a player is asked to win in tight windows
- Role: Boundary bailout versus slot mover versus red zone profile
- Style: A receiver's "target diet"
More importantly, it can also trigger a useful scouting question: Does a player have a significant number of contested catch targets because he can’t separate, or because the offense asks him to win in tight windows? That’s a real question. And it’s a much better use of contested data than treating one percentage as a final grade.
2026 Draft Snapshot: Makai Lemon vs. Ja’Kobi Lane
This is exactly why the stat needs context:
Makai Lemon will measure in at under 5’11” and posted a 66.7% breakout contested catch rate, which will generate an easy “plays bigger than he is” talking point for draft analysts.
Ja’Kobi Lane, who is a 6’2+ receiver, has a lower breakout contested catch rate (43.5%) but based on evaluation, profiles as a legitimately strong contested catcher.
If you treat breakout CC% like a scouting verdict, you risk crowning the wrong guy and downgrading the right one because across buckets, breakout contested catch % doesn’t behave like a stable predictor of post-rookie NFL contested catch efficiency.
Conclusion: Stop Treating a Percentage Like A Trait
Contested catch percentage isn’t meaningless; it’s just a stat that gets asked to do a job it can’t reliably do, especially when it’s treated like a projection tool. The real problem isn’t the number; it’s the confidence people attach to it. If you’re going to build draft takes around data, you can’t ignore the basic question of whether it actually translates just because the stat makes for a clean narrative.
So here’s the takeaway fans can actually use:
- Don't draft the label
- Use contested catch opportunities as an indicator of role and style
But most importantly, don't just take what all analysts are saying at face value. If you've watched a player all year and thought he's done well, don't let someone who's watched two videos from Caddy's Cutups and looked at PFF's Advanced Stats tell you differently. Context matters. Just make sure you've done the research (or read the articles of someone who actually does).