Fantasy Football WR PPR Draft Strategy: Projections vs. ADP, as well as Hidden Clues to Spotting Overperformers
Lessons Learned
Introduction
By the time fantasy draft season hits its stride, wide receivers dominate the conversation. The elite ones are gone in the first two rounds, and the middle rounds are littered with names deemed to have “safe floors,” others as “high-upside gambles” who could just as easily disappear from relevance.
Unlike quarterbacks or running backs, wide receivers operate in a far less predictable ecosystem. A QB injury, a rookie breakout on the same team, or a midseason scheme shift can completely upend target hierarchies. In PPR formats especially, a receiver’s value hinges on subtle things: route depth, separation rate, red zone usage, the kind of metrics that rarely show up in highlight reels but can swing an entire season.
This is the third entry in my six-part series dissecting how well expert projections and ADP fared across each fantasy position in 2024. I’ve already looked at quarterbacks and running backs. Now, it’s time to see what trends hold for a position where volume can change in a single week and “boom or bust” is practically baked into the job description.
Here, I’m chasing two questions:
Between projections and ADP, which came closer to nailing wide receiver performance in 2024 vs. actuals?
Could any of the biggest breakouts have been spotted in advance, or were they true draft-day landmines waiting to be unearthed?
Data and Approach
For each wide receiver heading into the 2024 season, I gathered their expert projections, Average Draft Position (ADP) from thousands of real drafts, and their actual season-long fantasy point totals. Additional details that are position-specific are also included, such as: targets, receptions, receiving yards, yards per reception, receiving touchdowns, catch rate, yards after catch (YAC), fumbles, and player age. With PPR scoring in mind, target share and efficiency stats were especially important, since they often separate the weekly WR3 dart throw from the reliable WR1.
A sample of the raw data used for this analysis is provided in Figure 1.
Just like with RBs, I excluded players whose seasons ended before they began. If a WR barely saw the field or posted near-zero points, that was an injury or depth chart issue, not a failure of projections or ADP. I also cut out extremely low-projection players to keep the focus on those realistically draftable in most leagues.
From there, I converted projections, ADP, and actual results into rankings. Rankings strip away the distraction of raw point totals, which can be misleading when comparing players across a 17-game season. For instance, if a WR was projected WR12, drafted WR15, and finished WR8, the ranking deltas make that difference clear without the noise of decimal points.
Projections vs. ADP Accuracy
Once the wide receiver dataset was finalized, I ran the same accuracy tests used for quarterbacks and running backs to answer the key question: in 2024, who predicted wide receiver performance better...expert projections or ADP?
The three metrics, with results for each, are as follows:
Spearman correlation – measures how well preseason rankings matched actual finishes, regardless of the exact point spread. Spearman correlation: 0.630 for projections vs. 0.596 for ADP
Mean Absolute Error (MAE) – the average difference, in ranking spots, between prediction and reality. MAE: 11.47 for projections vs. 11.79 for ADP
Root Mean Square Error (RMSE) – similar to MAE but penalizes big misses more heavily. RMSE: 14.16 for projections vs. 14.80 for ADP
In all three measures, projections edged out ADP. While the differences weren’t massive, they were consistent, suggesting that for wide receivers, model-based projections provided a slightly clearer picture than the crowd consensus.
This is in contrast to the running back results, where ADP held the advantage. One possible reason: wide receivers tend to have more stable year-to-year roles and production patterns than running backs, making them easier for projection models, which rely on historical stats, usage rates, and team context, to evaluate. The public may still be swayed by offseason narratives, camp hype, or single highlight plays, leading to slightly more ranking noise.
The takeaway? For wide receivers in 2024, trust the models. When projections and ADP disagreed, siding with the data-driven forecast would have been the slightly better call.
Diamonds in the Rough: 2024 WR Overperformers
This is where the value really showed up. The biggest WR overperformer of 2024 was Ja’Marr Chase, who wasn’t exactly a sleeper by ADP (WR4) or projection (WR5), but he still blew past expectations: 403.0 actual points vs. 281.2 projected for a +121.8 surge, finishing WR1. Right behind him was rookie Brian Thomas Jr. (ADP WR35, proj WR34), who erupted for 284.0 vs. 175.6 (+108.4) and finished WR4, a massive hit for anyone who took the shot. Jerry Jeudy (ADP WR43, proj WR38) turned in 240.9 vs. 165.7 (+75.2) to land as WR12, and Ladd McConkey (ADP WR30, proj WR36) delivered 240.9 vs. 172.7 (+68.2) to finish WR11. Teammates Quentin Johnston (ADP WR50, proj WR56) and Jaxon Smith-Njigba (ADP WR32, proj WR29) both paid off too: Johnston logged 174.7 vs. 106.7 (+68.0) for WR36, while JSN posted 253.0 vs. 186.1 (+66.9) for WR8.
What I like about this group is how it blends archetypes. Chase was a premium pick who still beat a high bar; Thomas and McConkey smashed as rookies; Jeudy finally translated opportunity into steady production; and Johnston/JSN validated second-year jumps with meaningful leaps over modest projections. The common thread isn’t one tidy stat, it’s roles that expanded faster than models (and often the market) priced in, plus enough efficiency and scoring to make the jump matter.
Searching for Predictive Clues
Looking at the stat-level correlations, it’s clear that some preseason metrics do a better job than others at hinting which wide receivers will outperform expectations. Efficiency stood out as the most overlooked edge, both receiving touchdowns and yards per target had the strongest positive relationships with overperformance, suggesting that models and ADP alike often fail to fully account for receivers who can maximize their output with each opportunity. Age also carried a mild positive correlation, hinting that older players with stable roles may be consistently undervalued due to lingering biases in analyst rankings.
On the flip side, some of the most familiar stats in fantasy proved to be traps. Projected receiving yards, often a centerpiece of preseason optimism, showed a tendency to overshoot reality, leaving managers holding players who didn’t deliver on volume expectations. Rushing usage for receivers, whether measured in yards, attempts, or efficiency, offered little to no predictive value and often skewed projections. Even fumble metrics, which seemed to weigh heavily in preseason models, showed minimal impact on actual fantasy output.
Ultimately, the numbers point to a recurring theme: projections tend to lean too heavily on raw yardage totals and ancillary rushing stats, while undervaluing efficiency and scoring potential. For drafters, spotting that gap may be the key to finding receivers who quietly deliver above their preseason billing.
Draft Strategy Implications
The 2024 wide receiver data reinforced that projections can be directionally accurate but still contain blind spots, especially in how certain player traits and usage patterns are valued.
When looking at which metrics aligned with performance, a few stood out:
Positive relationships (metrics linked to overperformance):
Receiving touchdowns - WRs projected for more TDs tended to exceed expectations, suggesting models may still undervalue the impact of high-leverage red-zone targets.
Yards per target - Efficiency was a quiet but important signal; WRs who made more out of each opportunity often translated that into better-than-expected fantasy output.
Age - Veteran receivers were slightly more likely to beat projections, hinting that analysts may be too quick to discount older players with established roles.
Negative relationships (metrics linked to underperformance):
Receiving yards projections - High yardage forecasts were the most overestimated element, with many WRs falling short of those lofty totals.
Rushing involvement - WRs projected for notable rushing yards or attempts rarely hit those marks, and the impact on total fantasy points was limited.
Fumbles - Projected fumbles appeared overweighted in the models, with actual results showing far less turnover impact than expected.
How this shapes my draft approach:
I’d lean toward WRs with strong efficiency metrics (especially yards per target) even if their projected totals aren’t eye-popping.
I’d be more willing to take a shot on proven veterans when their ADP suggests age-based skepticism.
I’d treat rushing usage for WRs as a “bonus” rather than a core value driver.
I’d be cautious of WRs propped up purely by high yardage projections without matching efficiency or touchdown upside.
While projections remain a valuable baseline, layering in these efficiency and bias insights gives you an edge, helping you spot the players most likely to quietly beat expectations while avoiding those set up to underdeliver.
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