For our “Does It Matter?” series, Part 44, we dove into the question of whether there is correlation between a wide receiver’s draft capital and their NFL success. Our analysis used historical data since 2003 to attempt to identify patterns that may have predictive power. This analysis is particularly valuable for comparing two players or evaluating a single player, but it shouldn’t be considered a definitive predictor of a player’s success or failure potential. Here’s all of our findings:
For this study, we focused on the top 50 fantasy football finishers each year since 2003, using PPR (Points Per Reception) fantasy scores. Throughout this study, the “bottom 10” will refer to players who finished between 41st and 50th in fantasy rankings each season.
Why the top 50? Choosing the top 50 fantasy performers allowed us to maintain a “happy medium” by avoiding the fringe roster players who rarely are likely to achieve top 10 performances. Although, going from the top 10 to the 41st-50th place finishers allowed us to examine truly the “best” and “worst” performers, while steering clear of the mid-range finishers.
To start, we created an averages chart which categorizes top fantasy finishers into 5 different groups: top 5, top 10, 11th-30th, and 31st-50th place. Across 19 out of 21 seasons (90.5%), top 5 finishers had similar or higher draft capital than the 31st-50th group. This suggests a strong correlation between higher draft positions and better fantasy performances.
Further, we segmented the top and bottom 10 finishers into 10 overall pick increments, rounded to the nearest 10. This revealed a trend where lower draft capital were more prevalent among top performers.
To find where the highest increase in performance occurs and where the least unique players emerge (indicating consistency), we developed a differences chart. This chart compares each draft capital plus the next 30 overall picks, subtracting the bottom 10 results from the top 10. The chart’s desired outcome is a negative number for unique differences (Orange) and a positive number for non-unique differences (Blue). This would indicate the top level consistency we are hoping for. From this, we identified the 50th overall pick and below as a possible range for consistent high performances. We will next attempt to verify or debunk this range.
To ensure maximum accuracy, we adjusted the range to attempt to identify the highest producing one in our spreadsheet. By testing various numbers around our initial findings, we discovered that the 70th overall pick (rounded to nearest 10) and below yields an 18.8% higher appearance rate in the top 10 compared to the bottom 10. This refined range will be the focus of this study going forward, and will be our optimal range for WR draft capital.
We broke down the top 50 fantasy finishers into 5 different categories: top 10, 20, 30, 40, and 50. This will help find a critical threshold for wide receivers when determining the StarPredictor Score (SPS), designed to predict player success or failures. The critical values are as follows:
Due to these findings, 257th overall (i.e., undrafted) became our critical threshold for Wide Receivers for our StarPredictor Score (SPS) model. Essentially, there is no critical value that will be assigned to WR’s for draft capital in our StarPredictor Score (SPS) model. We are hoping to have this model fully functional by the beginning of the 2027 NFL season. You can subscribe to our mailing list to get updates on this model when it begins coming out here:
Using standard statistical methods, we calculated a Pearson Value of -0.142, indicating a strong correlation between draft capital and fantasy production. We are hoping for a minimum of 0.1, or a maximum of -0.1 while studying world-class athletes as we are. For reference to something that everyone acknowledges matters in prospect scouting, and to show the accompanying Pearson value, RB draft capital prevailed a -0.234 Pearson value.
To assess whether this is a recent or dying trend, we compared the last two decades in terms of our identified WR Draft Capital range for the top 10, 11th to 40th place finishers, and the bottom 10. This chart revealed that the optimal range has remained relatively consistent over time, reinforcing the validity of our findings.
| 2004-2013 | |||
| Top 10 | 11 through 40 | Bottom 10 | |
| All count | 100 | 298 | 99 |
| All 70 and below | 71 | 172 | 49 |
| % (Optimal Range/all) | 71.0% | 57.7% | 49.5% |
| 2014-2023 | |||
| Top 10 | 11 through 40 | Bottom 10 | |
| All count | 100 | 300 | 100 |
| All 70 and below | 66 | 191 | 49 |
| % (Optimal Range/all) | 66.0% | 63.7% | 49.0% |
Next, we applied our findings to the 2024 Rookie Wide Receiver NFL class.
We broke it down into players who fell within our optimal range, and those who fell out of it. Those findings can be seen below:
| Marvin Harrison Jr. | 4th overall |
| Malik Nabers | 6th overall |
| Rome Odunze | 9th overall |
| Brian Thomas | 23rd overall |
| Xavier Worthy | 28th overall |
| Ricky Pearsall | 31st overall |
| Xavier Legette | 32nd overall |
| Keon Coleman | 33rd overall |
| Ladd McConkey | 34th overall |
| Ja’Lynn Polk | 37th overall |
| Adonai Mitchell | 52nd overall |
| Malachi Corley | 65th overall |
| Jermaine Burton | 80th overall |
| Roman Wilson | 84th overall |
| Jalen McMillan | 92nd overall |
| Luke McCaffrey | 100th overall |
| Troy Franklin | 102nd overall |
| Javon Baker | 110th overall |
| Devontez Walker | 113th overall |
| Jacob Cowing | 135th overall |
| Anthony Gould | 142nd overall |
| Ainias Smith | 152nd overall |
| Jamari Thrash | 156th overall |
| Bub Means | 170th overall |
| Jha’Quan Jackson | 182nd overall |
| Malik Washington | 184th overall |
| Johnny Wilson | 185th overall |
| Casey Washington | 187th overall |
| Tejhaun Palmer | 191st overall |
| Jordan Whittington | 213th overall |
| Ryan Flournoy | 216th overall |
| Brenden Rice | 225th overall |
| Devaughn Vele | 235th overall |
| Tahj Washington | 241st overall |
| Cornelius Johnson | 253rd overall |
Our study highlighted a correlation between draft capital and fantasy football success for wide receivers. While anomalies obviously will exist, high draft capital generally correlates with higher fantasy rankings. You should focus on players drafted anywhere from the 75th pick and earlier. This range includes the 1st round up to just before the midpoint of the 3rd round.
Everybody knows stats matter, but which stats mean the most and which are just noise? Additionally, what are the target benchmarks athletes should aim to achieve in each statistic? That's what this chart answers. Type in your desired position in the "Position" field to see the key metrics players need for a higher chance of NFL success. Then, filter the success boost or Pearson value from highest to lowest to see which stats mean the most. Pearson values of 0.1 and higher OR -0.1 or lower indicates correlation. Unlock all metrics by signing up with the links provided. For only $0.99/month!
Our series has always sought to push the boundaries of sports analytics. This latest installment reaffirms our commitment to uncovering the hidden dynamics that define the game. Every Saturday, we’ll dive into intriguing questions, bust myths, and settle debates with thorough analysis. We welcome your input. Therefore, please leave comments or reach out with topics you’re eager to see dissected. All of our research can be found on our Analytics Page. Up next on our agenda for Part 45 of “Does It Matter?” is an examination of Wide Receiver College Yards Per Route Run (Y/RR): Does it matter? If so, what’s the Y/RR threshold necessary for NFL success? Mark your calendars; every Saturday we shed light on the topics that matter to you. All it takes is a quick question being asked and we will go to work for you!
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