Linebacker Weight: Does It Matter? A Comprehensive Analysis
12/14/2024
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In Part 35 of our “Does It Matter?” series, we looked to find whether a linebacker’s weight could predict their success in
For part 37 of our “Does It Matter?” series, we attempted to find whether a linebacker’s 40-yard dash time can predict their success in fantasy football. From looking into our data, we found an optimal range and 10 rookies who fell within that range. Here is the breakdown of all our findings:
For our analysis, we examined the top 50 fantasy football finishers since 2003. Throughout this study, you will see the term “bottom 10”, which is defined as leaderboard finishers ranked from 41st to 50th each season.
Why the top 50? The decision to analyze the top 50 allowed us to maintain a “happy medium.” Examining players further down the leaderboards would be looking at fringe roster players, potentially only skewing our data given their unlikelihood to rank in the top 10. Conversely, going as far down as 50 allowed us to compare the best to the worst still.
To begin our study, our averages chart categorized finishers into 4 different groups: Top 5, Top 10, 11th-30th, and 31st-50th places. From this, it is seen that 15 out of 21 seasons (71.4%), the Top 10 performers had the same or lower 40-times compared to the 31st-50th finishers. This implies a subtle trend that lower 40-times align with higher fantasy football scores more times than not.
We also segmented the top and bottom 10 finishers’ 40-times into 0.01-second increments. For this analysis, it was difficult to see exactly where the top 10 contrasted from the bottom 10. Typically, it is relatively easy to identify how the weight of the top 10 chart is different than the bottom 10, which you can’t easily decipher here.
In the pursuit of identifying an applicable threshold linking 40-yard dash times to NFL success, we created a differences chart to compare individual 40-times plus the next 0.05 seconds, 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 desired consistent top level consistency we are hoping for. Through this chart, it appeared as though 4.62 seconds and below was a potential threshold for top performances. We will next attempt to verify this by applying this to all top and bottom 10 finishers since 2003.
By testing the above mentioned range and altering it to different nearby ranges and thresholds, it was revealed that 4.60 seconds and below prevailed the highest producing optimal range, producing a 17.5% higher top 10 appearance rate than those in the bottom 10. Therefore, this will be our optimal range for Linebacker 40 Yard Dash Times, and will be the subject of this research going forward.
To find maximum allowable 40-times for our SPS model, we categorized the top 50 fantasy finishers into subgroups of the top 10, 20, 30, 40, and 50. Those findings are below:
Due to this, we identified 5.16 seconds as a crucial threshold for when we build our StarPredictor Score (SPS) model. This model will attempt to predict busts and successes, and we are hoping to have this ready by the ’27-’28 NFL season. Essentially, Linebackers must measure in at 5.16 seconds or lower in order to not be considered a certain future bust by our model. You can subscribe to our mailing list to get updates on this model when it begins coming out here:
Utilizing standard statistical methods, our data returned a Pearson value of -0.125. This indicates a negative, but strong, correlation between a linebacker’s 40-time and overall fantasy production, reinforcing the idea that lower 40-times produce higher fantasy football success. For world-class athletes, our minimum Pearson value goal that would indicate statistical significance would be >0.1 or < -0.1. For reference to something that everyone acknowledges matters in prospect scouting and its accompanying Pearson value, RB draft capital prevailed a -0.234 Pearson value.
By examining our optimal range across decades, we were able to contextualize the significance of our identified 40-time range in terms of time significance. These findings suggest the optimal range has more importance in the most recent decade, as you can see below:
| 2004-2013 | |||
| Top 10 | 11 through 40 | Bottom 10 | |
| All count | 67 | 205 | 65 |
| All 4.60 and below | 24 | 37 | 14 |
| % (Optimal Range/all) | 35.8% | 18.0% | 21.5% |
| 2014-2023 | |||
| Top 10 | 11 through 40 | Bottom 10 | |
| All count | 77 | 236 | 74 |
| All 4.60 and below | 41 | 82 | 22 |
| % (Optimal Range/all) | 53.2% | 34.7% | 29.7% |
With the groundwork laid out, our final step is evaluating how the 2024 rookie linebacker 40-yard dash times align with our optimal 40-time range. That breakdown is below:
| Payton Wilson | 4.43 seconds |
| Dallas Turner | 4.46 seconds |
| Kalen DeLoach | 4.47 seconds |
| Edgerrin Cooper | 4.51 seconds |
| Trevin Wallace | 4.51 seconds |
| Jordan Magee | 4.55 seconds |
| Edefuan Ulofoshio | 4.56 seconds |
| Mohamed Kamara | 4.57 seconds |
| Curtis Jacobs | 4.58 seconds |
| Chris Braswell | 4.60 seconds |
| Tyrice Knight | 4.63 seconds |
| Nathaniel Watson | 4.63 seconds |
| Cedric Gray | 4.64 seconds |
| Darius Muasau | 4.70 seconds |
| Easton Gibbs | 4.73 seconds |
| Aaron Casey | 4.75 seconds |
| Maema Njongmeta | 4.91 seconds |
| Marist Liufau | 4.64 seconds |
| Gabriel Murphy | 4.68 seconds |
| Javon Solomon | 4.72 seconds |
| Steele Chambers |
| TyRon Hopper |
| Michael Barrett |
| JD Bertrand |
| Tatum Bethune |
| Junior Colson |
| Tommy Eichenberg |
| Jaylan Ford |
| Jontrey Hunter |
| Jeremiah Trotter Jr. |
Speed may not be the sole predictor of NFL success. Although, our research suggests a clear relationship between faster 40-times and higher fantasy football finishes. The optimal range for Linebacker 40-yard dash times is 4.60 seconds and below, resulting in a 17.5% higher top 10 appearance rate than in the bottom 10.
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. Premium Analytics subscribers get priority. All of our research can be found on our Analytics Page. Up next on our agenda for Part 38 of “Does It Matter?” will be an examination of Linebacker RAS (Relative Athletic Score): Does it matter? If so, what’s the RAS threshold necessary for NFL success? Mark your calendars; every Saturday we shed light on the topics that matter to you.
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 $0.49/month!
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