Linebacker 40 Yard Dash: Does It Matter? A Comprehensive Analysis
12/21/2024
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For part 37 of our “Does It Matter?” series, we attempted to find whether a linebacker’s 40-yard dash time can predict their
For part 18 of our “Does It Matter?” series, we dove into the data to figure out whether shuttle times at the NFL Combine can predict success for wide receivers in fantasy football. Further, we looked to uncover a range which occurs in top level performances most frequently.
To maintain consistency in our numbers, we strictly used NFL Combine shuttle times. Further, we only looked at WRs who finished in the top 50 in fantasy football points per reception (PPR) since 2003. Throughout this study, you will see the “bottom 10” term which is defined as PPR finishers 41st-50th every season.
We created an averages chart showing the shuttle times for WRs in different finishing categories. The goal of this was to get an initial feel for whether lower shuttle times are for sure going to prevail more top Level performances or not. The chart’s categories are as follows:
However, our findings from this data were inconclusive. The averages chart appeared to not indicate any trends that correlated shuttle times with fantasy football success.
To get a closer look at top and bottom 10 finishers, we began by segmenting the shuttle times of all top 10 finishers since 2003 into 0.01 second increments. We then did the same with the bottom 10 finishers. Both charts can be seen below this, with the top 10 first. From this, you can see that the most significant increase in successful WRs appeared at the 4.25-second mark when you compare both charts. This finding suggests that shuttle times at or around 4.25 seconds could be a benchmark for the range we will hopefully find next in our differences chart.
To achieve our goal of finding a range of shuttle times where more top-level performances occur versus bottom-level performances, we created a differences chart. This chart compares top 10 and bottom 10 NFL Combine shuttle times, plus the next 0.10 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 performances we are hoping for. From this analysis, you can see that shuttle times of 4.35 seconds and under appears to be a potential performance range that correlates to higher NFL success. This was a big insight into setting the performance threshold, which we will verify next.
Next, we wanted to verify whether this range occured more amongst all WR’s, or if this occurred more just amongst top performing WR’s. Therefore, we ran the numbers to see how often this threshold occurred in the bottom 10. After this, we will compare against the top 10.
So here it is: for the bottom 10, there were 96 WRs in our data with shuttle times. 79 of which finished at or under 4.35 seconds. This accounted for 82.3%. This establishes a benchmark for comparing it to the top performers. If more than 82.3% occurred in the top 10, then we found a more frequent top performing Shuttle time threshold, which you will see next.
To determine whether our threshold represented the average WR’s shuttle time, or the average top-performing WR’s shuttle time, we applied it to all top 10 finishers from 2003 to 2023. Out of 103 top 10 finishers, 89 were in the 4.35 seconds and under range, accounting for 86.4%. This shows a 4.1% increase, which is relatively insignificant compared to our other findings and the most insignificant WR findings thus far. Luckily, we recently upgraded our spreadsheets to make quick threshold/range adjustments.
This fine-tuning ability helps us ensure we’ve identified the highest-producing range. After testing various numbers close to our initial findings, we found that adjusting the range to 3.87 to 4.30 seconds resulted in a 15.4% higher occurrence in the top 10 than in the bottom 10! This range will be the subject of this article going forward.
We next wanted to identify a critical NFL Combine shuttle time where different fantasy leaderboards have never seen. There was a massive outlier, which was Juju Smith-Schuster, whose shuttle time was 5.01. Excluding him, here are the maximum shuttle times seen across different leaderboard thresholds since 2003:
Due to these findings, 4.50 seconds will be our critical value. This is for our StarPredictor Score (SPS) model, where we will be attempting to predict NFL successes or busts. Essentially, athletes must finish under or at 4.50 second shuttle times in order to not be considered a bust. We are hoping to have this model fully functional by the beginning of the 2025 NFL season.
We next wanted to use standard statistical methods to see if there is a correlation between shuttle times and fantasy production. Here are the findings:
For P-Values, 0.05 and below indicates strong correlation, therefore showing this is not a strong predictor of fantasy production alone. As far as the above Rsquared value, this means that variations in shuttle times explain only 0.2% of fantasy production. In other words, 99.8% of fantasy scores can be attributed to other factors. Since we are studying world class athletes, the Rsquared value we are hoping for is a minimum of 1.0%. For reference to data which prevailed correlation, part 13 of our “Does It Matter?” series found that BMI predicts 1.4% of the changes in WR fantasy points. Here is the shuttle time regression chart:
Despite the lack of regression testing support, we wanted to see if this is an emerging trend, or the opposite. By applying the optimal range to the last two decades, a trend emerged where most of the top 10 finishers consistently fell within 3.87 to 4.30 seconds more frequently in recent years. As you can see by comparing the frequency which this range shows up in the top 10 versus the bottom 10, there is a 15.6% increase in the last decade versus the 2004-2013 decade. This breakdown can be seen below:
| 2004-2013 | |||
| Top 10 | 11 through 40 | Bottom 10 | |
| All count | 35 | 162 | 38 |
| Between 3.87 and 4.30 | 27 | 116 | 27 |
| % (hard zone/all) | 77.1% | 71.6% | 71.1% |
| 2014-2023 | |||
| Top 10 | 11 through 40 | Bottom 10 | |
| All count | 62 | 174 | 55 |
| Between 3.87 and 4.30 | 45 | 100 | 28 |
| % (hard zone/all) | 72.6% | 57.5% | 50.9% |
We matched the 2024 rookie WR NFL class against our identified shuttle time range (3.87 to 4.30 seconds). The full class is listed below:
To have some more fun, we found that the average shuttle time for all athletes was 4.22 seconds. Also, the median time was 4.21 seconds. If you want to get more specific, we found a much more narrow range which produces more top talent between 4.13 to 4.30. This range occurred in the top 10 at a 21.2% higher rate than the bottom 10.
We attempted to uncover a specific shuttle time where the highest increase in performance occurs while also identifying the range where the least unique players appear, indicating top-level consistency. Through this research, we found that shuttle times between 3.87 and 4.30 seconds are not just an average WR measure, but an optimal performance threshold for top athletes. Although, it should be taken with a grain of salt as we seen no regression testing support for shuttle times alone being a performance predictor.
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 19 of “Does It Matter?” is an examination of the WR 3-Cone Drills: Do they matter? If so, what’s the 3-Cone time threshold necessary for success? Mark your calendars; every Saturday we shed light on the topics that matter to you. If you’re a Premium Analytics subscriber, all it takes is a quick question being asked and we will go to work for 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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For part 37 of our “Does It Matter?” series, we attempted to find whether a linebacker’s 40-yard dash time can predict their
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