Defensive Back RAS: Does It Matter? A Comprehensive Analysis

For part 34 of our “Does It Matter?” series, we looked into the question of whether a Defensive Back’s Relative Athletic Score (RAS) can predict their success in the NFL. From this, we uncovered a specific range where RAS consistently appears more in the top fantasy football finishers compared to the bottom finishers. Here are all of our findings:

What Is RAS?

Relative Athletic Score (RAS) is a metric used to evaluate the athleticism of NFL prospects based on their performances in Combine and Pro Day drills. Developed by Kent Lee Platte in 2013, RAS takes various physical attributes such as speed, agility, explosiveness, and size to normalize them on a scale from 0 to 10. The results are then color-coded to provide a quick visual comparison of a player’s athletic traits relative to other players of the same position. This system helps teams and analysts quickly assess the athletic potential of prospects. Us at BrainyBallers have used RAS religiously in evaluating talents.

Methodology

Our study focused on NFL players who finished in the top 50 fantasy football finishers every year since 2003. We defined the “bottom 10” as those finishing 41st to 50th place each season.

Why the top 50? We chose the top 50 to maintain a “happy medium” in our analysis. If we looked beyond the top 50, we’d start including players who are on the edge of staying on an NFL roster. These fringe players are obviously not likely to score in the top 10, and could only skew our data. Although, we wanted to compare the best to the worst performers within a reasonable range. Simply comparing the top 10 to the 11th place, or including an average number which includes the 11th place doesn’t fulfill our personal itch of identifying meaningful trends. By focusing on the top 50, we ensure a broad, yet relevant, comparison without diluting the significance of standout performances.

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DB RAS Averages Chart

To begin our analysis, we created an averages chart which categorizes players into four groups: top 5, 10, 11-30th, and 31-50th since 2003. Surprisingly, no clear trends emerged from these charts. In 12 out of 21 seasons (57.1%), the top 10 finishers had the same or higher RAS than those who finished 31st-50th. This caused initial doubt in RAS as a meaningful metric, as the averages chart seems to be a good predictor of how the linear regression typically will pan out.

Segmented Top & Bottom 10 Finishers Since 2003

Further, we segmented the top 10 finishers since 2003 into increments of 0.1 RAS. This segmentation revealed only a possible slight emphasis on higher RAS scores amongst the top 10. The mere slight weight difference of these charts showed that RAS might not be the decisive factor we’d hoped for in differentiating elite fantasy players from average ones. Those charts can be seen below, with the top 10 first.

DB RAS Differences Chart

In our quest to discover the RAS (Relative Athletic Score) threshold that indicates the highest likelihood of NFL success for Defensive Backs, we created a differences chart. 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. By looking at each RAS score, adding the next 0.5 RAS increment, and subtracting the bottom 10 results from the top 10 results, we noticed that a RAS of 8.9 and above seems to correlate with high-performing DBs. This gave us a good threshold to explore further.

Verifying the Optimal DB RAS Range: Bottom 10

To validate this threshold, we compared the RAS scores of all DBs who finished in the bottom 10 from 2003 onwards. Out of 164 DBs, 46 had a RAS of 8.9 or higher, accounting for 28.0% of this group. Our goal was to see if a similar or higher percentage appeared in the top 10, indicating whether this RAS range is common among top-performing DBs or just all DB’s. That will be evaluated next.

Verifying the Optimal DB RAS Range: Top 10

Amongst the 173 DBs who finished in the top 10 between 2003 and 2023, 60 players had a RAS of 8.9 or higher. This represents 34.7% of top 10 finishers, a 6.6% increase from the bottom 10 group. This suggests that we may have identified an average top-performing DB’s RAS rather than just an average RAS for all DB’s. Although this is great, this is very unspectacular compared to all our T10 to B10 findings for other metrics.

Verifying the Optimal DB RAS Range: Fine-Tuning

Using our spreadsheet, we experimented with different RAS ranges to determine the most productive range. The results showed that adjusting our focus to a RAS range of 9.1 to 9.8 led to an even more significant outcome. This refined range demonstrated an 11.7% higher top 10 appearance rate compared to the bottom 10. Therefore, this will be the subject of this study going forward.

Establishing the Critical RAS Threshold for Defensive Backs

Next, we broke down the top 50 fantasy football finishers to identify critical values to fuel our StarPredictor Score (SPS) model, which will attempt to predict potential NFL successes and busts. For this, we categorized fantasy finishers into five groups of 10, ensuring a thorough understanding of the RAS impact across all performance levels. Interestingly, we found that the minimum RAS across the top 10, 20, 30, 40, and 50 finishers consistently held at 1.30.

Critical Values:

• Top 10 min: 1.30 RAS
• Top 20 Min: 1.30 RAS
• Top 30 Min: 1.30 RAS
• Top 40 Min: 1.30 RAS
• Top 50 Min: 1.30 RAS

Due to this, 1.3 RAS (after rounding) will serve as a critical threshold for when we produce our StarPredictor Score (SPS) model. Essentially, Defensive Backs must have a 1.3 or higher RAS in order to not be considered a certain future bust by our 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:

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DB RAS Regression Testing

Using standard statistical methods, we investigated the correlation between a DB’s RAS and their fantasy production. The findings were as follows:

• P-Value: 0.0932
• R² Value: 0.00392

Surprisingly, these values suggest no significant correlation between a DB’s RAS and their fantasy output. Typically, a P-value below 0.05 demonstrates a strong correlation, yet here, our P-value is much higher. Similarly, an R² value of 1.0% or above would indicate a stronger predictive relationship; however, the R² we observed showed that only 0.4% of the variance in fantasy scores could be explained by RAS alone.

Despite these findings, our analysis won’t fully dismiss RAS but rather recognize that 99.6% of performance variance is influenced by other factors.

Decadal Differences

Further analysis included examining how relevant these RAS values are over decades. Our decadal differences chart uncovered an important trend: RAS’s impact has diminished in recent years, particularly in mid-range finishers. This insight will further temper the weight of RAS in our SPS model.

Application to 2024 Rookie DB NFL Class

With our RAS range identified, we’re now turning our focus to the 2024 Rookie DB class, while breaking down how these prospects align within our established optimal RAS Range. This breakdown can be seen below:

2024 NFL Rookies in our optimal range (9.1 to 9.8 RAS):

2024 NFL Rookies out of our optimal range:

2024 NFL Rookies with no RAS:

Conclusion

While our study revealed insights, it did not uncover groundbreaking correlations between RAS and fantasy success. Our findings found that Defensive Backs with a RAS between 9.1 and 9.8 prevailed the most consistent top-level performance in the NFL. Although, there was no regression testing support. The weight this will have in the SPS model will be minimal.

More Data Next Week!

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 35 of “Does It Matter?” we will be finding an average Running Backs touches at career decline. What is it going to be? Mark your calendars; every Saturday we shed light on the topics that matter to you.

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Stats To Use For Scouting Potential League Winners

Everybody Knows Stats Are Cool. But Which Stats Are The Coolest and Mean The Most? 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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