2026 Fantasy Football Rookie Mock Draft 1.0
02/10/2026
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As the 2026 NFL Draft approaches, we are gearing up with our first rookie fantasy football mock draft. In this draft, we
For the next installment in our 93-part “Does It Matter?” series, we looked into another metric for Tight Ends: Speed Score (as popularized by PlayerProfiler). In this article, we look at whether a TE’s Speed Score – a metric that adjusts a player’s 40-yard dash time for their weight – actually predicts future fantasy success, what benchmarks define an elite prospect, and how much weight you should truly give this number in your prospect scouting sessions.
To conduct this study, we analyzed the top 50 PPR fantasy football finishers at the Tight End position dating back to 2003. All speed scores were sourced from PlayerProfiler.
Why the top 50? We chose this range to establish a “happy medium” for our data set. Expanding the pool further would have introduced “fringe” roster players who rarely see the field which would only skew the data. Conversely, we needed a significant enough sample to compare the best to the worst. By using the 41st–50th place finishers (our “Bottom 10”) as a baseline, we created a distinct contrast against the Top 10 elite finishers to see which physical traits truly separated them.
Our first test involved charting the average Speed Scores for three distinct groups since 2006: the Top 10, the 11th–30th finishers, and the 31st–50th finishers. A clear, undeniable trend emerged from this: Higher Speed Scores correlate with higher fantasy production. The data was extremely consistent across this timeline. In 18 out of 18 seasons (a perfect 100% hit rate), the top five fantasy finishers had higher average Speed Scores than those finishing in the 31st–50th range. This suggests that while speed isn’t the only factor for a Tight End, it acts as a significant “ceiling raiser” for Tight End production.
To dig deeper, we segmented every Top 10 finisher since 2003 into Speed Score “buckets” (rounded to the nearest 1.0). When comparing the distribution charts of the Top 10 versus the Bottom 10, the trend became even more obvious. The Top 10 finishers are significantly more weighted toward the higher end of the Speed Score spectrum. Players in the bottom tier of fantasy production typically lacked the size-speed adjusted explosiveness found in the top 10. Those charts can be seen next, with the top 10 coming firs:
Our main goal was to find a functional threshold that signals top-level consistency while minimizing “outlier” noise from unique players. To do this, we created a “Differences Chart.” This chart compared each Speed Score (plus a rolling window of the next 3.0 Speed Score), subtracting the results of the Bottom 10 from the Top 10 within that specific group. The chart’s desired outcome is a negative number for unique differences (Orange) and a positive number for non-unique differences (Blue).
From this visualization, a clear signal began to appear at the 105.0 and above mark. This served as our first indicator of an optimal range, which we will test to verify next.
To refine this further, we ran multiple range adjustments to ensure we pinpointed the exact window with the highest density of elite finishers compared to bottom finishers. After testing various thresholds near our initial 105 and above threshold, the data pointed to an even more significant cutoff. We found that a Speed Score of 108 and higher is the optimal range. Tight Ends in this range appear in the Top 10 at a rate 38.2% higher than they do in the Bottom 10. Therefore, this is the optimal benchmark you should look for when evaluating prospects and will also be included in our Ultimate Athlete Blueprints which offers an easy-to-read table housing all of our researched metrics combined in one place for you to view as seen here:
Due to these findings, Speed Scores could play a factor in our Star-Predictor Score (SPS) model. The Star-Predictor Score (SPS) is a scouting tool designed to maximize investment potential and reduce risks when drafting rookies in Fantasy Football. It is proven to have a higher accuracy than draft capital alone to predict fantasy football success. The SPS includes 13 to 17 metrics, with the exact number varying by the player’s position. All these metrics are pre-NFL, and some are invented by us, providing a complete analysis of a player’s analytical profile. The SPS gained widespread notoriety for its high accuracy, having made it on Barstool and The Pat McAfee Show. The SPS can be found here, and future projected SPS grades can be unlocked here.
Don’t just draft for this year. Gain the knowledge needed to position yourself to secure your future with SPS rookie data.
To ensure these trends weren’t just coincidental, we applied standard statistical testing. This analysis yielded a Pearson Value of 0.277. In the context of football analytics and fantasy projection, this value demonstrates a strong correlation between Speed Scores and future fantasy production. We are hoping for a minimum of 0.1, or an inverse correlation maximum of -0.1 when 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, QB draft capital prevailed a -0.219 Pearson value.
Finally, we looked at decadal differences to see if the modern NFL has shifted what they consider a “Big and Fast” Tight End. We compared the Top 10, the 11th–40th place finishers, and the Bottom 10 across the last two decades. This data reveals that while the trend is slightly lower in the most recent decade, it still showcased a significant trend.
| 2004-2013 | |||
| Top 10 | 11 through 40 | Bottom 10 | |
| All count | 53 | 125 | 42 |
| All 108 and above | 35 | 41 | 9 |
| % (Optimal Range/all) | 66.0% | 32.8% | 21.4% |
| 2014-2023 | |||
| Top 10 | 11 through 40 | Bottom 10 | |
| All count | 98 | 294 | 98 |
| All 108 and above | 55 | 96 | 21 |
| % (Optimal Range/all) | 56.1% | 32.7% | 21.4% |
With all this being said, Speed Score absolutely does matter. It successfully measures a Tight End’s ability to create mismatches while finding the heavy players who can run like a wide receiver. This can create a nightmare for linebackers and safeties and our data proves this translates directly to PPR points. When evaluating any specific player, look for them to hit our identified 108+ optimal range. If a prospect falls below our optimal range, history suggests they face a steeper uphill battle to becoming a weekly fantasy starter.
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 94 of “Does It Matter?” is an examination of Tight End Burst Scores: Do They Matter? If so, what’s the Burst Score 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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