So named for the backfield weapons it means to identify, Satellite Score is a metric that adjusts college receiving production (using target share) for total production (using Dominator Rating) to show which RBs were contextually the most involved as receivers in college.
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While the round a player was drafted in and the more volume-based target share statistic are better predictors of how much receiving volume a RB is likely to see in the NFL (as as a general rule of thumb, the best players are the most productive players, in both college and the NFL), Satellite Score is the best predictor of the portion of a RB's total NFL opportunities that targets will account for. The higher the Satellite Score, the higher degree to which receiving the ball projects to be an element of a player's NFL role. The r-squared values of the statistics that best correlate to targets as a percent of a player's total opportunities (targets + carries):
College target share is likely not as much a product of a player's receiving ability as we generally think; it is often more a product of their ability overall. If a RB is being fed the ball as the best player on his college team's offense, spoon vs. fork isn't an important distinction when the goal is simply to have him eat. He's likely going to receive a vast majority of the team's carries as well as a significant portion of the team's targets in the passing game. One prime example is the college production profile of Jay Ajayi.
Jay Ajayi had himself an absolute buffet during his last season at Boise State in 2014. Rushing for over 1,800 yards, catching 50 balls, and scoring 32 TDs, Ajayi posted a 90th-percentile 41.3% Dominator Rating and an 86th-percentile target share of 12.4%. He was the Boise State offense as one of the premier offensive weapons in the country, catching more balls as a RB that season than future first-round pick Breshad Perriman did at wideout. So why isn't Ajayi one of the premier versatile bellcow backs in the NFL, a 220 lb. receiving weapon in the mold of Le'Veon Bell, David Johnson, and DeMarco Murray? Injuries have played a part in Ajayi's maybe not reaching his ceiling in the league, but he boasts career receiving bests of just 27 receptions and 158 yards, while his career targets/opportunity rate of 13.3% is well below the league average of 22.8% (based on RBs drafted since 2007). Such a strong showing as a college receiver should have seen Ajayi translate that skillset into NFL production.
If you adjust Jay Ajayi's college target share for his total college production, though, you see that his receiving numbers were likely a function of his being the best player on his team and thereby being given the ball by any means necessary. Based on his 50th-percentile 30.0 Satellite Score, we should have expected Ajayi to be no more than an average producer as a receiver in the NFL. His 30.0 Score is actually lower than the 10-year average of 32.2, and, true to it, Ajayi has never been a significant contributor in the passing game.
In addition to identifying those high producers whose target shares betray more complete skill sets than the players actually possess, Satellite Score is capable of uncovering the low-Dominator Rating and low-target share backs who profile as good receivers in the NFL. Florida State's Chris Thompson was a 14th-percentile Dominator Rating and 28th-percentile target share producer in college. Despite far inferior college production to other satellite backs Theo Riddick, Giovani Bernard, and Nyheim Hines, Chris Thompson's 77th-percentile 41.2 Satellite Score showed that he was a player that should carve out a role as a receiver in the NFL. Six years into his career, he has done just that, with a 51.5% targets/opportunity rate that is more than double the league average.
The extremely low end of the Dominator Rating spectrum provides more difficulty in deciphering extreme (most problematically, extremely high) Satellite Scores. In the case of Spencer Ware, even a 39th-percentile target share mark was impressive enough in the face of an 11th-percentile Dominator Rating that they together produced a 92nd-percentile Satellite Score of 54.9, a comparable figure to those of players like Elijah McGuire and Alvin Kamara. Spencer Ware has been a serviceable receiver during his NFL career, but his Satellite Score suggests a player who specializes in catching the ball. In cases such as this, it's important to investigate a player's college production profile more completely, looking for both higher Dominator Rating seasons that are likely to produce higher-confidence Satellite Scores, as well as consistency in the player's year-over-year share of their team's targets.
Looking for something in the numbers to back up the feeling I couldn't shake about Penny's profile, I stumbled upon the thought of adjusting target share for Dominator Rating to give a more contextual idea of how much a player was involved in the passing game. Penny's lost rookie season didn't show us much about what he actually is as a player, and he could certainly yet show to be a good receiver in the NFL, but Satellite Score ended up being exactly what I was looking for: a metric that better predicted NFL receiving role than the statistics previously available.
Players on the opposite end of the spectrum are of course almost exclusively two-down grinders. Notable exceptions from the 10th-percentile range are Rashad Jennings, a player with several 30-reception seasons on his resumé, and Jerick McKinnon, whose low target share was due to his playing QB in college. Many of the players this low on the Satellite Score totem pole are simply bad players:
In the less severe ranges, there are some rules of thumb that are apparent to me from various types of scores. While a Satellite Score under 20 indicates a player is very unlikely to ever produce as a receiver in the NFL, below-average Scores in the 20's are often indicative of a prospect without great receiving ability who may still have the chance to become a passably effective receiving target in the NFL. Some players near that range highlighted here are good examples:
An above-average (greater than 32.2) Satellite Score indicates a player we can reasonably expect to contribute to his team's passing attack in the NFL, with confidence in that expectation of course increasing the higher the Score. This unfiltered selection of players with 30-something scores shows players at a variety of talent levels:
As Scores enter the mid-40's, we should expect players to employ pass-catching as one of their best attributes, but not necessarily as the signature aspect of their game. This sample of guys in that range is a good example:
Brian Spurlock -- USA Today Sports
While the round a player was drafted in and the more volume-based target share statistic are better predictors of how much receiving volume a RB is likely to see in the NFL (as as a general rule of thumb, the best players are the most productive players, in both college and the NFL), Satellite Score is the best predictor of the portion of a RB's total NFL opportunities that targets will account for. The higher the Satellite Score, the higher degree to which receiving the ball projects to be an element of a player's NFL role. The r-squared values of the statistics that best correlate to targets as a percent of a player's total opportunities (targets + carries):
College target share is likely not as much a product of a player's receiving ability as we generally think; it is often more a product of their ability overall. If a RB is being fed the ball as the best player on his college team's offense, spoon vs. fork isn't an important distinction when the goal is simply to have him eat. He's likely going to receive a vast majority of the team's carries as well as a significant portion of the team's targets in the passing game. One prime example is the college production profile of Jay Ajayi.
Jay Ajayi had himself an absolute buffet during his last season at Boise State in 2014. Rushing for over 1,800 yards, catching 50 balls, and scoring 32 TDs, Ajayi posted a 90th-percentile 41.3% Dominator Rating and an 86th-percentile target share of 12.4%. He was the Boise State offense as one of the premier offensive weapons in the country, catching more balls as a RB that season than future first-round pick Breshad Perriman did at wideout. So why isn't Ajayi one of the premier versatile bellcow backs in the NFL, a 220 lb. receiving weapon in the mold of Le'Veon Bell, David Johnson, and DeMarco Murray? Injuries have played a part in Ajayi's maybe not reaching his ceiling in the league, but he boasts career receiving bests of just 27 receptions and 158 yards, while his career targets/opportunity rate of 13.3% is well below the league average of 22.8% (based on RBs drafted since 2007). Such a strong showing as a college receiver should have seen Ajayi translate that skillset into NFL production.
If you adjust Jay Ajayi's college target share for his total college production, though, you see that his receiving numbers were likely a function of his being the best player on his team and thereby being given the ball by any means necessary. Based on his 50th-percentile 30.0 Satellite Score, we should have expected Ajayi to be no more than an average producer as a receiver in the NFL. His 30.0 Score is actually lower than the 10-year average of 32.2, and, true to it, Ajayi has never been a significant contributor in the passing game.
In addition to identifying those high producers whose target shares betray more complete skill sets than the players actually possess, Satellite Score is capable of uncovering the low-Dominator Rating and low-target share backs who profile as good receivers in the NFL. Florida State's Chris Thompson was a 14th-percentile Dominator Rating and 28th-percentile target share producer in college. Despite far inferior college production to other satellite backs Theo Riddick, Giovani Bernard, and Nyheim Hines, Chris Thompson's 77th-percentile 41.2 Satellite Score showed that he was a player that should carve out a role as a receiver in the NFL. Six years into his career, he has done just that, with a 51.5% targets/opportunity rate that is more than double the league average.
Limitations
Satellite Score is not without its deficiencies as a metric. On each extreme of Dominator Rating, the adjustment of receiving involvement to total production can produce Satellite Scores that may be deceiving. Christian McCaffrey's 98th-percentile 50.7% Dominator Rating was so high that even his 95th-percentile 16.7% target share produced a 32.9 Satellite Score that is just above the 10-year average. Matt Forte's 57.1% Dominator Rating had an even more drastic effect on his Satellite Score despite a 92nd-percentile target share number: his 25.1 is in the 32nd-percentile of Satellite Scores. In cases such as these, common sense and a holistic view of the player's profile is necessary. 4 straight 20+ reception seasons in college told you that Matt Forte profiled as a good receiver in the NFL, and everything else about Christian McCaffrey's profile so obviously screamed that he would be an elite receiver out of the backfield that taking a Satellite Score warped by insane production as an indictment of his NFL potential would have been obtuse.
The extremely low end of the Dominator Rating spectrum provides more difficulty in deciphering extreme (most problematically, extremely high) Satellite Scores. In the case of Spencer Ware, even a 39th-percentile target share mark was impressive enough in the face of an 11th-percentile Dominator Rating that they together produced a 92nd-percentile Satellite Score of 54.9, a comparable figure to those of players like Elijah McGuire and Alvin Kamara. Spencer Ware has been a serviceable receiver during his NFL career, but his Satellite Score suggests a player who specializes in catching the ball. In cases such as this, it's important to investigate a player's college production profile more completely, looking for both higher Dominator Rating seasons that are likely to produce higher-confidence Satellite Scores, as well as consistency in the player's year-over-year share of their team's targets.
Creation
The inspiration for Satellite Score was a problem I encountered in my evaluation of Rashaad Penny in 2018. Similar to the Jay Ajayi example laid out earlier, the case of Penny was of an incredibly dominant college RB with an upper-percentile share of his team's passing targets. Despite these metrics staring me in the face telling me that Penny was a complete, 3-down back, nothing else about Penny's profile suggested to me that he was a player I should actually expect to be a significant receiving threat in the NFL. He was big and had straight-line speed with not much quickness, and while I don't like to rely on the eye test for my prospect evaluations, I didn't see as much "wiggle" to Penny's game as you would typically expect good NFL receiving backs to have.
Looking for something in the numbers to back up the feeling I couldn't shake about Penny's profile, I stumbled upon the thought of adjusting target share for Dominator Rating to give a more contextual idea of how much a player was involved in the passing game. Penny's lost rookie season didn't show us much about what he actually is as a player, and he could certainly yet show to be a good receiver in the NFL, but Satellite Score ended up being exactly what I was looking for: a metric that better predicted NFL receiving role than the statistics previously available.
Using Satellite Score
Other than the warnings I've already outlined about the extremes of Dominator Rating and how it influences Satellite Score, I'll provide some general interpretations I have about what a given Satellite Score means for a player's NFL potential. Almost without exception, the uppermost-percentile Satellite Score players end up with roles in the NFL that showcase their receiving ability. A player with a Satellite Score in the 95th-percentile (at least a 60.0) is an excellent receiver:
Players on the opposite end of the spectrum are of course almost exclusively two-down grinders. Notable exceptions from the 10th-percentile range are Rashad Jennings, a player with several 30-reception seasons on his resumé, and Jerick McKinnon, whose low target share was due to his playing QB in college. Many of the players this low on the Satellite Score totem pole are simply bad players:
In the less severe ranges, there are some rules of thumb that are apparent to me from various types of scores. While a Satellite Score under 20 indicates a player is very unlikely to ever produce as a receiver in the NFL, below-average Scores in the 20's are often indicative of a prospect without great receiving ability who may still have the chance to become a passably effective receiving target in the NFL. Some players near that range highlighted here are good examples:
An above-average (greater than 32.2) Satellite Score indicates a player we can reasonably expect to contribute to his team's passing attack in the NFL, with confidence in that expectation of course increasing the higher the Score. This unfiltered selection of players with 30-something scores shows players at a variety of talent levels:
As Scores enter the mid-40's, we should expect players to employ pass-catching as one of their best attributes, but not necessarily as the signature aspect of their game. This sample of guys in that range is a good example:
In Conclusion
Satellite Score is a metric I've developed in an effort to better understand the skillsets and predict the NFL roles of RB prospects. Armed with greater context and coupled with a holistic view of player profiles, Satellite Score can be effectively wielded in our mission to quantitatively evaluate prospects by measuring rather than describing who they are as players. Its counterpart is Power Score, a physical/athletic-based metric I've developed that seeks to better identify RB prospects who profile as high-volume rushers. Power Score will be introduced in an upcoming article.
Dominator Rating and target share data either manually calculated or referenced from playerprofiler.com.
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