Using Market Share Receptions to Project WR Efficiency

duzyu487hvid59acWhat’s more important in a game of football than efficiency? Probably nothing.

This post will be looking at the efficiency of the top 2014 WR prospects. To figure out how efficient each WR was with every reception he had, we’ll be using the following formula: DR/msREC. If you’re late to the party, DR stands for dominator rating, which is a rating based on the extent at which a WR accounted for his team’s receiving yards and receiving touchdowns. msREC is a WR’s receptions divided by the receptions his entire team had throughout the season.

Before we break down the numbers I think it is important to remember a few things:

– This statistic is far from a deciding factor that ranks the talent level of these WRs. Rather, it is a tool that may raise some negative questions about certain players, hint towards which WRs are undervalued, or solidify the assumptions we had of some of the players. Use these findings as more of a descriptive tool.

– Efficiency drops as usage increases. A player with 15% of his team’s receptions and a dominator rating of 27 is not automatically better than a player with 35% of his team’s receptions and a dominator rating of 40.

– A per reception efficiency score of 1 means a WR was just as efficient as the rest of his team. This is probably a bad sign since the average college player doesn’t get drafted.

No that we have that out of the way, let’s take a look at the per reception efficiency ratings of the same 136 WR sample size used in Shawn Siegele’s WR Holy Grail piece:

Rec Efficiency Score1.331.18

As made evident by the table, the hits were more efficient than the misses. The hits increased their DR by 1.33 with every msREC percentage earned, while the misses only increased their DR by 1.18 with every msREC percentage they earned. To put the .15 gap into perspective we’ll use the average msREC percentage of all WRs in the sample size (26.47) and plug in each efficiency rating. At the efficiency level of the hits with the average msREC number, they would post a DR of 35.2. At the efficiency level of the misses with the same msREC number, they would post a DR of 31.2. While the 4% difference isn’t a massive gap, the .15 efficiency difference is notable. With that being said, let’s take a look at the 2014 WR class.

Porspect%MS RecDRDR/msREC
Mike Davis2237.901.72
Alex Neutz2541.351.65
Kelvin Benjamin1929.301.54
Martavis Bryant1218.501.54
Mike Evans2030.201.51
Davante Adams2840.751.46
L'Damian Washington2028.501.43
Devin Street2636.851.42
Josh Huff2433.801.41
Donte Moncrief1925.251.33
Paul Richardson3546.251.32
Brandin Cooks3138.901.25
Brandon Coleman1518.551.24
Odell Beckham Jr.2935.051.21
Bruce Ellington2125.101.20
Cody Hoffman2731.501.17
Sammy Watkins3032.301.08
Jarvis Landry3840.051.05
Cody Latimer2627.401.05
Jordan Matthews4648.301.05
Jared Abbrederis3637.001.03
Allen Robinson4037.300.93
Marquise Lee2926.150.90


Mike Davis has a great PRE (per reception efficiency) score, but low usage is probably inflating his score a ton. The same can be said about many other prospects in this table as well.

Alex Neutz PRE score is really impressive and his msREC percentage is only 1.47 below the average of the 136 WR sample size mentioned earlier. If this list was to predict a sleeper he would be the one. Alex also has size on his side at 6’3 205. If anyone can find his date of birth PLEASE write me on twitter I cannot find it anywhere.

– Another test another walk in the park for Davante Adams. He’s the most efficient WR on this list with an above average msREC percentage.

Paul Richardson is a guy who should probably be valued a little higher. He fails the stature test by a wide margin, but his college production is one of the most impressive in the ’14 class.

Jordan Matthews‘ PRE score doesn’t bother me too much because his usage was massive, but I would have liked him to score in the 1.15 range.

Allen Robinson‘s usage was the second highest on the chart, but his PRE score is still terribly low. It’s something to keep in mind when picking between two close prospects when drafting or ranking.

– 29 WRs from the 136 player sample had a PRE score below 1.00, 26 of those players were misses. Marquise Lee had an injury filled season, not sure what excuse you can make for Robinson other than his red zone numbers took a nose dive.

– The top of the chart is dominated by guys with impressive red zone TD rates, while the bottom of the chart is full of guys with low red zone TD rates. This is probably because it is easier for WRs to improve their DR by catching TDs on a low number of receptions than it is for a player to boost their DR by gaining large amounts of yards through a low number of catches.

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