Every year dynasty fantasy owners are looking for a leg up in their rookie draft. Many owners are now big into using analytics, trying to find stats that reveal what player will be the next fantasy stud.





These past few months I have been gathering data and creating a database with an abundant amount of college stats for rookies in the 2020 NFL Draft. Most of the stats were scraped from ESPN and cfbstats but where I took it a step further was collecting my own data on targets and 1st downs. This was possible through the public use of play-by-play stats from ESPN and CBS Sports . It was a tedious process but has allowed me to take an innovative look at prospects and market shares.





Background





(skip "Background" if you're familiar with market shares)

Before getting too deep into market shares, for those who are newer to fantasy, what even are they? Market shares originated as an economic term and defined as "the portion of a market controlled by a particular company or product." With the Moneyball movement, market share made its way into sports. In football, market shares are the percentage of a team's stats a specific player produces by himself. So, our new definition for football would be, "the team stats controlled by a particular player." Stats commonly used for market shares are targets, receptions, yards, and TDs but can be used for basically any raw statistic teams have.





An easy example of market shares would be a team that has a total of 200 completed passes over a season. One of the receivers on that team had 50 receptions, so his market share of receptions would be 25%. Easy peasy right? Alright, let's take things a step further.

What happens if we combine market share metrics? That brings us to Dominator Rating. Originated from Frank DuPont and his book Game Plan, this metric is used for skill positions (RB, WR, TE) to exemplify their production with yards and TD market shares. For wide receivers and tight ends, this only involves their receiving aspect, very straightforward. For running backs, both rushing and receiving aspects are incorporated because running backs are involved with both.





As an example let's say a team amasses 3000 passing yards and 20 passing TDs over a season. The receiver/tight end is responsible for 1000 receiving yards and 10 receiving TDs. So, his market share of receiving yards would be 33.33% and his market share of receiving TDs would be 50%. We then average those two percentages and get a Dominator Rating of 41.67%, this would be considered an excellent score. Anywhere from 35% and above is considered a potential WR1, 20-35% is considered a mid-level talent/WR2, and below 20% is considered a red flag. For tight ends, the red flag mark is slightly lower at below 15%.





An easy example for a running back would be a team that racks up 3000 passing yards, 2000 rushing yards, 20 passing TDs, and 20 rushing TDs. The running back is responsible for 500 receiving yards, 1000 rushing yards, 2 receiving TDs, and 8 rushing TDs. The team stats for receiving and rushing are then added together to get total yards and total TDs. So, the running back is responsible for 1500 yards of the 5000 team total yards and 10 TDs of the 40 team total TDs. So, his market share of total yards would be 30% and his market share of total TDs would be 25%. Take the average of those percentages and we get his Dominator Rating of 27.5%, this would be considered a mid-level score. Any score over 40% is considered top tier and anything below 15% is considered a red flag.





Now that we understand market shares and Dominator Rating we can move on to the more advanced stats, never before done anywhere else... You could say they're out of this galaxy.





Complete Dominator Rating





As we know, Dominator Rating accounts for the production of yards and TDs but what about the forgotten stat, 1st downs? A stat that is not commonly found in the public but still quite important in the offensive game. The goal of an offense is to pick up yards to get a 1st down and those 1st downs lead to the ultimate goal of a TD. So, why do we track yards and TDs but not 1st downs? Although we don't see 1st down counted in fantasy football often, I theorize they can add necessary context for evaluating prospects. Herein lies the Complete Dominator Rating (CDR).





Complete Dominator Rating is Dominator Rating with the addition of market shares for 1st downs. Yards, TDs, and 1st downs each account for 1/3 of its weight. Here's how the top 10 scores turned out for 2020 prospects at each position for their final 2 seasons combined (only FBS):





WR

TE

RB





We can see the comparison of how each scored for their Complete Dominator Rating, Dominator Rating, yards, TDs, and 1st down-market shares. The first thing my eyes were drawn to from this was that Complete Dominator Rating tends to be lower than Dominator. This makes sense because the percentage for 1st downs on average is the lowest and TDs are the highest. This isn't necessarily a good or bad thing but it does bring an added balance to the Dominator Rating.

The standard deviation for these categories further shows the weight TDs hold with the highest variation. Complete Dominator reflects much similar to yards, which falls in the middle of the three variables. Dominator Rating has a tendency to get spiked up because of the weight TDs carry, especially when having such a lower sample size compared to yards and 1st downs.





If we take the average team total for each of the three variables from each drafted WR prospect 2010-2019 (310 prospects) we get the following; 3508 yards, 27 TDs, and 148 1st downs. That would mean for every 130 yards a player gains is equal in weight to 1 TD. That's basically double to the weight they hold in fantasy, where 130 yards is 13 points and 1 TD is 6. If we want to get close to that weight then that's where 1st downs fall, with roughly 5.5 1st downs being equal to 1 TD.





Does this mean fantasy score weights are wrong? Not necessarily, but I do feel this helps shine a light on why TDs have too much weight with the way that Dominator Rating fluctuates. The addition of 1st downs, by way of the Complete Dominator Rating, brings balance and adds further context.





Market Share Production Score





The next metric measures the market shares productivity for how often players get the ball in their hands, in addition to traditional market shares. Just looking at Dominator Rating we don't know this information. Market Share Production Score adds that value.





Market Share Production Score works similarly to Dominator Rating, for receivers/tight ends accounting for their influence in the receiving game, and for running backs, their influence with both receiving and rushing. The difference is receptions or touches is half of the weight, while the other half comes from Complete Dominator Rating or Dominator Rating (whichever is available, I account for both in my database). Simply put, the reception/touches share and CDR/DR are added together for a Market Share Production Score.





An easy example would be a receiver has a 30% reception market share and a 35% Dominator Rating, so their Market Share Production Score would be a 65. For running backs, simply use touches instead of receptions. Equations can be seen below:





WR/TE: (MSrec + DR) *100 = MSPS





RB: (MStch + DR) *100 = MSPS





Below shows how the top 10 scores turned out for 2020 prospects at each position for their final 2 seasons combined:





WR

TE

RB

Now we know how productive players are with the opportunities given but what about efficiency? That's where this last metric comes in.





Market Share Efficiency Score





This last metric takes the difference between the Dominator Rating and reception/touch market share. This shows whether they are plus or minus on how their Dominator Rating compares. The hypothesis behind this was that I figured Dominator Rating would be similar to the percentage they had for reception market share.





I looked at how WRs drafted between 2010-2019 compared to each other in their final season. On average, their reception market share was 25% whereas Dominator Rating was 30%. This would mean that Complete Dominator Rating would come even closer to reception market share and they did with the 2020 WR sample size I have (69 prospects). The average reception market share came to 18.2% whereas the average Complete Dominator Rating was 20%. This felt close enough for Market Share Efficiency Score to serve its purpose. Complete Dominator Rating is preferable for this but with only having that metric for 2020 prospects, I'll continue on here using just Dominator Rating.





If a receiver has a 35% Dominator Rating and a 30% reception market share, we subtract their reception market share from their Dominator Rating, and we get a Market Share Efficiency Score of +5.00. For running backs, we'd simply use touches instead of receptions. Equations can be seen below:





WR/TE: (DR - MSrec) *100 = MSES

RB: (DR - MStch) *100 = MSES





Below shows how the top 10 scores turned out for 2020 prospects at each position for their final 2 seasons combined:





WR

TE

RB

Conclusion





These three metrics work best when analyzed together, they help tell the story of a player in further depth. Complete Dominator Rating adds the context of 1st downs, Market Share Production Score exemplifies the volume of productivity, incorporating receptions/touches, and Market Share Efficiency Score shows how well players are producing with the receptions/touches provided. The story is still out on whether these metrics project prospects more than any other metrics though and I will continue further research into that. But at the very least these metrics add further context to the 2020 draft prospects.





Thanks for reading my first article with FFAstronauts and I look forward to bringing more fantasy and NFL Draft content!