Wednesday, July 31, 2019

2019 NFL Win Over/Under Total Predictions!!

Going Head to Head vs Vegas, Baby!!


The preseason begins TODAY and here is my totally numbers driven stab at providing baseline 2019 over/under wins projections for each NFL team. 

Here is a brief step by step overview of how the numbers were crunched:

  1. Take last year's Points For ("PF") and Points Against ("PA") totals for each team.
  2.  Use an actual 2018 Strength of Schedule ("SoS") list of your choice to find the correlation between it and each of the above.
  3. Based on this correlation, break out the portion of 2018 totals for each team into "Team Portion" which represents the amount of PF and PA generated by the team through their talent, coaching and scheme and the "SoS Portion" which represents the impact of the opposition's resistance.
  4. Apply a Rating Scale based on the distribution to give simple grades like in school (Top Team earns "100%" grade,  teams below the mean by more than 1 standard deviation earn "67%" or less).
  5. Conduct the same exercises for 1-4 above using the 2019 "SoS" projections of your choice.
  6. Find the difference between the Actual PF and PA Ratings and their corresponding projected values; this is your adjustment to the "SoS Portion" in #3 above.
  7. Add up your projected 2019 "SoS Portion" with the 2018 "Team Portion" (this is unadjusted for personnel or scheme philosophy changes that may have occurred over the off-season).
  8.  Find the difference between the PF and PA and divide by 16 games to give you the 2019 per game Margin of Victory.
  9. Divide the 2019 MoV by the 2018 MoV to get the change in 2019 games.

The table below shows the results

2018 Actual - Duh.

2019 Projected - Shows the win total using the method outlined above.  "+/-" represents the increase or decrease in wins projected for 2019 over 2018.

Vegas W - Shows the number for wins posted on www.oddsshark.com


Notes:

  • Obviously, there are no half wins but this projection is in line with the Vegas win over/under numbers below; the recap at the end of the season will round the numbers for comparison.
  • Denver moves up the most whole games from 6 to 9.5 (10).
  • Tennessee looks to fall off a cliff going from 9 wins to 2 in our analysis...dang. Looks like going from the 13th easiest schedule to the 4th most challenging could take its toll.
  • Bullish compared to Vegas: 
    • New Orleans +4 (14 vs 10 Vegas over/under)
    • LA Rams +4 (14 vs 10)
    • Miami +4 (8.5 vs 4.5)
    • Chicago +3.5 (12.5 vs. 9)
    • Houston +3.5 (11.5 vs 8)
    • LA Chargers +3 (13 vs 10)
  • Bearish compared to Vegas:
    • Tennessee -5.5 (2.0 vs 7.5 Vegas over/under)
    • San Francisco -3 (5 vs 8)
    • NY Jets -3 (4.5 vs 7.5)
    • Cleveland -2.5 (6.5 vs 9)
    • Green Bay -2 (7 vs. 9)
  • Based on the above, here are the Division placings:
    • AFC East:  NE, MIA, BUF, NYJ
    • AFC North:  BAL, PIT, CIN, CLE
    • AFC South:  Tie HOU and IND, JAX, TEN
    • AFC West:  Tie KC and LAC, DEN, OAK
    • NFC East:  PHI, DAL, WAS, NYG
    • NFC North: CHI, DET AND MIN (Tie), GB
    • NFC South: NO, CAR, ATL, TB
    • NFC West:  LAR, SEA, SF, ATL
The above exercise was fun but the outcome is not at all sensitized with all the factors that the oddsmakers layer into their projections.  But does that even matter?  We'll find out at the end of the 2019 NFL season when we recap our results. 
Don't forget to leave a comment.  

Happy NFL Day and have a great season (unless you are a Patriots fan)!

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Check out my analysis of the Wide Receivers from 2019 NFL draft based on Dominator Rating (DR) compared to my Efficiency finding ratio, ROI HERE.

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Friday, July 19, 2019

2020 NCAA Wide Receiver Draft Class Dominator Rating vs "ROI"

FBS Just Over One Month Away!!

Football action is around the corner and I wanted to follow up my "NFL Rookie Dominator Rating Vs Return on Investment" article with the same analytical peek at the upcoming FBS season comparing many of the top seniors and underclassmen likely to declare for the 2020 draft wide reciever class.

Briefly, Dominator Rating, or "DR" measures the average of a player’s percentage of team receiving yards and percentage of the team's receiving touchdowns. 
Return on Investment or "ROI" seeks to uncover just what the name implies...if I invest a passing target in getting the ball to a receiver, what kind of output in terms of production am I going to get from him?  

For more detail into each of the metrics we will discuss, please refer to the original article referenced above. 

DR vs ROI


The table below is organized as follows:
  • Player Name, Team and Class
    • "r" means redshirt
    • "T" means transfer
    • "MM" means player served a two year Morman mission
    • JUCO prefix indicates the number of years at his current school post JUCO
  • Height (inches), Weight (lbs) and Density (Dns) -Simple density calculated as Wt/Ht
  • DOM = Dominator Rating as detailed above. 
    • Score: Based upon the distribution of all sample scores based on an "A to D" grading system with 100% awarded to the top scorer and a 65% assigned to the score at the bottom of the range 1 standard deviation below the mean. 
  • DOM w/o RB = Dominator Rating excluding RB statistics (to provide an "apples to apples" comparison to ROI which eliminates those same stats).
    • THE TABLE BELOW IS SORTED BASED ON THIS METRIC.
  • ROI = Return on Investment is as detailed above. 
  • Diff = Difference between DOM w/o RB and ROI.
    • The lower the number the more parity between Dom w/o RB and ROI; the larger the more disparity.
  • Rec/TD = Number of receptions to generate 1 Touchdown




What's With All the Colors?  

The numbers in the table above are exclusive to their respective columns so a 25% score in one column is not the same as a 25% score in the others. Each metric was sorted independently based on the distribution:



Consensus -  The eye naturally lands on rows where the color and font are the same in all three categories, which indicates DR and ROI agree. Here are the favorable players who meet that standard.
  • Superior:  One name stands above all and that is Tulane's Darnell Mooney.  If you've never heard of him, that is the point of ROI, to screen out guys who may get lost in the draft hype machine.  While his numbers show he dominated and was the most efficient in FBS, film study is required to see if that was because his teammates were truly, truly below NFL level prospects or if he will back up his numbers with solid execution and mastery of fundamentals. 
  • Outstanding:  Louisana Tech's Adrian Hardy was a high school QB and you know I love receivers who were signal callers. His ratings were consistent across all three metrics so I will make sure I take the time to really check him out this coming season. 
  • Above Average:  MSU Bulldog Isaiah Zuber (formerly of  Kansas State), Kentucky's Lynn Bowden Jr. (former QB), Cornhusker JD Spielman (Minnesota Vikings GM Rick Spielman's son, so he has NFL access)  and college journeyman Kirk Merritt of Arkansas State are all bold yellow across the board.
Disparity - There can be a lot of variance between DR and ROI for an individual player.  To eliminate the noise, we will focus on two criteria to see who has the most divergent scores:
  1. In terms of DR w/o RB and ROI, the player has one above average (Blue, Green or Yellow Bold) and another below average (Yellow, Orange or Red) and
  2. There must be a difference of at least two grades between them.
DR Favorable/ROI Unfavorable






  1. Rice's Austin Trammell has a Dom w/o RB that is indicative of a late 1st round pick but his ROI is subpar based on the data.  He has come away with all-Conference USA hardware each of his first two years so we'll see what he can do in 2020.
  2. Jalen Reagor of Texas Christian  is a legacy player, his father having won a Super Bowl ring with the Colts.  He is showing Top 20 pick with his DR w/o RB but his ROI is two levels down which indicates he may have had over-distribution of targets last year. 
  3. Washington Huskie Aaron Fuller , the lone senior of this group, was the leading receiver for UW evidenced by his high DR w/o RB but his performance overall was distinct from the rest of the team but not in a positive way, as far as ROI efficiency is concerned. 
The three receivers above are special talents,  however the disparity between our metrics needs to be investigated with review of game video to see what is up. 

ROI Favorable/ DR Unfavorable






  1. Dezmon Patmon of Wazzu was third on the team in terms of receptions which resulted in a disappointing DR w/o RB however he led the team in receiving yards.  That helped put him near the top of our list in terms of ROI. It will be interesting to see if Mike Leach increases his targets given his superior efficiency. 
  2. Nick Westbrook of Indiana makes me wonder how a 1st team all-state receiver out of Florida...FLORIDA...decided to spend his college career at Indiana, a school not known for football.  His injury 2 years ago may have been a blessing in disguise, permitting him a redshirt senior year in 2019. I was a huge fan of his last few years and I know he will become one of the more talked about "sleeper" names in the 2020 draft process. 
  3. USC's Michael Pittman is, indeed, the junior of the former NFL Super Bowl ring wearing running back. No slouch in his own right,  Deuce certainly made use of his NFL access evidenced by an All American high school career.  His marginal DR  is driven by being 3rd on the team in receptions in 2018, his outstanding ROI by efficient production.  USC is loaded at WR with Vaughns and St. Brown (1st and 2nd in 2018 receptions) so we will see if Pittman can further distinguish himself. 
Receptions/Touchdown

Unlike DR, ROI does not take into consideration receiving touchdowns because there are many factors involved beyond the receiver's skill.  As an additional aid, it is helpful to check TD production through receptions/TDs.  



As you can see, the above-average REC/TD ratios have no correlation to DR w/o RB or ROI as it is independent of both metrics:
  • DR includes player's percentage of team touchdowns it can be misleading; Army had 7 passing TDs in 2018 with 4 going to Jordon Asberry for 57.1% of team touchdowns.  Couple that with his 21.0% share of team receiving yards and he's a late first round pick with a Dominator Rating of 39.1%.
  • Across the range from above average (Blue, Green and Bold Yellow) to below aveage (Flat Yellow, Orange and Red) the distribution in the table above resembles the protoypical bell curve. 
  • I believe a better way to evaluate TD contribution is apart from any reception/yardage measure by using the REC/TD ratio.
  • One observation that is interesting is many of the top "brand" name WRs in this coming draft go into 2019 with DR w/o RB and ROI hovering around average but boasting elite REC/TD ratios. 
    • It will be interesting to see how these players perform in the upcoming year to see if the productivity/efficiency numbers increase to the level of their TD generation.
    • It bears noting that Alabama's Jeudy (discussed as a possible WR1 this coming draft)  got the only Outstanding REC/TD ratio with a TD scored every 5.09 receptions. 

In Conclusion

While the numbers can be similar for a player across the three primary metrics we reviewed, Dominator Rating, Dominator Rating without Running Back stats and Return on Investment, it is critical to compare them exclusively within each data set.  Just as Dominator Rating is not infallible, neither is ROI.  In fact, ROI is best used as a screening tool to find players who may have been overlooked by the media draft machine; especially given how REC/TD and not Dominator Rating seems to be more line with the players receiving media buzz this pre-season.

Keep an eye on this space for updates all NCAA season long for FBS receiver ROI trends with periodic review of FCS, DII and DIII top ROI receivers.

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Wednesday, July 10, 2019

2019 NFL Draft Wide Receiver Review - Dominator Rating vs. "ROI"

NFL Action in Less than 1 Month!

NFL football kicks off August 1st when Denver takes on Atlanta in the first preseason game of 2019 and so it's a  great time to review some of the NFL's newest players selected in the Player Draft held this past April.  

This space focuses on receivers and so we will take the time to compare and contrast players drafted based on the following performance metrics:

Dominator Rating 

Dominator Rating, or "DR" measures the average of a player’s percentage of team receiving yards and percentage of team receiving touchdowns.  From online sources, this concept was brought to the internet mainstream by the guys at Rotoviz.com.  They admit the Dominator moniker is not a promise the player will dominate at the next level, but an apt description of how the player dominated his team's passing game.  A DR > 50% would suggest NFL superstar potential (top 10 draft pick) for a prospect, 40%-50% would suggest a player worthy of a top 20 pick, 35%-40% indicates late first round,early second, and so on.
In looking at evaluating receivers I felt such a measure would be great at isolating potential NFL prospects for further review...but something didn't feel right.  Just because a player was targeted more frequently, did that mean he was the best player on the field in the passing game?  Maybe he was the guy because he it was his turn as a senior or maybe the coach just liked him or maybe he had the hype going into the season and running the passing game through him would keep the team on the news. And there were rarely diamonds in the rough to uncover with DR...the players were widely know because they were at the top of the stats columns.  A guy could be responsible for 50% of his teams receiving yards and receiving TDs but maybe they were force feeding him and there were other, more efficient options available who were outside the limelight. But how would you find those guys?


Return on Investment

Return on Investment or "ROI" seeks to uncover just what the name implies...if I invest a passing target in getting the ball to a receiver, what kind of output in terms of production am I going to get from him?  Starting with the basic concept of the DR, the percentage of his team's receiving yards a player generates, ROI goes deeper,  comparing also the percentage of his team's receptions the receiver converts from his targets.  The player's Return on Investment is compared to other players and, unlike DR, the players are tiered based on distribution using standard deviation; therefore, there is no fixed ranking scale.  The number is absolute in that it tells us exactly how much more production a player generated from his opportunities compared to the average receiver. 
As an efficiency measure,  the impact of high volume receivers is eliminated because ROI is based on rates.  However, to weed out one dimensional deep threat players, only receivers with reception totals greater than 1 standard deviation below the mean are included (the "Sammy Coates rule").   
Unlike DR, this metric ignores touchdowns because there are many factors contributing to a score that may not be directly influenced by the receiver (play design, downfield blocks, blown coverages, etc).  Not that touchdowns are considered useless, as Reception to Touchdown ratio is also monitored in overall receiver evaluation.  

DR vs ROI

So let's compare receivers drafted in the 2019 NFL Player Draft based on these two measures.  First let's look at the top DR players (the numbers below exclude RB statistics which is a requirement for ROI).



Round = NFL Draft Round selected; Overall = Overall Pick. DR=Dominator Rating; ROI = Return on Investment


The players are ranked based on the distribution with the color code key, below:





The table above shows the top-ranked receivers by DR starting with Andy Isabella at 52.1% going to the bottom tier of the range of 30% (held by undrafted Terren Encalade of Tulane).

From the above, there were 32 FBS players in the 2019 draft with DRs > 30%.  

  1. Of those, 13 were drafted with an average draft position of 135.1 (40.6%).
  2.  Twelve were offered contracts as Undrafted Free Agents (37.5%).
  3.  Seven are still awaiting NFL opportunities (21.9%)
  • Isabella projects to be of superstar ilk, based on DR alone. 
  • Of course, many factors go into player selection, but when it came to mapping DR to draft position, Marquise Brown nailed it by going late 1st rounder with a DR of 35.2%.
  • Jamarius Way, who has good size at 6'3" 215 lbs was the highest DR player (39.1% for late 1st/early 2nd round consideration) to go undrafted, possibly hindered by a less than spectacular Combine and coming out of a small program.
  • Players who were consistent in terms of tier ranking for both DR and ROI are:
    •  Outstanding:  Hakeem Butler
    • Above Average: Antoine Wesley, Marquise Brown, Travis Fulgham, Marcus Green and Johnathan Boone. 



Now let's take a look at this from an ROI perspective:


Per the Sammie Coates Rule, the list above excludes players with less than 42 receptions, so some of your favorites may be missing. 


The table above shows the top-ranked receivers by ROI starting with Damion Willis (6'3" 204 lbs)  formerly of Troy who provided a return of 58.1% more production than expected based on his share of targets, receptions and yards. ROI considers all receivers greater than 1 deviation above the mean (compared to the 30% cutoff for DR)  so Marquise Brown rounds out the list with 15.1% ROI.

From the above, there were 25 FBS players in the 2019 draft with above-average or better ROI .  
  1. Of those, 11 were drafted with an average draft position of 147.2 (44%).
  2.  Eleven were offered contracts as Undrafted Free Agents (44%).
  3.  Three are still awaiting NFL opportunities (12%)
  • CIN also picked a high ROI and DR players in Tyler Boyd and Josh Malone so it's no surprise they went with Willis. 
  •  The highest ROI guy not on the DR list is Olabisi Johnson who was drafted in the 7th round.
  • Interestingly, the three who are not currently on teams qualified for both the DR and ROI recognition tiers (Campbell Jr, M. Williams and Boone) - maybe one will get a shot to latch on somewhere. 
  •  There are eight ROI players who did not make the DR list:
    • Drafted: Johnson (#247), Jennings Jr (#120) and Arcega-Whiteside (#57).
    • UDFA: Custis, Richardson, Poindexter (a poor man's Arcega-Whiteside given development), Ratliff-Williams and Murray.
  • Two of my personal favorite prospects, Miller and Butler, were the only two to generate Outstanding of better tier rankings for both DR and ROI. Looking forward to see if they show and prove this year. 

What's the Difference?




The table above shows the players who have at least a two tier difference between their DR and ROI that carries then over the mean.  There is nothing scientific about this table but it will be interesting to see who succeeds and who fails when it is all said and done.  The guys in orange background are favored by DR but below average in ROI while the opposite is true for green.




Conclusion

The point of this comparison is not to prove any metric "right" or "wrong" but to set a basis to track results that could lead to fine tuning both these metrics for better predictive results.  It will be a lot of fun comparing the two over the years and I hope you will come along for the ride.

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