# "weighted Points Created" for Football

I took a peak down the football “Wins Above Replacement” rabbit hole recently and, although I’ve never been much for fantasy football (at least, not as it’s generally played today), I wondered if there couldn’t be a ‘better’- dare I say “more ottoneu”- method to scoring fantasy football.

The challenges with creating a football “WAR” (or a similar, all-encompassing advanced metric, such as one that could be used for fantasy purposes) are many. Without delving into all that here, my thinking instead is to translate and scale different measures for fantasy football outputs into what we already know to be an incredibly perfect measure: the ottoneu fantasy baseball offensive formula (which, of course, is built from weighted Runs Created (wRC)). The idea is to effectively create a “wRC” for fantasy football… or, what I’ll call a ‘weighted Points Created’ measure.

Because of the game’s statistical complexity, all offensive and defensive stats will be valued within the same “wRC” translation; that is, there won’t be a separate formula for offensive and defensive scores. Instead, the goal here is to translate our baseball stat ‘categories’ from the ottoneu formula into football stat ‘categories’. From there, we can balance the two translations with a relationship factor between how many occurrences occur for each football stat versus baseball stat in each category. After that, we set a weighting for each football stat within a category by multiplying the ‘balance factor’ between sports by the weighted measure from the baseball formula.

One important note: there is no measure that factors offensive touchdowns of any kind- passing, rushing, or receiving (although there are measures for Defensive and Return TD’s). As with wRC, where “Runs” aren’t factored but instead predicted, the same is true here- where offensive scores aren’t factored, but are (hopefully) predicted. The philosophical comparison is that baseball isn’t a game of R’s, but a game of Outs, and avoiding enough Outs will eventually score R’s (and securing Outs efficiently will prevent them); likewise, the point of football isn’t to score, but rather to move the chains toward a fresh set of downs (or to prevent first downs defensively), and in doing so eventually the offense will score naturally. This is important to remember as I work through the figuring of each statistical category’s relative translation between baseball and football.

As a further side note, I like to see H2H scores that reflect actual “real-life” scores; which is to say, I’m dividing the ottoneu Hitting formula by 10 as it relates to the “balance factor” between the two sports. For example, instead of a -1 AB value, I prefer -0.1. The idea is that each player’s score will reflect his actual football/game points value, based on the stats and weights assigned to them, with each team’s score better reflecting the sort of score you’d see in an actual NFL game.

Another aside, I’m using categories that are available on Yahoo’s platform as that is arguably the most customizable game engine. Whether these stats (or better stats) are available with ottoneu’s service, I wouldn’t know.

Also, although it’s a little late to start a league I’d be remiss if I didn’t invite anyone who would like to join the one I’ve set up on Yahoo to test this format. You can follow the league here; or join with this link. The league is free and set for 12 Teams with an Auction Draft scheduled on TUE, 9/11 @ 8:15pm ET (estimated draft time is ~2 hrs). Scoring will start on Week 2, with a 12-Week regular season and Playoffs starting on Week 14-16. I’ll also create a Divisional schedule once the league is full, just for fun.

With all that said, let’s dive in…

ROSTERS
I argue that the purpose- or goal- of fantasy sports is (or should be) to intuitively build a complete team that is reflective of ‘real life’ with ‘realistic’ scores. The first step to accomplishing this goal is with Roster settings. For this reason, I’m keeping “Kickers” and “Team Defense/Spec. Teams” as part of the setup, while also having roster spots for individual defensive players. The full roster categories are:
Offense - QB, RB, TE, WRx2, WR/TE, WR/RB, WR/RB/TE, K
Defense - DT, DE, LB, CB, S, DB, Dx2, DEF
(“D” as a ‘UTIL’-type spot for any defensive player)

So that’s 9 “players” on both sides of the ball. I’m not sure if the number of Bench/IR slots really matter here (at least not to the extent as they do in a H2H baseball format), so I’m only concerned with a balanced Active roster design.

SCORING
The fun stuff. I’ve added a philosophical explanation for the inclusion of the football stats for each formula category. The mathematical computations are made using 2017 stats only; I’m sure the differences year-to-year would change some of the balance factors somewhat, but I’m not sure to what degree it really matters. In any case, I wasn’t going to go deeper than last year as I’m offering this mainly as a proof of concept.
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AB, -0.1 (baseball)
Football equivalents: Pass Attempt, Rush Attempt, Passer Sack, Passer Interception, Incomplete Pass, Fumbles, and Fumbles Lost

Philosophically, AB’s are the impetus for every play- as are Passing and Rushing Attempts in football. That is, no play happens without one of these occurring (ignoring the AB vs PA factor here). In football terms, every play takes time off the clock and moves the game closer to an end- thus the negative values. The Passer Sack, Passer Interception, Incomplete Pass, Fumbles, and Fumbles Lost stats further reflect unsuccessful offensive plays which work to undermine the team’s chances to score points before the end of the game.

Mathematically, there were 165,567 AB’s in the MLB last year. To make the balance translation, all of the occurrences in the categories above are added up, which equals 40,250 PassATT + RushATT + PassSACK + PassINT + INCpass + FUM + FumLOSS. The balance factor is then 40250 / 165567 = 0.243. The final step is to multiply the baseball weighting by the balance factor; so in this case, 0.243 * -0.1 = -0.024. The weighting, then, for the seven football categories here is “-0.024”.
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H’s, 0.56 (baseball)
Football equivalents: Receptions, Completed Pass, Pass Defended, Tackles Solo, and Tackles Assisted

Philosophically, H’s are the basic measure for a Hitter’s success. Likewise, these are the basic category measures for offensive and defensive success.

Mathematically, there were 42,215 H’s in the MLB last year. In the NFL, there were 55,982 occurrences of the above categories. The balance factor is then 42215 / 55982 = 0.754. Multiplied by the weighting factor, 0.754 * 0.56 = 0.422. So the “weighted Points Created” factor for these five football categories is “0.422”.
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2B’s, 0.29 (baseball)
Football equivalents: Receiving Yards, Defensive Sack, Tackle for Loss, and Fumbles Forced

Philosophically, these are all an additional ‘degree’ of offensive and defensive success. They describe events that either move the ball “more” forward (offensively) or backward (defensively).

Mathematically, there were 8,397 2B’s in the MLB last year. The NFL saw 119,034 occurrences of the stats above. 8397 / 119034 = 0.071 balance factor, * 0.29 = 0.020. So these four football categories here have a “0.020” weighting. In Yahoo, this translates to a “48.88 Yards = 1 Point” for the Rec YDS category.
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3B’s, 0.57 (baseball)
Football equivalents: Receiving 1st Down, Defensive Fumble Recovered, Defensive Interception, Blocked Kick, 3 & Outs Forced (team stat), 4th Down Stops (team stat)

Philosophically, these are all plays that describe a further ‘degree’ of success. They describe events that either move the chains (for receivers) or turn the ball over (for defense). Two of the three team stats that are being counted in the formula are in this category.

Mathematically, there were 795 3B’s in the MLB in 2017; in the NFL, there were 8,314 plays for the football categories above. 795/8314 = 0.096 *0.57 = 0.055 weighting for the football stats in this category.
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HR’s, 0.94 (baseball)
Football equivalents: Passing 1st Down, Rushing 1st Down, Defensive TD, Safety, Kickoff+Punt Return TD (team stat)

Philosophically, as with HR’s, these are all the “best possible” plays for both sides of the ball. As I detailed above, the goal of the offense is to establish 1st Downs (with all plays starting as either a Pass or Rush play), while any scoring play on defense and special teams is the ultimate reward there. The KO/PR TD stat is the third of three team stats factored in this exercise.

Mathematically, there were 6,105 HR’s last year; in football, the number of plays above totaled 8,955. So 6105/8955 = 0.6817 * 0.94= 0.641 weighting for the five football stats here.
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BB+HBP, 0.3 (baseball)
Football equivalents: Pass Yards, Rush Yards, Return Yards, Turn-Over Return Yards

Philosophically, these are all describing the degree to which the player who starts the play (offense) or ends the play (defense) moves the ball in their direction.

Mathematically, there were 17,592 BB’s+HBP’s for Hitters last season, and 210,127 occurrences of the above football stats. 17592/210127 = 0.084 * 0.3 = 0.025 weighting. As all of these describe Yardage, the translation is 39.81 Yards = 1 Point for these four football stats.
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SB, 0.19 (baseball)

Philosophically, the SB/CS dynamic is being used here to describe all Point-After attempts; as the MLB average for SB% tracks relatively closely to the success percentage of all PAT attempts, this makes for a logical plug-in for football.

Mathematically, there were 2,527 SB’s last season and 1,967 successful PAT’s last season. 1967/2527 = 0.778 * 0.19 = 0.148 weighting for these PAT categories.
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CS, -0.28 (baseball)
Football equivalents: FG Missed, Extra Point Missed

Philosophically, these balance out the successful PAT categories above (excluding unsuccessful 2-Pt Conv’s).

Mathematically, there were 937 CS and 229 missed PAT’s last year. 229/937 = 0.244 balance factor * -0.28 = -0.068 is the factor to score these football stats.
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FULL “weighted Points Created” FACTOR LIST

“AB Category”
Offense = Points
PassATT = -0.024
RushATT = -0.024
PassSACK = -0.024
PassINT = -0.024
INCPass = -0.024
FUMB = -0.024
FumLOSS = -0.024

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“H Category”
Offense = Points
REC = 0.422
CompPASS = 0.422

Defense = Points
PassDEF = 0.422
TackSOLO = 0.422
TackASST = 0.422

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“2B Category”
Offense = Points
RecYDS = 48.88 YDS = 1 Pt

Defense = Points
SACK = 0.020
TackLOSS = 0.020
FumFORCED = 0.020

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“3B Category”
Offense = Points
REC1stDown = 0.055

Defense = Points
FumREC = 0.055
INT = 0.055
BlocKICK = 0.055
3&OForced(TEAM) = 0.055
4thDownSTP(TEAM) = 0.055

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“HR Category”
Offense = Points
PASS1stDown = 0.641
RUSH1stDown = 0.641

Defense = Points
DefTD = 0.641
SAFETY = 0.641
KO+PRTD = 0.641

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“BB+HBP Category”
Offense = Points
PassYDS = 39.81 YDS = 1 Pt
RushYDS = 39.81 YDS = 1 Pt
ReturnYDS = 39.81 YDS = 1 Pt

Defense = Points
TORetYDS = 39.81 YDS = 1 Pt

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“SB Category”
PAT Attempts = Points
2PTConv = 0.148

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“CS Category”
PAT Attempts = Points
FGMissed = -0.068
XPMissed = -0.068

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You can check-out the player pool for my Yahoo league linked above here (sorted by Offense and 2017 stats). Some positional comparisons:

QB
#5 B. Roethlisberger, 376.82
#15 J. Goff, 319.41
#25 J. McCown, 268.47

RB
#1 L. Bell, 123.01
#5 M. Gordon III, 93.52
#25 J. Ajayi, 56.04

WR
#1 A. Brown, 79.50
#5 L. Fitzgerald, 74.94
#25 D. Amendola, 48.45
#50 A. Cooper, 37.67

TE
#1 T. Kelce, 61.05
#5 J. Doyle, 50.49
#15 A. Hooper, 33.27
#25 D. Njoku, 22.76

LB
#1 B. Martinez, 64.62
#5 P. Brown, 62.17
#25 R. Shazier, 42.70
#50 T. Davis, 34.70

DB
#1 A. Jackson, 61.76
#5 L. Collins, 48.08
#25 D. Slay, 38.64
#50 T. Jefferson, 34.83

DL
#1 K. Mack, 34.77
#5 C. Campbell, 31.12
#15 A. Robinson, 25.86
#25 B. Graham, 22.31

K
#1 W. Lutz, 12.42
#5 C. Boswell, 10.74
#15 B. Walsh, 7.97
#25 A. Rosas, 6.21

TEAM (2 Def Cat’s + 1 Spc Tm Cat)
#1 Baltimore, 4.47
#5 Denver, 3.96
#15 New Orleans, 3.17
#25 Miami, 2.59

Naturally, QB’s by far have the most influence on “points created” with both the remaining offensive and defensive player pools relatively balanced between each other at some factor less than QB’s, and K’s and Team Defenses/Special Teams having the least weighted influence- though still enough to perhaps affect the outcome of any match. Or in other words, about what you’d expect from each roster component in terms of their overall impact on the game if you were building a more complete team.

Anyway, just throwing it out there- but I think establishing a more unique and intuitive method for scoring fantasy football would be the “ottoneu way” to further distinguish the service as an innovator within the field. As people continue to struggle to find an adequate football version of WAR, I propose we could do just that here for fantasy purposes by working from the wRC baseball formula that ottoneu was built around.

In any case, I’m now looking forward to this fantasy football season for the first time in like 15 years or so, if only just to see how this format could play out…

This is really interesting, thoughtful stuff. I’ll share it on Twitter. I have some thoughts, but I would like to see what other people think first.

Thanks for writing this up, @ballnglove82

1 Like

I agree, this is interesting. I think you have a major issue though because in baseball every extra base hit counts as a AB, H, and then the extra base hit bonus. In your set-up a 2b is worth less than a BB and a H is almost the same value as a 3B. You’ll need to add the H value into the extra base hit scores or do something to rectify that difference.

I’m sure I’ll have some other thoughts after I ponder it more, but my first question is why are ‘passing’ and ‘rushing’ stats scored the same and ‘receiving’ stats scored differently.
And return yards are really heavily weighted, which doesn’t seem to fit to me. Return yards are a completely different situation than a play from scrimmage.

I’ll have to ponder the bigger picture of using wrc from baseball to convert directly get to football points a little more.

I did that write-up on not much sleep and caught a math error this morning; the “AB” category was multiplied by -1 instead of -0.1, so that adjusts the QB and RB values. I edited the post to reflect this.

Each play starts as either a Passing or Rushing play; no play actually starts as a Receiving play. Receiving is a secondary result of a Passing play, and as such it has a lesser impact. In other words, to paraphrase Keyshawn, someone’s got to give him the damn ball before a WR can be a factor…

This is one thing that seems to be a hang-up in the efforts to create a football “WAR”; people are factoring RB’s and WR’s in the same “skill position” realm, when really everything should be factored as either ‘Rush’ or ‘Pass’ with everything else (e.g., Receiving) following that.

I would say that the purpose of grouping these football stats together within each baseball category isn’t meant to compare each football play against other football plays, but rather to fit a “success narrative” around each football stat relative to it’s equivalently weighted baseball category. That is the goal of wRC, afterall: to quantify a narrative to predict how many Runs a player’s production is worth. Likewise, the idea here is to predict how many Points each stat is worth.

The narrative for the “BB+HBP” category is that all of these Yards move the ball closer towards a score- sort of like a BB or HBP moves a Hitter to a base without factoring the Hitter’s actual skillset (other than his “eye”). Whether it’s from scrimmage as part of a multi-play drive or a one-shot return play, the only purpose of the category is to quantify the movement of the ball on the field.

Now a play from scrimmage will have a much larger value than a return play because of the combination of factors. For example, a guy will have a 40 Yard Kickoff return and earn 1 point and that’s it- sort of like saying that returning the ball 40 Yards is worth 1/6th of a TD. Comparatively, another player will Rush for 40 Yds (+1 pt) on 10 Att’s (10*-0.024) with a pair of Rushing 1st Down’s (0.641*2) which = 2.042 points, or twice as impactful as that 40-Yd Return play.

There are combination factors at play here, too. The thing, though, is that football is a much more complicated game to score than baseball. In baseball, everyone on offense performs the same duties; obviously, the same can’t be said for football. That’s why there are so many football stats within each singular baseball wRC category.

Which is to say that you’re going to have factors that stand alone as well those which build on each-other because each stat describes a different part of the same or different plays made by the same or different players on the field. So rather than draw that direct comparison between sports as you’re illustrating here, I instead looked to define each stat’s “success narrative” which could then be plugged-in to the “degrees” of the weighted wRC formula. That’s the purpose of the “balance factor”, which creates a fractional representation of the the occurrences for each category within each sport before multiplying by the category weight.

The goal here isn’t to compare baseball to football really, or even to compare football to football, but to translate an already effective ‘score predictability’ model between sports by weighting the comparative “success narrative” for each stat. So, don’t look at it as a direct application of the wRC formula into football, but rather as a comparative translation of the wRC’s degrees of success into a narrative for each football play.

I’m not sure how much sense I made above so I’ll try another way to paint this…

wRC, as a summation of each of it’s components, weights events within the baseball universe as a way to describe scoring predictability. When translating the measure into football, each category must be balanced relative to the number of occurrences within it- or, all of the plays in the football universe have to be balanced to the plays in the baseball universe.

For example, there were almost 12 times as many Pass/Rush/Return/TOReturn Yards last year as there were BB+HBP; in order to translate that category into football, the weighting of 0.3 needs to be multiplied by the fractional representation of that occurrence relationship. This is why the actual multipliers I’m suggesting for each category look so different than they are with baseball, relative to each other. That’s the difference in the comparison between universes (using my ‘success narratives’).

Which is to say, you don’t need to have the same difference in weights for each category between the two sports/formulas in order to maintain the same weighting relationship within the scoring predictability model. The key is in the translation between universes.

To clarify the “success narratives” and “occurrence balance translations” (using 2017 stats for the ocurrence/balance factor):

AB (-1, or -0.1) : Pass Attempt, Rush Attempt, Passer Sack, Passer Interception, Incomplete Pass, Fumbles, and Fumbles Lost (-0.243, or -0.024 weight translation); 0.243 occurrence balance factor
Narrative - things that start a play (AB and PassATT, RushATT) and describe unsuccessful offensive attempts (like an AB without a BB or H).

H (5.6, or 0.56) : Receptions, Completed Pass, Pass Defended, Tackles Solo, and Tackles Assisted (4.223, or 0.422 weight translation); 0.754 occurrence balance factor
Narrative - basic measures for offensive and defensive success

2B (2.9, or 0.29) : Receiving Yards, Defensive Sack, Tackle for Loss, and Fumbles Forced (0.205, or 0.020 weight translation; 4.89 or 48.88 Rec YDS = 1 pt, depending on your decimal preference); 0.071 occurrence balance factor
Narrative - events that describe an additional degree of success for both offense and defense (moving the ball ‘more’ forward/backward)

3B (5.7, or 0.57) : Receiving 1st Down, Defensive Fumble Recovered, Defensive Interception, Blocked Kick, 3 & Outs Forced-TEAM, 4th Down Stops-TEAM (0.545, or 0.055 weight translation); 0.096 occurrence balance factor
Narrative - events that describe a further level of success for offense (moving the chains, receivers) and defense (turnovers)

HR (9.4, or 0.94) : Passing 1st Down, Rushing 1st Down, Defensive TD, Safety, Kickoff+Punt Return TD-TEAM (6.408, or 0.641 weight translation); 0.682 occurrence balance factor
Narrative - the ‘best possible’ successful events that could happen for either offense (moving the chains, passers/rushers) and defense (scoring plays)

BB+HBP (3, or 0.3) : Pass Yards, Rush Yards, Return Yards, Turn Over Return Yards (0.251, or 0.025 weight translation; 3.98 or 39.81 YDS = 1 pt, depending on your decimal preference); 0.084 occurrence balance factor
Narrative - quantifies how much players that start a play (offense) or end a play (defense) move the ball in their positive direction

SB (1.9, or 0.19) : FG Made, 2 Point Conversions, Extra Point Made (2.441, or 0.244 weight translation); 0.778 occurrence balance factor
Narrative - like ‘stealing’ an extra point or FG after the offense did all the work

CS (-2.8, or -0.28) : FG Missed, Extra Point Missed (-0.684, or -0.068 weight translation); 0.244 occurrence balance factor
Narrative - getting ‘caught’ trying to ‘steal’ the cheap points; SB% is similar to all FG and PAT percentages, and it gives Kickers their own ‘section’ in the formula

"Upon Further Review"

Relative to the original post, I made some adjustments to the Roster and Scoring settings in the fantasy league that I linked to above.

I did a 10-year study on all the football and baseball occurrences for each scored statistic to use in weighting each category’s points value. I also moved some of the scoring categories to different “success narrative” categories and adjusted the Roster positions to better account for the points distribution of the overall player pool.

And upon even further review, after putting together the 10-year study (but factored after our league’s draft), I’ll be using a slightly different take on this idea (which I am posting as a separate thread) next year.

But to put a bow on this one…

Roster Positions
These are the final settings for rosters:
Offense - QB, WRx3, RBx3, TE, WR/RB/TE, K
Defense - DT, DE, LBx3, CB, S, DB, D, Team DEF/ST
Bench - 5 slots (encourages more FA/Waiver action)

Scoring
Relative to the original post, I’ve moved “Team Defensive 3&Outs Forced” and “Team Defensive 4th Down Stops” to the “HR” narrative category, and I changed “Blocked Kicks” from an individual stat to a Team stat and moved that to the “HR” category as well.

I also decided to figure a “Difficulty” balance for Kickers relative to the FG make/miss ranges (more below). These adjustments raised the points value of both K’s and Team DEF/ST (now with four team-influenced “HR”-weighted categories) to a level where they could now be a factor in any matchup.

Current Fantasy League’s Scoring
Based on the 10-year study for both sports, I made the following points adjustments in the current league (for Extra Points, I only used a 3-year study to account for the rule change on PAT ball placement).

One important note: I could not find accurate statistics for every category. Where possible, I defaulted to Yahoo’s stats and averaged-out for any years that were unaccounted for. Ultimately, as each category is a “basket” of stats that are then weighted to baseball’s occurrences, and as the vast majority of stats that can be found are accurate, I didn’t consider any estimates to be major factors on the formula as a whole.

• “AB” Success Narrative (-0.1 or -1)
Things that start a play or describe an unsuccessful Offensive play
Categories: Passes Attempted, Rushes Attempted, Incomplete Passes, Interceptions Thrown, Passer Sacks, Fumbles, Fumbles Lost

• 10-Yr BASEBALL occurrences: 1,657,173
• 10-Yr FOOTBALL occurrences: 406,176
• ‘Fantasy Universe Balance Ratio’: 0.245 (406176/ 1657173)
• Fantasy Football Category Scoring Weights: -0.0245 or -0.245 (0.245 * -0.1 or -1)
• “H” Success Narrative (0.56 or 5.6)
Basic measures for Offensive and Defensive success
Categories: Completed Passes, Receptions, Passes Defended, Tackles Solo, Tackles Assisted

• 10-Yr BASEBALL occurrences: 424,665
• 10-Yr FOOTBALL occurrences: 581,827
• ‘Fantasy Universe Balance Ratio’: 0.7299 (424665/ 581827)
• Fantasy Football Category Scoring Weights: 0.4087 or 4.087 (0.7299 * 0.56 or 5.6)
• “2B” Success Narrative (0.29 or 2.9)
Plays that describe an additional degree of Offensive and Defensive success
Categories: Receiving Yards, Tackle for Loss, Defensive Sack, Fumbles Forced

• 10-Yr BASEBALL occurrences: 84,150
• 10-Yr FOOTBALL occurrences: 1,214,160
• ‘Fantasy Universe Balance Ratio’: 0.0693 (84150/ 1214160)
• Fantasy Football Category Scoring Weights: 0.02 or 0.2 (0.0693 * 0.29 or 2.9); Rec Yards translation= 49.75 or 4.975 YDS = 1pt
• “3B” Success Narrative (0.57 or 5.7)
Plays that describe a another additional degree of Offensive and Defensive success
Categories: Receiving 1st Down, Defensive Interception, Defensive Fumble Recovered

• 10-Yr BASEBALL occurrences: 8,754
• 10-Yr FOOTBALL occurrences: 68,181
• ‘Fantasy Universe Balance Ratio’: 0.1284 (8754/ 68181)
• Fantasy Football Category Scoring Weights: 0.0732 or 0.732 (0.1284 * 0.57 or 5.7)
• “HR” Success Narrative (0.94 or 9.4)
Plays that describe the “ultimate” Offensive and Defensive success (not factoring Offensive TD’s)
Categories: Passing 1st Down, Rushing 1st Down, Defensive TD, Safety, Kick-off & Punt Return TD (Team), 3&Outs Forced (Team), 4th Down Stops (Team), Blocked Kick (Team)

• 10-Yr BASEBALL occurrences: 49,490
• 10-Yr FOOTBALL occurrences: 108,364
• ‘Fantasy Universe Balance Ratio’: 0.4567 (49490/ 108364)
• Fantasy Football Category Scoring Weights: 0.4293 or 4.293 (0.4567 * 0.94 or 9.4)
• “BB+HBP” Success Narrative (0.3 or 3)
The factor that describes how much the ball was moved in either the Offense’s or Defense’s positive direction
Categories: Passing Yards, Rushing Yards, Return Yards, Turn-Over Return Yards

• 10-Yr BASEBALL occurrences: 168,175
• 10-Yr FOOTBALL occurrences: 2,501,468
• ‘Fantasy Universe Balance Ratio’: 0.0672305 (168175/ 2501468)
• Fantasy Football Category Scoring Weights: 0.020169 or 0.20169; Rec Yards translation= 49.58 or 4.958 YDS = 1pt
• “SB” Success Narrative (0.19 or 1.9)
Events that “steal” additional points after an Offensive drive

• 3-Yr BASEBALL occurrences: 7,569
• 3-Yr FOOTBALL occurrences: 6,014
• ‘Fantasy Universe Balance Ratio’: 0.7946 (6014/ 7569)
• Fantasy Football Category Scoring Weights…
• XP Made and 2-Pt Convserions: 0.151 or 1.5097
• For additional details on FG Ranges, see the section below…
• FG Made, 0-19 Yards: 1.375 or 13.753
• FG Made, 20-29 Yards: 0.163 or 1.634
• FG Made, 30-39 Yards: 0.243 or 2.434
• FG Made, 40-49 Yards: 0.373 or 3.728
• FG Made, 50+ Yards: 1.171 or 11.711
• “CS” Success Narrative (-0.28 or -2.8)
Events that describe the unsuccessful attempt to “steal” additional points after an Offensive drive
Categories: Extra Points Missed, FG’s Missed (within different ranges)

• 3-Yr BASEBALL occurrences: 2,999
• 3-Yr FOOTBALL occurrences: 688
• ‘Fantasy Universe Balance Ratio’: 0.2294 (688/ 2999)
• Fantasy Football Category Scoring Weights…
• XP Missed: -0.0642 or -0.642
• For additional details on FG Ranges, see the section below…
• FG Missed, 0-19 Yards: -9.2926 or -92.926
• FG Missed, 20-29 Yards: -1.0197 or -10.197
• FG Missed, 30-39 Yards: -0.1808 or -1.808
• FG Missed, 40-49 Yards: -0.04598 or -0.4598
• FG Missed, 50+ Yards: -0.02027 or -0.2027

All of that said, I used the study and considerations for a setup that is better scaled to the wRC baseball formula relative to a hypothetical league’s “Replacement Level” for each position and devised a different (“better” fantasy) scoring system detailed in this second thread.

Field Goal Made & Missed Difficulty Scales
As a way of increasing and scaling the scoring production of K’s, I created a “difficulty” weighting for the five different FG ranges available. This rating was factored within the “SB/CS” weighted points formula above.

The “Difficulty” scales went 1-3-5-7-9 for each successive “FG Make” range and 9-7-5-3-1 for each successive “FG Missed” range. To factor the point value of each range, I took the “FG/SB” balance ratio and multiplied by the 0.19 SB Point value and the corresponding ‘Difficulty Factor’ (and made the same calculations for the ‘CS’ category’s FG Miss ranges). I then divided this number by the rate of occurrence for each FG within the specified range (e.g., # of 0-19 FG’s / # of total FG’s). This number was then divided by 10 to bring the value back within range for K’s.

One clear difference to note here is the points differential for FG’s made in the 0-19 Yards range, which are valued significantly above all other FG’s made between 20-49 Yards. The mathematical reasoning is that there are fewer occurrences within that range than with any other. The other factor here is that no FG attempt within that range has been missed within the time-frame of the study (and as such, I had to ‘pretend’ like one was in order to set a reasonable point-value for any missed attempt); as a result, the points penalty for any miss within that short range is more significant than any other point value for any other FG range, make or miss.

As it relates to ‘real life’, however, the “philosophical” reasoning for this could be that every team’s scoring probability jumps significantly in the Red Zone- and that is what’s reflected in the Pts value of FG’s within that range. In other words, any FG’s attempted within 0-19 Yards are pretty much a given because the Offense was so successful at moving the ball to a spot where the K shouldn’t miss (and if he does, the ‘levered’ trade-off is reflective of that); so, any points produced within that range are practically ‘automatic’. As it relates to each individual K and their influence on any fantasy matchup, however, because there are generally less than a dozen attempts within that range in the NFL every season, points scored within the range still have a relatively small influence on any game and the K’s season as a whole.

Initial/Post-Draft Impressions
First, Yahoo’s draft platform on draft night for the league linked above was incredibly slow and choppy and it was difficult to have an effective Auction Draft. So, negative marks on them for that.

Second, my impression on the draft strategies for most in the room was similar to what you might expect in a more “regular” fanatasy football league; big money was spent on offensive skill (non-QB) players while the end of the draft was more or less reserved for Defensive players, even though the two roles score similarly. Many teams also didn’t reserve much cash for a backup-QB, which (I think) is considerably more important for a league with this scoring.

Considering the scoring dynamic between players/roles as well as between football/baseball, it seems that QB’s score similarly per game as SP’s (~15-40+ pts per) while everyone else scores similar to Hitters (per game). However, in terms of the week-to-week roster/scoring balance, I expect the offensive positions to be a little more volatile (like Pitchers are in fantasy baseball) while the defensive side will score more consistently each game (like Hitters).

In a way, that’s not unlike a fundamental difference between the two sports: Outs are a given in baseball (or, the “Pitching” side is expected to be more successful than not- the volatility comes when the defense doesn’t secure the ‘expected’ Outs) while in Football it’s all about Yards and 1st Downs (or, the “Offensive” side is expected to be more successful than not- it’s just a degree of how successful they are vs the other team’s defense). Because of this, I expect most managers to continue to roster just enough defensive players to field a full defensive lineup while using all of their Bench on offensive ‘matchup streaming’ options. However, because of injuries and Bye weeks, I’m expecting there to be almost as much value in having extra defensive player on the bench in lieu of extra offensive players (and so far after the first two weeks of the season, it seems as though more Defensive players have a “Questionable” or “Out” status than Offensive players in any given week- so it might be necessary to expand on Bench spots in the future).

Looking ahead to how the league might play out, my expectation is that it will be those minor differences in a player’s production relative to his average or expected output that will make the difference in our fantasy matchups. I’m interested to see how many instances there are where a team’s QB performs significantly worse than his opponent’s but the production of the other players on the roster is enough to make-up the difference, and I’ll be paying special attention to how team’s play their defensive rosters. I’ll also be watching the balance of the players available in the FA pool.

OK- that’s a wrap for this setup. Now onto a formula evolved from this one…