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alexfall862

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  1. Ad Application:

    • Game: NCAA National Championship or Super Bowl (depending on when turnover happens)
    • Company: Nacrotics Anonymous
    • Sponsoring the first fumble of each game
    • Script: "This turnover has been brought to you by your anonymous friends at NA. Whether it's fleeing the police across the country in a stolen Subaru or losing a championship game to the third best team in Oklahoma, turn to us after your rock bottom."
    • Tagline: "Don't fumble your life away. Don't be Matt Howard."

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  2. Oh sorry, the other 20 points are the affinities. So a perfect school would get 50% of the total possible score addition from that, and then another 20% comes from having or not having affinities. Broadly speaking, the difference between a 0-12 school and a 12-0 school is about the same as 1 affinity matching.
  3. Hello Coaches!

     

    Welcome to the second Dev Diary for 2022 on the new recruiting system for this coming season.

     

    Recruiting Dev Diaries for 2022

    Dev Diary 54: Recruiting Affinities Refresh | Close to Home

    Dev Diary 55: Recruiting Affinities Refresh | Other Affinities

    Dev Diary 56: Recruiting Efficiency Score

    Dev Diary 57: Recruiting on the Interface

     

    With this diary, I want to introduce the new recruiting system. The goal of overhauling the system was to take advantage of what the interface gives us in the form of new ways to connect on-field performance and recruiting while both preserving and nerfing the affinity system.

     

    Challenges of Last Season

     

    One of the things that was clear when reviewing the first season of recruiting was that affinities had a very strong influence on whether a team could even consider competing for a recruit. Schools could invest as little as 5 points into a recruit and get 90% of their necessary points through the affinity bonus system. In isolation, this doesn't mean too much, but the effect it had on recruiting was in shutting out competition and leading to a dice roll in player generation dictating committals before recruiting even began.

     

    We can also take advantage of the interface, and more realistically simulate the way a player may consider a school. Beyond affinity matching having a strong hand in recruiting choices, we also saw Georgia and Nebraska bring in really strong classes despite absolutely putrid seasons. To be fair, in real life poor teams can often out recruit their relative place in the standings due to affinity with recruits, but while both teams were closing the season getting blown out, they were also signing 5* recruits and that just didn't pass the smell test.

     

    The new recruiting system retains the points based recruiting backbone of the previous system. Each team still gets 50 Recruiting Points (now called Recruiting Time Points - think of the 50 points as an approximation of how your coaching staff divides their time among recruits) each week. (or fewer if you have an administrative penalty for bad gameplans or other site issues).

     

    Recruits still have a threshold that ticks down over time and reacts to the number of teams recruiting them.

     

    What has changed are two things: we've swapped out the Affinity Bonus for a Recruiting Efficiency Score and recruits now have memories.

     

    Recruits are Now Goldfish

     

    Before we dive into the big change, let's go over memories. One of the bigger issues that came up in feedback was the battle of trying to overcome schools who were currently inactive but had pushed the committal threshold so high that no other school could get a player to commit until the last week of the recruiting season.

     

    Part of this was intended. Recruits should naturally want to wait to hear back form all possible options - but when looking at some of the recruiting battles, it was clear that this behavior from recruits was ultimately harmful to the fun of recruiting and not all that realistic as a recruit is unlikely to commit to a school that's ghosting them.

     

    Recruits will now only evaluate the last ten weeks when counting the number of teams interested in them. They will still consider all Recruiting Time Points when calculating a decision, though, so a school that was active in week 1 could conceivably get a commitment without further activity provided no other school made a serious effort on that player.

     

    Recruiting Efficiency Score

     

    The Recruiting Efficiency Score is a modifier to team's point totals with recruits meant to be an approximation of how well your pitch is landing with a recruit. 0-8 with no affinity match with a recruit? Expect your pitch to be less effective with a recruit than a 2-6 school with 1 affinity match, or a an 8-0 juggernaut that's also close to home.

     

    The value of the modifier in the Recruiting Efficiency Score is between -20% and 20%, meaning that the worst possible fit for a recruit is at 80% strength compared to the median school. It also means that the best possible situation has effectively 120% strength in recruiting. When pitting the best fit against the worst fit, it would be a 50% advantage for the best fit school. That's far more modest than the previous affinity system gave out.

     

    The nuts and bolts of how the affinity score is calculated are below, but broad strokes are this: wins and losses account for 30% of the score, postseason participation of various kinds and strengths (bowl game, conference championship appearance, conference title, playoff, etc.) account of 10%, and 50% of the score is evaluated by matching affinities.

     

     

     

    The specific weights for the current calculations of the RES are as follows:

    ItemWeights
    Previous Season Overall Record Wins over Conference Games Played5.00%
    Previous Season Conference Wins over Conference Games Played5.00%
    Current Season Overall Record W over Games Played10.00%
    Current Season Conference W over Games Played10.00%
    Coach Career Record Wins (avg wins per season over total games per season)10.00%
    Affinity Match 125.00%
    Affinity Match 225.00%
    Postseason Games (Full Credit for Bowl Game Participation, Bowl Outcome has No Weight)5.00%
    Conference Championship (Full Credit for Title, Half Credit for Participation)5.00%
    Rivalry Trophies Held / Other Flavors (WIP, may be added for 2023)0.00%

     

     

     

    Examples

     

    This is all a little heady, so let me give some example situations.

     

    Tulsa had a perfect season last year. They maxed out every category in the RES that a school can control. Their score for the year was 100%.

     

    If they're recruiting a player they have 1 affinity match for, their RES goes to 110%, and 120% if they match both affinities.

     

    Because this is a modifier on the Recruiting Time Points, Tulsa's RES for a 1 affinity match recruit would be:

     

    Week 1: (5 RTP Points in Week 1) * RES of 110% = 5.5 Points logged into the recruit in week 1.

     

    Let's say Tulsa loses their opener. That would impact their score (0/0 games played is full credit in the RES, but once a game is played it references that outcome. 0/0=1 is meant to be an approximation of hope springing eternal in the offseason.) This would drop their baseline RES score from 100% to 94.76%. The affinity bonus still applies, so in week 2 their RES would be 104.76%.

     

    Week 2: (5 RTP Points in Week 1 + 5 RTP Points in Week 2) * RES of 104.76% = 10.476 Points logged into the recruit week 2.

     

    Oh no, they also lose their home conference opener as well! But, to make up for that, they're spending 10 RTP points this week on the recruit instead of 5. Their baseline RES drops to 89.56% because they're now getting 0 credit for current season conference record.

     

    Week 3: (5 RTP Points in Week 1 + 5 RTP Points in Week 2 + 10 RTP Points in Week 3) * RES of 99.56% = 19.912 Points logged into the recruit week 2.

     

    Competition

     

    Let's now say that Texas Tech has an interested in that same player and also has an affinity match, but where Tulsa had the best season, Texas Tech has the worst. For comparison of the system, let's say they start off white hot and win their first game and conference opener.

     

    Their initial RES is 90% and they have 1 affinity match for an RES with this recruit of 100%. Let's say they win a noncon week 1 and a conference game week 2 and go into week 3 sensing a battle with Tulsa and also put in 10 puts in week 3. This is how it would break down:

     

    Week 1: (5 RTP Points in Week 1) * RES of 100% = 5 Points logged into the recruit in week 1.

     

    Week 2: (5 RTP Points in Week 1 + 5 RTP Points in Week 2) * RES of 100.29% = 10.0029 Points logged into the recruit week 2.

     

    Week 3: (5 RTP Points in Week 1 + 5 RTP Points in Week 2 + 10 RTP Points in Week 3) * RES of 100.53% = 20.106 Points logged into the recruit week 2.

     

    So we can see that Texas Tech started the season at a 10% disadvantage, but in just 3 weeks were able to shorten the gap in RES score, by virtue

     

    In a third example, let's say Texas Tech has all the plans in the world to contest this recruit, but instead of opening white hot, they fall flat on their face while Tulsa continues on pace.

     

    Tulsa by Week 3: Baseline RES of 100% + 10% Affinity Bonus = 110% * 20 = 22 points logged.

    Tech by Week 3: Baseline RES of 80% + 10% Affinity Bonus = 90% * 20 = 18 points logged.

     

    In a fourth example, let's say everything about the previous example stays the same, except Tulsa has no affinity match with this particular recruit.

     

    Tulsa by Week 3: Baseline RES of 100% + 10% Affinity Bonus = 100% * 20 = 20 points logged.

    Tech by Week 3: Baseline RES of 80% + 10% Affinity Bonus = 90% * 20 = 18 points logged.

     

    Takeaways

     

    The example above uses the best and worst team possible by on-field performance. Tulsa currently has the highest possible score, and Texas Tech has the lowest possible score. For most teams, their baseline RES scores are going to revolve around 90-95% throughout the season. While that's not nothing, it isn't a huge difference in impact on the total race for a recruit.

     

    However, cumulatively, a bad season is about a 10-15% difference in RES and it takes roughly 1 affinity match to counteract that deficit. This has the intended goal of making teams that should have no business in real life of competing for recruits against powerhouse programs think twice before chasing after 5* players - yet at the same time doesn't completely eliminate the possibility they could get one.

     

    Conference championships and bowl games last until the next round of games, so they can act as a buoy for teams that have a bad follow-up year. This advantage doesn't seem unrealistic, as the 'glow' doesn't come off a team in less than a year.

     

    The longer the sim goes, the more stable a coaching record value is going to be. This should act as a stabilizing force for many programs with long-tenured programs, and will also protect coaches who take over struggling teams from being tied behind the recruiting anchor of their new team's previous season record. A 9-3 good coach taking over a 3-9 program equals out to the same credit as a 6-6 team with a 6-6 coach.

     

    2021 End of Year Scores

     

    The RES score is supposed to be an evolving number, but to give you some idea of of the effect it will have by year's end, here's what last year's end of season RES would have looked like:

     

    Without the bump from the RES calculator treating the beginning of the season as a 'clean slate', Texas Tech sits at 80% along with UTEP.

     

     

     

     

    TeamSUM of Recruiting Efficiency Score
    Tulsa100.00%
    Florida State99.31%
    Kentucky99.27%
    Wisconsin98.53%
    Texas State98.43%
    Ohio97.02%
    North Texas97.02%
    Boston College96.43%
    Old Dominion95.59%
    Alabama95.59%
    Baylor95.46%
    San Diego State95.30%
    Purdue95.09%
    Illinois95.09%
    Texas95.04%
    Air Force94.80%
    Tennessee94.71%
    TAMU94.71%
    Oregon94.67%
    Arizona94.26%
    Florida Atlantic93.87%
    Akron93.87%
    Appalachian State93.52%
    California93.28%
    Virginia93.24%
    Temple93.24%
    UAB93.02%
    Tulane92.99%
    Troy92.99%
    Missouri92.99%
    Mississippi State92.99%
    Marshall92.99%
    Duke92.99%
    Cincinnati92.99%
    TCU92.44%
    Kansas State92.44%
    Colorado92.44%
    Western Michigan92.14%
    UNLV92.14%
    Central Michigan92.14%
    Stanford91.66%
    Oregon State91.66%
    Ohio State91.66%
    Michigan State91.66%
    Wyoming91.30%
    Utah State91.30%
    Rice91.30%
    New Mexico91.30%
    Bowling Green91.30%
    Arkansas State91.30%
    NC State91.27%
    Georgia State91.27%
    Georgia Tech90.45%
    UTSA90.42%
    SMU90.42%
    Pittsburgh90.42%
    Louisiana Tech90.42%
    Fresno State90.42%
    Auburn90.42%
    UCLA89.97%
    Oklahoma State89.97%
    Rutgers89.71%
    Coastal Carolina89.58%
    Penn State89.19%
    Minnesota89.19%
    Maryland89.19%
    Ball State89.12%
    East Carolina88.96%
    Nevada88.08%
    Navy88.08%
    Lousiville88.08%
    Florida International88.08%
    Florida88.08%
    USC87.69%
    Kansas87.69%
    Iowa State87.69%
    Arizona State87.69%
    Northern Illinois87.21%
    North Carolina87.21%
    Middle Tennessee87.21%
    Kent State87.21%
    Eastern Michigan87.21%
    Colorado State87.21%
    Birginia Tech87.21%
    Arkansas87.21%
    BYU86.92%
    Michigan86.92%
    West Virginia86.78%
    Northwestern86.78%
    UCF86.33%
    South Carolina86.33%
    Miami (OH)86.33%
    Georgia Southern86.33%
    Ole Miss86.29%
    Louisiana86.29%
    Iowa86.14%
    Umass86.08%
    San Jose State85.42%
    Memphis85.42%
    Buffalo85.38%
    Washington85.22%
    Oklahoma85.22%
    Indiana85.22%
    Notre Dame84.58%
    Army84.58%
    Western Kentucky84.50%
    Wake Forest84.50%
    USF84.50%
    Southern Miss84.50%
    South Alabama84.50%
    Miami (FL)84.50%
    Clemson84.50%
    Washington State84.31%
    UConn83.67%
    New Mexico State83.67%
    LSU83.63%
    Nebraska83.39%
    Liberty82.75%
    Toledo82.71%
    Syracuse82.71%
    Louisiana-Monroe82.71%
    Houston82.71%
    Hawaii82.71%
    Charlotte82.71%
    Boise State82.71%
    Utah82.61%
    Vanderbilt81.79%
    Georgia81.79%
    UTEP80.00%
    Texas Tech80.00%

     

     

     

    Here's that distribution as a graph

     

     

     

     

    1649578912924.png.4300ab74a641e49720b338934a55e4bb.png

     

     

     

    and the quartile measurements - lower scores tend to be lower than the high scores are high, meaning that having a bad season is going to separate you from the meh teams more than than a meh season is going to separate you from the good teams. Again, this is the intended outcome. That's not to say teams that perform poorly can't recruit good players, they'll just need to be more mindful of affinity matches and spend more points per recruit.

     

     

     

     

    Min80.00%
    2nd Quartile85.58%
    3rd Quartile89.19%
    4th Quartile92.99%
    Max100.00%

     

     

     

     

     

     

    This is a WIP

     

    This project is a WIP. Other derivations of this general idea are also possible.

     

    Testing on this concept has been slow, because the number crunching is just a little too much for a google sheet to handle, and I'm sure we'll learn things when we do a test run off of the interface. As stated above, the goal here is to take advantage of what the interface gives us in the form of new ways to connect on-field performance and recruiting while both preserving and nerfing the affinity system.

     

    I could foresee the overal span of effect changing from the 80%-120% to 70%-130% or 90%-110% if coaches feel on-field performance has too dynamic an effect or not dynamic enough of an effect.

     

     

    Wrap Up

     

    Unlike the affinity refresh project, this is more of a single person project - so I'll take credit for whether this sinks or swims. I would like to shout out @TuscanSota though for getting the interface closer and closer to up and running and for talking me through what he can do the facilitate this idea. As I mentioned above, this is a WIP, but thanks to @TuscanSota, the bones of this project are ready to go in the interface.

     

    Like everything else, I welcome your input and these diaries are an effort to be as transparent as possible about the way recruiting works, where my minds going as far as these projects, and I look forward to a test run in the near future. The next dev diary in this quartet will be written and released shortly as a preamble to the first test run of this recruiting system.

    1649579341137.png.e6abb1ef9764e3fcc9892192bbbd1224.png

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  4. Hello Coaches!

     

    Welcome to the second Dev Diary for 2022 on the new recruiting system for this coming season.

     

    Recruiting Dev Diaries for 2022

    Dev Diary 54: Recruiting Affinities Refresh | Close to Home

    Dev Diary 55: Recruiting Affinities Refresh | Other Affinities

    Dev Diary 56: Recruiting Efficiency Score

    Dev Diary 57: Recruiting on the Interface

     

    With this diary, I want to go over the cleaning run on affinities for the next season. The goal for this offseason was to look at all affinity assignments and make sure teams were getting bonuses that made sense and that the system overall was reflecting something close to reality. Specifically with the non-close to home affinities, the goal was to find a way to tie the affinity assignment into objective measurements as much as possible.

     

    In some ways, the affinities aren't strictly objective qualities, but we made an effort as a working crew to find public reference points we can point coaches to, instead of 'well it just feels right'.

     

    Academics

     

    Academics is now tied to the 2022 US News Top 20.

     

     

     

    AdditionsRemovals
    FloridaGeorgia

     

     

     

    Service

     

    No changes were made to Service, as those are tied to the Service Academies, Army, Navy, and Air Force [iSPOILER]...and soon to be Space Force? [/iSPOILER]

     

    Religion

     

    No changes were made to Religion, as those are the 11 schools aligned with a specific religious institution:

     

    Baylor (Baptist General Convention)

    Boston College (Jesuit)

    BYU (Mormon)

    Duke (United Methodist Church)

    Liberty (Jerry Falwell)

    [iSPOILER]Nebraska (Corn)[/iSPOILER]

    Notre Dame (Catholic)

    SMU (United Methodist Church)

    Syracuse (Nonsectarian, formerly United Methodist Church)

    TCU (Disciples of Christ)

    Tulsa (Presbyterian Church)

    Wake Forest (Nonsectarian, formerly Baptist)

     

    Large Crowds

     

    Large Crowds was made to include schools with attendance capacity above 70,000 fans. 3 schools were removed. None added.

     

     

     

    AdditionsRemovals
    N/AMissouri (61,620)
    SDSU (35,000)
    UAB (47,100)

     

     

     

    Small School

     

    Small schools were pinned to enrollment data from US News. 7 schools were added, and 4 were removed.

     

     

     

    AdditionsRemovals
    AkronApp State
    CMUIllinois
    EMUMiami (OH)
    HawaiiNew Mexico
    NM State
    NIU
    Northwestern
    Syracuse
    Toledo

     

     

     

    Frontrunner

     

    Frontrunner was changed from the somewhat unknowable measure of team overall from before any games were played to a list of championship teams. These are the schools who won their conference championship and/or made the playoff. By changing this definition, it is also the first affinity in the sim tied directly to on the field results! 8 teams were added, 15 were removed.

     

     

     

    AdditionsRemovals
    BaylorAlabama
    North TexasArizona
    OhioArizona St
    San Diego StCMU
    OregonGeorgia Tech
    Texas StLSU
    Boston CollegeMichigan St
    PurdueNotre Dame
    Ohio St
    Oklahoma
    Oklahoma St
    Oregon St
    TCU
    Wake Forest
    Washington

     

     

     

    Climate

     

    Climate has been removed from affinities, because after review, it seemed like assignment was completely arbitrary and since we couldn't tie it to a specific reference point, it was therefore also unfair. 17 schools were removed, 5 of which had no other affinity.

     

     

     

    Removals
    Arizona*
    Arizona St*
    Cal
    Clemson
    Coastal Carolina
    FIU*
    Florida
    Hawaii
    Miami (FL)
    SDSU
    South Carolina
    Stanford
    Tennessee
    UCF*
    UCLA
    USC
    USF*

     

    *No other affinity

     

     

     

    Current Affinity Assignments

     

    See this thread for current affinity assignments.

     

    Here are the numer of affinities by school:

     

     

    SchoolSUM of Total Affinities
    Notre Dame4
    Boston College4
    Wisconsin3
    Wake Forest3
    Tulsa3
    Duke3
    Baylor3
    Vanderbilt2
    USC2
    UCLA2
    Tulane2
    Texas2
    TCU2
    Syracuse2
    Stanford2
    SMU2
    Rice2
    Northwestern2
    Navy2
    Michigan2
    Illinois2
    Florida State2
    Florida2
    Army2
    Air Force2
    Wyoming1
    Washington1
    Virginia1
    UAB1
    Troy1
    Toledo1
    Texas State1
    Texas A&M1
    Tennessee1
    Southern Miss1
    South Carolina1
    South Alabama1
    San Diego State1
    Purdue1
    Penn State1
    Oregon1
    Oklahoma1
    Ohio State1
    Ohio1
    Northern Illinois1
    North Texas1
    North Carolina1
    New Mexico State1
    Nebraska1
    Michigan State1
    Miami1
    Marshall1
    LSU1
    Louisiana-Monroe1
    Louisiana Tech1
    Louisiana1
    Liberty1
    Kentucky1
    Iowa1
    Hawaii1
    Georgia Tech1
    Georgia1
    Eastern Michigan1
    Coastal Carolina1
    Clemson1
    Central Michigan1
    California1
    BYU1
    Bowling Green1
    Auburn1
    Arkansas State1
    Arkansas1
    Alabama1
    Akron1
    Western Michigan0
    Western Kentucky0
    West Virginia0
    Washington State0
    Virginia Tech0
    UTSA0
    UTEP0
    Utah State0
    Utah0
    USF0
    UNLV0
    UMass0
    UCF0
    Texas Tech0
    Temple0
    San Jose State0
    Rutgers0
    Pittsburgh0
    Oregon State0
    Old Dominion0
    Oklahoma State0
    New Mexico0
    Nevada0
    NC State0
    Missouri0
    Mississippi State0
    Mississippi0
    Minnesota0
    Middle Tennessee0
    Miami (OH)0
    Memphis0
    Maryland0
    Louisville0
    Kent State0
    Kansas State0
    Kansas0
    Iowa State0
    Indiana0
    Houston0
    Georgia State0
    Georgia Southern0
    Fresno State0
    Florida Atlantic0
    FIU0
    East Carolina0
    Connecticut0
    Colorado State0
    Colorado0
    Cincinnati0
    Charlotte0
    Buffalo0
    Boise State0
    Ball State0
    Arizona State0
    Arizona0
    Appalachian State0

     

     

     

    Future Affinity Plans and Ideas

    For those 5 schools schools who lost out on their affinity, and for any other coaches that find themselves either out of affinities or are down one - there's no need to fret quite yet! Our next dev diary will go into the ways that affinities are being reworked in the actual recruiting process. You'll have to stay tuned to hear the specifics, but in general expect affinities to have ~5-10% boost to recruits as opposed to the ~900% boost possible when gaming the previous system in the most efficient way possible.

     

    As a team, we also floated some new affinity ideas, but with recruiting moving entirely into the interface and a pretty substantial recruiting process overhaul, we've left the affinity additions out of this next recruiting cycle.

     

    Here are some of the ideas floated out by team members in the past, that are under consideration:

     

    Party School

    Schools were the students party pretty hard. Issue with adding is that's arguably any school.

     

    Urban/Rural Schools

    Schools located in urban areas could get a boost with kids who want to live the city life, rural school the opposite. Issue with adding is having to find the delineation between urban and rural - especially with so many schools being in bedroom communities around larger metro areas. Is Northwestern urban because Chicago or rural because Evanstown is a "small town"? Probably not, because it's pretty clearly part of the metropolitan area. What about Ames and Des Moines or Bloomington and Indianapolis?

     

    Large School

    This is the corollary to the small school affinity already listed. Issue with adding is whether this really does anything different than the large crowds affinity.

     

    With the move into the interface, there's also long-term potential to tie affinities into on-field performance in a more direct manner. Some of the affinities suggested that fall into that category are:

     

    Play Style

    Players could get an affinity match with schools who have particular schemes assigned. Issue here is how to measure that, and what happens to teams that change scheme - is it fair to penalize a team for switching scheme? What even defines a scheme?

     

     

    NIL Opportunities

    Players could get an affinity match with schools who have large endowments and high enrollments. Issue with adding is similar to a Large School affinity. Does it really add anything different or just reinforce that affinity?

     

    Playing Time

    Certain players look for where they will start immediately. Issue with adding is how that would be measured without becoming a particularly hairy evaluation each recruiting week.

     

    Play with a Legendary (QB/RB/WR/TE/OL/DL/LB/CB/S/K/P/Coach)

    Players with this type of affinity want to commit to a school where a particular position player or coach is at - and they want to learn or be in the same position group room as the best of the best. Issue here is how discerning how it's different from the frontrunner affinity, and it also has the same challenge as the playing time affinity. Evaluating anything over 130 rosters could become hairy very quickly.

     

    Feel free to suggest your own affinity ideas here as we will use the 2022 season to start planning recruiting changes in 2023.

     

    Wrap Up

     

    I asked some users to help out with this job, and special thanks need to go to @PoopyRhinoPickle @subsequent @TuscanSota @Rocketcan @tsweezy for their help and especially to @PoopyRhinoPickle as this dev diary would probably have been posted a month from now without his help compiling all of the changes.

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  5. Hello Coaches!

     

    Welcome to the first Dev Diary for 2022 on the new recruiting system for this coming season.

     

    Recruiting Dev Diaries for 2022

    Dev Diary 54: Recruiting Affinities Refresh | Close to Home

    Dev Diary 55: Recruiting Affinities Refresh | Other Affinities

    Dev Diary 56: Recruiting Efficiency Score

    Dev Diary 57: Recruiting on the Interface

     

    With this diary, I want to take a moment to talk about the changes to close to home assignment for the next season. The goal for this offseason was to look at all affinity assignments and make sure teams were getting bonuses that made sense and that the system overall was reflecting something close to reality. This Dev Diary is for the Close to Home affinity, which affects around 60% of all recruits in a given class.

     

    Close to Home Score

     

    In order to compare schools' situations as close to objectively as possible, I developed a score to reflect the strength of a team's close to home assignments. There's a little bit of math behind it, but the gist of the score is that the higher the number, the stronger the close to home advantage that team should have.

     

     

     

    The nitty gritty of the score is this: First, the source of the score is the 2021 recruiting class. Each recruiting region was scored by the number of recruits in that region (i.e. a region with 25 recruits would have a score of 25).

     

    That number was then divided by the number of schools who were booked to receive a close to home bonus for that region. (i.e. if a region had 25 recruits and 4 schools assigned, the score would be 6.25)

     

    Each school in the given region scores that they qualify for. In effect, this score should represent the number of potentially uncontested recruits for a school if all schools with close to home for that region did not compete against each other.

     

    A score of 30 for a school like UCF means that they could theoretically get a full class and change worth of players recruited with a close to home bonus and not have them contested by other schools. A school like Utah St with a score of 2.6 means that even if everything breaks right and other schools in their close to home orbit avoid competing with them for recruits, they should only expect to have 2 or 3 recruits with the close to home bonus in their class.

     

    In practice, not all of the players eligible for a school's close to home bonus will be worth signing, and schools are absolutely going to compete for recruits against each other, so the numbers aren't 1:1 to an expected outcome - but it gives both a point of comparison for affinity assignments and some broad context for the schools themselves even if it's not an exact match.

     

     

     

    When comparing schools, first let's look at total number of players each school could recruit with a close to home bonus. This is the total number of players in CtH states for schools, multiplied by 60% (the percentage of recruits generated with close to home affinity):

     

     

     

     

    SchoolAverage of Likely Recruits with CtH Matched
    Rice307.2
    SMU261
    South Carolina249.6
    Clemson249.6
    Texas240
    Florida240
    Baylor240
    Louisiana225
    Notre Dame223.8
    Auburn222
    West Virginia221.4
    Georgia Southern216
    Florida State216
    Texas A&M187.2
    Houston187.2
    Pittsburgh182.4
    USF180
    UCF180
    Miami180
    Florida Atlantic180
    FIU180
    Georgia Tech177.6
    Georgia177.6
    Texas Tech174.6
    Fresno State173.4
    Toledo172.8
    Bowling Green172.8
    Southern Miss171
    Mississippi State171
    South Alabama163.8
    Maryland160.8
    Michigan158.4
    Georgia State156
    Oklahoma State151.2
    San Diego State150
    Kentucky148.8
    UNLV148.2
    Cincinnati146.4
    Eastern Michigan142.2
    TCU141
    Oklahoma141
    North Texas141
    Appalachian State139.2
    Penn State136.8
    North Carolina132.6
    Ball State130.2
    Arizona State126.6
    Troy126
    UTSA120
    Texas State120
    Temple119.4
    Marshall118.2
    Navy117.6
    Virginia Tech113.4
    Louisiana-Monroe112.8
    Army112.2
    Wake Forest111
    Old Dominion111
    East Carolina111
    Duke111
    USC110.4
    UCLA110.4
    Tulane105
    Rutgers105
    LSU105
    Alabama103.8
    Ohio102
    Northwestern100.8
    Ohio State99.6
    Kent State99.6
    Akron99.6
    NC State93.6
    Charlotte93.6
    Western Michigan89.4
    Nevada88.2
    Oregon87.6
    Missouri87
    Northern Illinois84.6
    Iowa84
    Wisconsin83.4
    Oregon State82.2
    Purdue81.6
    Indiana81.6
    Virginia81
    Western Kentucky75
    Memphis73.8
    UAB66
    Boise State63
    Arkansas61.8
    Michigan State58.8
    Buffalo58.2
    Illinois51
    Stanford50.4
    San Jose State50.4
    California50.4
    Miami (OH)46.8
    Louisville46.8
    Mississippi45.6
    Louisiana Tech45.6
    Vanderbilt44.4
    Tennessee44.4
    Middle Tennessee44.4
    Central Michigan42.6
    Air Force42.6
    New Mexico40.8
    Nebraska40.8
    Kansas40.2
    Tulsa39
    Washington State37.8
    Washington37.2
    Kansas State37.2
    Iowa State37.2
    Utah34.2
    UTEP33.6
    UMass33.6
    New Mexico State33.6
    Connecticut33.6
    Boston College33.6
    Wyoming33
    BYU33
    Colorado State32.4
    Colorado32.4
    Arkansas State30.6
    Minnesota30
    Utah State27
    Syracuse25.2
    Arizona21.6
    Hawaii15

     

     

     

     

    This is certainly one measure to see which schools have an advantage with close to home as an affinity, but one thing it doesn't capture is the degree to which multiple teams are competing for the same resources. After all, is Hawaii really the worst place to try and recruit players who want to stay close to home? Is West Virginia really that strongly positioned?

     

    So instead of looking at total recruits, let's use the Close to Home Score.

     

     

     

     

    School2021 Class CtH Score
    Florida42
    Georgia Southern33.66
    Rice33.38666667
    Florida State31.5
    USF30
    UCF30
    Miami30
    Florida Atlantic30
    FIU30
    SMU29.29166667
    Georgia Tech28.99333333
    Auburn26.83333333
    South Carolina26.80285714
    Clemson26.80285714
    Texas26.66666667
    Baylor26.66666667
    UNLV25.89538462
    Arizona State24.1
    Texas Tech24.05833333
    Fresno State23.54038462
    Louisiana23.20333333
    San Diego State23.125
    South Alabama22.48333333
    Georgia State21.66
    Georgia21.66
    Texas A&M20.05333333
    Houston20.05333333
    Troy19.33333333
    Notre Dame19.25666667
    Maryland18.87714286
    West Virginia18.58214286
    Navy18.57714286
    USC17.91538462
    UCLA17.91538462
    Penn State17.75214286
    Oklahoma State17.23333333
    Southern Miss17.20333333
    Mississippi State17.20333333
    TCU15.95833333
    Oklahoma15.95833333
    North Texas15.95833333
    Pittsburgh15.58214286
    Temple15.57714286
    Iowa15.37714286
    Army15.215
    Hawaii15
    Rutgers13.655
    Toledo13.59
    Bowling Green13.59
    Oregon13.48038462
    UTSA13.33333333
    Texas State13.33333333
    Oregon State13.065
    Wisconsin12
    Appalachian State11.66785714
    Arkansas11.65714286
    Michigan11.55
    Eastern Michigan11.55
    Louisiana-Monroe10.845
    Louisiana Tech10.845
    Northwestern10.74
    Missouri10.53214286
    UAB10.48333333
    Alabama10.48333333
    Tennessee10.46785714
    Kentucky10.365
    North Carolina10.30285714
    Western Michigan10.065
    Miami (OH)10.065
    Cincinnati10.065
    Boise State9.955384615
    Tulane9.87
    LSU9.87
    Akron9.625
    New Mexico9.128571429
    Virginia8.957142857
    Kansas State8.457142857
    Virginia Tech8.442857143
    Marshall8.325
    Ball State8.265
    Wake Forest8.142857143
    Old Dominion8.142857143
    Liberty8.142857143
    East Carolina8.142857143
    Duke8.142857143
    UTEP8.1
    New Mexico State8.1
    Northern Illinois8.04
    Nevada8.020384615
    Purdue7.706666667
    Indiana7.706666667
    Illinois7.706666667
    Mississippi7.65
    Memphis7.65
    Washington State7.56
    Washington7.44
    Western Kentucky7.365
    NC State7.302857143
    Coastal Carolina7.302857143
    Charlotte7.302857143
    Syracuse7.255
    Iowa State6.978333333
    Arizona6.6
    Ohio6.525
    Minnesota6.453333333
    Ohio State6.225
    Kent State6.225
    Stanford6.040384615
    San Jose State6.040384615
    California6.040384615
    Buffalo5.575
    Nebraska5.51047619
    UMass5.415
    Connecticut5.415
    Boston College5.415
    Kansas5.39047619
    Vanderbilt5.325
    Middle Tennessee5.325
    Michigan State5.325
    Central Michigan5.325
    Air Force4.98
    Tulsa4.875
    Arkansas State4.232142857
    Louisville3.84
    Wyoming3.825
    Utah3.715384615
    BYU3.715384615
    Colorado State3.705
    Colorado3.705
    Utah State2.686813187

     

     

     

     

    This score does a good job of reflecting close to home advantages both in the sim and in real life. You can see all the rocky mountain schools tearing each other apart at the bottom due both to having few recruits in their regions, but also due to so many schools being in the same region. Instead of being ranked as the weakest school for close to home advantages, Hawaii is now in the upper middle of the rankings. This makes some sense, because while they may only have 25 recruits, there's no other competition that can argue a recruit could stay close to home without playing for Hawaii.

     

    We've spent some considerable time talking about the Close to Home Score, and I want to emphasize that this isn't a measure we tried to fit our schools to, but a score that lets use know whether our existing assignments pass the 'smell test'. The actual work of assignment and reassignment of close to home regions was done with quite a bit of hand-checking of regions and whether a school would plausibly be able to make the argument to a recruit that they'd be able to stay closer to home than their other options.

     

    In general, as far as straight geography, schools in the middle of the country have a geographically larger orbit in close to home regions and the coasts have a much tighter window to argue for close to home. My sense is that this reflects reality, as communities on the coast tend to be denser on the coasts and sparse in the plains, particularly the northern plains.

     

    2022 Close to Home Changes

     

    All of the above is a preamble to this - the changes that have been made for 2022 to Close to Home affinity assignments!

     

    You can look at the 2022 specific state assignments here and see an interactive map here. (One thing the map can't do is divide between the sub-state regions we have for California, Florida, and Texas. Copy the drive document to avoid two users trying to select things at the same time)

     

     

     

     

    School2022 Region Assignments2021 Region AssignmentsDifference
    Florida42420
    Georgia Southern33.6631.52.16
    Rice33.3866666734.13333333-0.7466666667
    Florida State31.531.50
    USF30300
    UCF30300
    Miami30300
    Florida Atlantic30300
    FIU30300
    SMU29.2916666729.291666670
    Georgia Tech28.9933333322.585714296.407619048
    Auburn26.8333333328.92857143-2.095238095
    South Carolina26.8028571429.13116883-2.328311688
    Clemson26.8028571429.13116883-2.328311688
    Texas26.6666666726.666666670
    Baylor26.6666666726.666666670
    UNLV25.8953846223.495384622.4
    Arizona State24.121.614285712.485714286
    Texas Tech24.0583333323.972619050.08571428571
    Fresno State23.5403846227.14038462-3.6
    Louisiana23.2033333324.23636364-1.033030303
    San Diego State23.12523.1250
    South Alabama22.4833333324.86493506-2.381601732
    Georgia State21.6619.52.16
    Georgia21.6622.58571429-0.9257142857
    Texas A&M20.0533333320.8-0.7466666667
    Houston20.0533333320.8-0.7466666667
    Troy19.3333333321.42857143-2.095238095
    Notre Dame19.2566666719.81738095-0.5607142857
    Maryland18.8771428621.1225974-2.245454545
    West Virginia18.5821428621.2425974-2.660454545
    Navy18.5771428615.72259742.854545455
    USC17.9153846217.915384620
    UCLA17.9153846217.915384620
    Penn State17.7521428619.45214286-1.7
    Oklahoma State17.2333333317.233333330
    Southern Miss17.2033333320.33160173-3.128268398
    Mississippi State17.2033333320.33160173-3.128268398
    TCU15.9583333315.958333330
    Oklahoma15.9583333315.958333330
    North Texas15.9583333315.958333330
    Pittsburgh15.5821428617.69714286-2.115
    Temple15.5771428617.27714286-1.7
    Iowa15.3771428611.486666673.89047619
    Army15.21516.795-1.58
    Hawaii15150
    Rutgers13.65515.355-1.7
    Toledo13.5914.15071429-0.5607142857
    Bowling Green13.5914.15071429-0.5607142857
    Oregon13.4803846213.480384620
    UTSA13.3333333313.333333330
    Texas State13.3333333313.333333330
    Oregon State13.06513.0650
    Wisconsin1211.366666670.6333333333
    Appalachian State11.6678571414.79090909-3.123051948
    Arkansas11.657142868.6752.982142857
    Michigan11.5513.99-2.44
    Eastern Michigan11.5511.965-0.415
    Louisiana-Monroe10.84511.8780303-1.033030303
    Louisiana Tech10.8454.4113636366.433636364
    Northwestern10.7410.252380950.4876190476
    Missouri10.5321428611.11666667-0.5845238095
    UAB10.483333339.4285714291.054761905
    Alabama10.4833333312.86493506-2.381601732
    Tennessee10.467857146.53.967857143
    Kentucky10.36510.92571429-0.5607142857
    North Carolina10.3028571413.17662338-2.873766234
    Western Michigan10.0659.5357142860.5292857143
    Miami (OH)10.0653.9857142866.079285714
    Cincinnati10.06510.62571429-0.5607142857
    Boise State9.9553846159.9553846150
    Tulane9.8710.9030303-1.033030303
    LSU9.8710.9030303-1.033030303
    Akron9.6256.642.985
    New Mexico9.1285714299.0428571430.08571428571
    Virginia8.9571428579.502597403-0.5454545455
    Kansas State8.4571428575.62.857142857
    Virginia Tech8.44285714310.39090909-1.948051948
    Marshall8.3258.74-0.415
    Ball State8.2658.825714286-0.5607142857
    Wake Forest8.14285714310.09090909-1.948051948
    Old Dominion8.14285714310.09090909-1.948051948
    Liberty8.142857143#N/A#N/A
    East Carolina8.14285714310.09090909-1.948051948
    Duke8.14285714310.09090909-1.948051948
    UTEP8.18.0142857140.08571428571
    New Mexico State8.18.0142857140.08571428571
    Northern Illinois8.048.227380952-0.1873809524
    Nevada8.02038461511.62038462-3.6
    Purdue7.7066666677.852380952-0.1457142857
    Indiana7.7066666677.852380952-0.1457142857
    Illinois7.7066666675.6666666672.04
    Mississippi7.654.4113636363.238636364
    Memphis7.659.111363636-1.461363636
    Washington State7.567.560
    Washington7.447.440
    Western Kentucky7.3658.685714286-1.320714286
    NC State7.3028571439.631168831-2.328311688
    Coastal Carolina7.302857143#N/A#N/A
    Charlotte7.3028571439.631168831-2.328311688
    Syracuse7.2553.7353.52
    Iowa State6.9783333336.3450.6333333333
    Arizona6.64.1142857142.485714286
    Ohio6.5256.94-0.415
    Minnesota6.4533333335.4451.008333333
    Ohio State6.2256.64-0.415
    Kent State6.2256.64-0.415
    Stanford6.0403846156.0403846150
    San Jose State6.0403846156.0403846150
    California6.0403846156.0403846150
    Buffalo5.5757.275-1.7
    Nebraska5.510476196.095-0.5845238095
    UMass5.4155.466428571-0.05142857143
    Connecticut5.4155.466428571-0.05142857143
    Boston College5.4155.466428571-0.05142857143
    Kansas5.390476195.975-0.5845238095
    Vanderbilt5.3256.5-1.175
    Middle Tennessee5.3256.5-1.175
    Michigan State5.3257.35-2.025
    Central Michigan5.3255.3250
    Air Force4.984.993186813-0.01318681319
    Tulsa4.8754.8750
    Arkansas State4.2321428574.775-0.5428571429
    Louisville3.843.985714286-0.1457142857
    Wyoming3.8253.838186813-0.01318681319
    Utah3.7153846153.728571429-0.01318681319
    BYU3.7153846153.5439560440.1714285714
    Colorado State3.7053.718186813-0.01318681319
    Colorado3.7053.718186813-0.01318681319
    Utah State2.6868131872.7-0.01318681319

     

     

     

     

     

     

    School20222021Difference
    Louisiana Tech10.8454.4113636366.433636364
    Georgia Tech28.9933333322.585714296.407619048
    Miami (OH)10.0653.9857142866.079285714
    Tennessee10.467857146.53.967857143
    Iowa15.3771428611.486666673.89047619
    Syracuse7.2553.7353.52
    Mississippi7.654.4113636363.238636364
    Akron9.6256.642.985
    Arkansas11.657142868.6752.982142857
    Kansas State8.4571428575.62.857142857

     

     

     

     

     

     

     

    School20222021Difference
    Charlotte7.3028571439.631168831-2.328311688
    South Alabama22.4833333324.86493506-2.381601732
    Alabama10.4833333312.86493506-2.381601732
    Michigan11.5513.99-2.44
    West Virginia18.5821428621.2425974-2.660454545
    North Carolina10.3028571413.17662338-2.873766234
    Appalachian State11.6678571414.79090909-3.123051948
    Southern Miss17.2033333320.33160173-3.128268398
    Mississippi State17.2033333320.33160173-3.128268398
    Nevada8.02038461511.62038462-3.6
    Fresno State23.5403846227.14038462-3.6

     

     

     

     

     

    Wrap Up

     

    I asked some users to help out with this job, and special thanks need to go to @PoopyRhinoPickle @subsequent @TuscanSota @Rocketcan @tsweezy for their help and especially to @PoopyRhinoPickle as this dev diary would probably have been posted a month from now without his help compiling all of the changes.

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