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Showing posts with label nfl. Show all posts
Showing posts with label nfl. Show all posts

Tuesday, May 14, 2024

Clark vs DeJean, A Fairly Competitive Game of One-on-One

A follow-up to my post, "Lavar vs Jordan, An Incredibly Lopsided Game of One-on-One". Cooper DeJean, professional football player and former Iowa Hawkeye, made headlines when he declared he could win a game of one-on-one against Caitlin Clark, professional basketball player and former Iowa Hawkeye.

Setting aside Austin Rivers's commentary on the crossover appeal of basketball/football players, Clark holds the all-time points record in both men's and women's college basketball. DeJean was a very good high school basketball player though, scoring more points in the state of Iowa than Carolina great Harrison Barnes, and recording more steals in the state of Iowa than Carolina great Marcus Paige.

So I set out to simulate DeJean's claim that if he lost, it would be by one or two. Using Clark's college senior year statistics at Iowa, compared to DeJean's high school senior year statistics at OABCIG, I simulated a game to 21 by ones and twos.

And he's right! I have Caitlin Clark winning 53.5% of the time by an average score of 21 to 20 - a very evenly matched game.

Notwithstanding the relative quality of competition, DeJean's high school statistics are fairly comparable to Clark's last year at Iowa - but where Clark wins out is her 3-Point Attempt Rate. Not her 3 Point percentage - Clark shot 37.8% her (college) senior year, compared to DeJean's 39.5%. But 60% of Clark's field goal attempts were threes - a ridiculously high volume compared to DeJean's 21.5%. 

Especially in a game of ones and twos, Clark's range and 3-point volume would give her the edge.

Thursday, December 3, 2020

How To Create a Simplex Linear Program Algorithm in Excel (Solver)

Calculating the optimal solution of a simplex linear program algorithm (simplex LP), using matrix math, by hand, is not that easy. But doing so in Excel, using Solver, is!

To illustrate, I'll calculate an optimal fantasy football lineup for this Sunday's Week 13 games. Of course, optimizing a simplex LP is straight-forward as long as the functions are linear - the hard part is devising an accurate projection system to maximize on. 

The Excel is linked here for downloadFirst, you'll need to load the Solver add-in. Then you'll need to identify:
  • Objective function (max, min, or equal to a value)
    • In this example, maximize projected fantasy points
  • Variables
    • In this example, binary variables identifying which players to draft
  • Constraints
    • In this example, a few:
      • Salary <= $50,000
      • Exact number of players in each position
      • All variables are binary
For doing this in Excel, using SUM and SUMPRODUCT are the building blocks to make sure the linearity constraint is satisfied. Additionally, SUMIF is very useful because it only allows for one criteria - while you can still violate linearity depending upon the criteria, SUMIF is easier for troubleshooting which formula broke your code (whereas SUMIFS has an unlimited number of criteria).


Column F contains our variables, column G contains our objective (maximize), and column J contains one of our constraints (maximize up to $50k).

Sunday, November 8, 2020

"What are the odds?" No NFL Team Has Played In the Super Bowl At Home

Every year, the Super Bowl is played at a different neutral site, determined years in advance. There have been 54 Super Bowls to date in 15 different cities, and yet no team has played in the game at their home venue. Just how unlikely is this, over the past 5+ decades?

I assumed each team had an equal chance of making the Super Bowl in a given season, and then went through the history of the league to determine the number of teams in each year. There are some wrinkles to account for over time, to ultimately calculate:

# possible teams at home * (# of teams to make the Super Bowl: 2 / # teams)

This can differ a given year if either the hosting venue has more than one tenet (such as MetLife Stadium), or the game was played at a site that wasn't home to an NFL team (such as the Rose Bowl).

1 - the above calculation gives the chance that the Super Bowl does not include the home tenet, and then multiplying this over every year gives the chances it hasn't happened yet: 3.3%

SeasonNumber# Playoff Teams# TeamsSB LocationHome?# Teams PossNo HomeRunningOdds
19661224Los Angeles, California1191.7%91.7%
19672225Miami, Florida1192.0%84.3%
19683226Miami, Florida1192.3%77.8%
19694226New Orleans, Louisiana1192.3%71.9%
19705826Miami, Florida1192.3%66.3%
19716826New Orleans, Louisiana1192.3%61.2%
19727826Los Angeles, California1192.3%56.5%
19738826Houston, Texas00100.0%56.5%
19749826New Orleans, Louisiana1192.3%52.2%
197510826Miami, Florida1192.3%48.2%
197611828Pasadena, California00100.0%48.2%
197712828New Orleans, Louisiana1192.9%44.7%
1978131028Miami, Florida1192.9%41.5%
1979141028Pasadena, California00100.0%41.5%
1980151028New Orleans, Louisiana1192.9%38.6%
1981161028Pontiac, Michigan1192.9%35.8%
1982171628Pasadena, California00100.0%35.8%
1983181028Tampa, Florida1192.9%33.2%
1984191028Stanford, California00100.0%33.2%
1985201028New Orleans, Louisiana1192.9%30.9%
1986211028Pasadena, California00100.0%30.9%
1987221028San Diego, California1192.9%28.7%
1988231028Miami, Florida1192.9%26.6%
1989241028New Orleans, Louisiana1192.9%24.7%
1990251228Tampa, Florida1192.9%23.0%
1991261228Minneapolis, Minnesota1192.9%21.3%
1992271228Pasadena, California00100.0%21.3%
1993281228Atlanta, Georgia1192.9%19.8%
1994291228Miami, Florida1192.9%18.4%
1995301230Tempe, Arizona1193.3%17.2%
1996311230New Orleans, Louisiana1193.3%16.0%
1997321230San Diego, California1193.3%14.9%
1998331230Miami, Florida1193.3%13.9%
1999341231Atlanta, Georgia1193.5%13.0%
2000351231Tampa, Florida1193.5%12.2%
2001361231New Orleans, Louisiana1193.5%11.4%
2002371232San Diego, California1193.8%10.7%
2003381232Houston, Texas1193.8%10.0%
2004391232Jacksonville, Florida1193.8%9.4%
2005401232Detroit, Michigan1193.8%8.8%
2006411232Miami Gardens, Florida1193.8%8.3%
2007421232Glendale, Arizona1193.8%7.8%
2008431232Tampa, Florida1193.8%7.3%
2009441232Miami Gardens, Florida1193.8%6.8%
2010451232Arlington, Texas1193.8%6.4%
2011461232Indianapolis, Indiana1193.8%6.0%
2012471232New Orleans, Louisiana1193.8%5.6%
2013481232East Rutherford, New Jersey1287.5%4.9%
2014491232Glendale, Arizona1193.8%4.6%
2015501232Santa Clara, California1193.8%4.3%
2016511232Houston, Texas1193.8%4.0%
2017521232Minneapolis, Minnesota1193.8%3.8%
2018531232Atlanta, Georgia1193.8%3.6%
2019541232Miami Gardens, Florida1193.8%3.3%
2020551432Tampa, Florida1193.8%3.1%
2021561432Inglewood, California1287.5%2.7%
2022571432Glendale, Arizona1193.8%2.6%
2023581432TBD1193.8%2.4%
2024591432New Orleans, Louisiana1193.8%2.3%

There is a reason the 1984 season is highlighted: the San Francisco 49ers won that Super Bowl, but the venue was Stanford Stadium - which was NOT their home stadium (which was Candlestick Park). That venue would be considered semi-home, and if the site would have been The Stick, this whole exercise would be moot.

This year the chances are pretty good, with the Tampa Bay Buccaneers currently tied for the best record in the NFC, and the Super Bowl held in Tampa. Which brings us to another wrinkle over recent history - Tom Brady.

The New England Patriots have had an incredible run over the past two decades, making 9 Super Bowls. But Foxborough, Massachusetts isn't in the rotation to host the game. So what if it was? What if Gillette Stadium replaced their AFC East counterparts' Dolphin Stadium?

The Patriots didn't make any of the 3 games played in South Florida. But as I previously determined, their "generic" odds of reaching the game were ~25% in any given year over the past 19 seasons.

If I apply this to the imaginary Foxborough years (Miami years in real life), the odds that no team would have played in the Super Bowl at home gets cut in half, to 1.7%.

SeasonNumber# Playoff Teams# TeamsSB LocationHome?# Teams PossNo HomeRunningOddsNEP?
2001361231New Orleans, Louisiana1193.5%11.4%1
2002371232San Diego, California1193.8%10.7%0
2003381232Houston, Texas1193.8%10.0%1
2004391232Jacksonville, Florida1193.8%9.4%1
2005401232Detroit, Michigan1193.8%8.8%0
2006411232Foxborough, Massachusetts1174.9%6.6%0
2007421232Glendale, Arizona1193.8%6.2%1
2008431232Tampa, Florida1193.8%5.8%0
2009441232Foxborough, Massachusetts1174.9%4.3%0
2010451232Arlington, Texas1193.8%4.1%0
2011461232Indianapolis, Indiana1193.8%3.8%1
2012471232New Orleans, Louisiana1193.8%3.6%0
2013481232East Rutherford, New Jersey1287.5%3.1%0
2014491232Glendale, Arizona1193.8%2.9%1
2015501232Santa Clara, California1193.8%2.8%0
2016511232Houston, Texas1193.8%2.6%1
2017521232Minneapolis, Minnesota1193.8%2.4%1
2018531232Atlanta, Georgia1193.8%2.3%1
2019541232Foxborough, Massachusetts1174.9%1.7%0