Geno’s Minor League Mashup Week 8: A Trip to Monte Carlo
This is the week we’ve all been pushing for. The final teams will be clinching playoff spots and those players prepare for extra football. When Geno asked me to fill in, I started thinking about what goes into this extra football. Some of us might not have never experienced the “big game” in football, or any sport, so I turned to some pros to give us our pre-game pep talks based on the current standings entering Week 8.
1st – “When you win, nothing hurts.” – Joe Namath
2nd – “Nobody who ever gave his best regretted it.” – George Halas
3rd – “To play this game you must have fire in you, and there is nothing that stokes fire like hate.” – Vince Lombardi
4th – “You need to play with supreme confidence, or else you’ll lose again, and then losing becomes a habit.” – Joe Paterno
5th – "I don’t think it’s about who you play, I think it’s about who you are." – Nick Saban
6th – "Football is a game of errors. The team that makes the fewest errors in a game usually wins." – Paul Brown
7th – "Football is a game of errors. The team that makes the fewest errors in a game usually wins." – Mike Singletary
8th – "Don’t worry about it. It’s just a bunch of guys with an odd-shaped ball." – Bill Parcells
Since Cam already went over the playoff scenarios and how each team could reach the possible spots in the standings, I’ll just throw out the chaos game of the week. It’s Annapolis at Madison, with a heaping side order of Albuquerque at Lincoln. Sure, the other two games matter, but only in the context of final placement. These 4 teams are fighting for their season… well, 3 teams in these two games are anyway.
Since Cam stole my literary thunder this week, I thought it’d be fun to run a couple Monte Carlo Simulation for the remaining week and we can see what the outcome based simply on statistical analysis. So, buckle up your chin straps, let’s get our geek on for a minute.
For those that don’t know, here is an elementary school explanation of a Monte Carlo simulation, thanks to ChatGPT:
Imagine you have a jar filled with red and blue marbles, but you don't know exactly how many of each. You want to find out the approximate ratio of red to blue marbles without counting them all.
To do that, you decide to play a game. You randomly pick a marble from the jar, note its color, and put it back. Then you repeat this process many, many times.
After playing the game many times, you can look at the results and see how many times you picked a red marble and how many times you picked a blue marble. By counting these occurrences, you can estimate the ratio of red to blue marbles in the jar.
This process is called a Monte Carlo simulation. It involves repeating a random experiment many times to get an idea of the possible outcomes and make estimations or predictions.
In more advanced scenarios, Monte Carlo simulations are used in different fields, such as finance, physics, or computer science. They help researchers and scientists understand the likelihood of certain events, simulate complex systems, or solve problems when there's uncertainty involved.
But at its core, a Monte Carlo simulation is like playing a game with a jar of marbles to make an educated guess about something you don't know for sure.
So basically, we are going to run an absurd number of simulations of Week 8 to see what teams make the playoffs and their ranking based on win percentage. 1000 iterations of Week 8 outcomes should do it. To do this effectively we get the standard deviation based on the scores of EVERY game already played and consider the points every team has scored and have allowed opponents to score. The results of the 1000 iterations showed the following:
Even more so I wondered what this data would’ve looked like had I run this simulation at Week 5:
Obviously, the more data that can be put into the simulation, the more granular the output. For example, that 1/100th point of space between the Cavalry & the Grizzlies only appeared at 1000 iterations. At 100 iterations they were both sitting at 0.188. So, what can we determine from this. Weeks 6 & 7 were fire for sure! A play or two one way or the other and we’d have a bit different of a field. At Week 5 there was a logjam at 3-2, and unfortunately, Lincoln was coming in scoring just 101 points for, with the Flight, Navigators, and Lynx scoring more (123, 111, & 109). This was enough for the scenarios run to create too large of a point deficit in each game for them to win the scoring fight each week. Those last three weeks were brutal in the scenarios too… where everyone who played a game that would create broader separation in the polls, failed to win it.
Lastly, here’s what the Monte Carlo simulation says (again, after 1000 iterations of each contest) will be the outcome of all the Week 8 contests:
If these scores hold up, the playoff landscape should, based on all the tie breakers, be Madison at Lexington and Annapolis at Lincoln; the great and powerful Monte Carlo has willed it so!
It was cool to see this play out, but as the old saying goes… Any given Sunday… or Saturday… right? The one thing that this Monte Carlo simulator doesn’t account for with how I built it, was APF will always APF, and that’s why we play the games. I am going to attempt to rework my Monte Carlo simulator for the next SFL season, just to see how it holds up as the season progresses.
Best of luck in Week 8, the combine, the playoffs, and the draft… it’s been a privilege to play alongside ya’ll in Season 7, and I know everyone will do great things in the pros!
Week 8 Predictions
Geno's Record: Week 7 - 3-0 ---> Total 10-8 (.556)
TJ's Record: Week 7 - 2-2 ---> Total 10-14 (.417)
Jay's Record: Week 7 - 3-1 ---> Total 8-5 (.615)
Slinn's Record: Week 7 - 2-2 ---> Total 8-4 (.667)
Total Prediction Record: Week 7 10-5 ---> Total 38-32 (.543)
But first, we have John Fullerton’s WORK HARD PLAY HARD Player (or Team) of the Week!
What is going on!?, I am back with my WHPH Segment. I wanna switch things up for this week however. I think instead of 1 Player I'm gonna pick a Team.
I wanna recognize the Ottawa Cavalry! Going into their Matchup facing the #2 4-2 Madison Lynx , The Cavalry had a 0-6 Record with being #8 in the Rankings. Even on paper, Madison was favored to win. I even called it in the Predictions. Well obviously, Ottawa told me to shut up and every other hater out there. This team worked together to get that 1st W of the Season!
It just seemed like the whole team was ready to get that 1st Win. QB Mccall had over 400 Yards Passing with a Comp % of .78! TE Mihata had a season high with 117 Receiving and 1 Tuddy! RB Sammons was having a little difficulty running that ball so then decided to help push this team by having a Season High of 82 Yards Receiving. Then on Defense, Ryan was everywhere with 6 Tackles and 1 INT. Can't forget about Towers who also had an INT. Leopold also put that pressure on with 1 Sack. I mean just looking at the stats from this game, Ottawa wanted to shine and not have an unfortunate winless season. When you Work Hard you Play Hard.
All I can say is, from someone who had a pretty bad season last year with the Rattlesnakes, keep your head up Cavalry. Finish the season strong, keep putting the work in at the gym, continue to spread your name out there, and just realize that your journey in the SFL has just begun!
#EasyMoney
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Predictions:
Tacoma @ Ottawa
Geno: Ottawa 24-21
Slinn: Ottawa 18-10
John: Sorry The Jacksons ooooooo, But Ottawa over Tacoma: 24 – 17
TJ: Ottawa 24-17
Lexington @ San Jose
Geno: Lexington 28-17
Slinn: San Jose 35-31
John: San Jose doesn't want a Repeat of Week 1 Facing Lexington: 27-20
TJ: San Jose 27-26
Annapolis @ Madison
Geno: NO PICK
Slinn: Madison 25-16
John: Watch Out Madison is Mad Annapolis: 27-17
TJ: Madison 24-21
Albuquerque @ Lincoln
Geno: Atoms 17-14
Slinn: Lincoln 19-15
John: Rattlesnakes Take The W and 1st Spot!!: 30-20
TJ: Lincoln 22-19
“Confidence doesn't come out of nowhere. It's a result of something ... hours and days and weeks and years of constant work and dedication.” – Roger Staubach