Does Florida State have the toughest schedule in the nation? Plus, how do professional gamblers break down a team's schedule in the preseason: Using proportional win shares to predict a team's final record

As the top 25 polls continue to trickle out and anticipation mounts as August approaches, I began to think about the Nation's most difficult schedules.  Schedule plays a huge role in a teams success-- probably a much larger role than anyone wants to admit.  Why?  Schedule is largely out of a team's immediate control.  90% of schedules are made years in advance, with only a non-conference game or two to be decided in the year before the current season.  Last season, we noted that UGA's schedule was much too tough to make a serious run at the National Championship.  Unfortunately for our prediction (and for UGA's title hopes), massive injuries derailed the Bulldog's season long before their attrition heavy schedule could catch up with them. 

My curiosity further spikes when ESPN's ACC Blogger, Heather Dinich posted her Dream 13 week ACC Road Trip.  13 games in 13 weeks, and the 'Noles are involved in 7 of them!  That's right, ESPN's ACC blogger is calling 7 of the 8 Seminole ACC matchups the game of the week.  That doesn't include a trip to the Swamp to face the odds-on favorite for the National Championship, the Florida Gators. 

Here's more on the 'Noles schedule:

  • 11 of the 'Noles 12 opponents played in bowl games last year.  I couldn't find any other team with more than 9. 
  • The 'Noles play only 6 home games.  Last year, they played 8. 
  • At least 5 and as many as 7 of the 'Noles opponents figure to be ranked teams.  Show me another team that's likely to play half of their games against ranked teams.  

Why does this matter?

Realistic prognostications and expectations. 

Date Opponent Result

Sep. 7 Miami-FL TBA
Sep. 12 Jacksonville St. TBA

Sep. 19 at BYU TBA
Sep. 26 South Florida TBA
Oct. 3 at Boston College TBA
Oct. 10 Georgia Tech TBA
Oct. 22 at North Carolina TBA
Oct. 31 NC State TBA
Nov. 7 at Clemson TBA
Nov. 14 at Wake Forest TBA
Nov. 21 Maryland TBA
Nov. 28 at Florida TBA

There just aren't any breaks in that schedule.  FSU starts with a mega-rivalry game on labor day night, then play a cross-country game at an experienced BYU team, followed by a game against USF that the 'Noles could easily overlook.  The 'Noles then finish with 6 of their remaining 9 games on the road.

I posted this today to remind people to form reasonable expectations, and I want to show you how those reasonable expectations can go awry.  

For instance, here's an excerpt from a recent conversation I had with a friend who is a big FSU fan.  I asked him to predict our season.  

Sep. 7 Miami-FL WIN
Sep. 12 Jacksonville St. WIN 

Sep. 19 at BYU LOSS
Sep. 26 South Florida WIN
Oct. 3 at Boston College WIN
Oct. 10 Georgia Tech WIN
Oct. 22 at North Carolina LOSS
Oct. 31 NC State WIN
Nov. 7 at Clemson WIN
Nov. 14 at Wake Forest WIN
Nov. 21 Maryland WIN
Nov. 28 at Florida LOSS

He went with 9-3.  That's a common prediction I've seen by FSU fans this offseason.  It would also be an amazing season for the 'Noles. 

The error my friend is making is that he is making definitive all of nothing calls on games that are anything but locks.  Football games are not 100%/ 0% probabilities (typically).  Now, could my friend be right?  Absolutely, but his methodology is suboptimal at best.  

It just so happens I have a friend of mine who is a professional gambler.  He has a day job, but he makes his living betting sports like a day trader plays the stock market, complete with a healthy dose of arbitrage.  Every year since my freshman year of college, we've gotten together and broken down the upcoming season, and we have a method.  We call it proportional win shares.  You can call it whatever you want, but I think you'll see how it's more effective than simply assigning "win" or "loss" to the games. 

The idea is simple:  assign a winning % to each game.  For instance, you could say that FSU has an 80% chance of beating Maryland (0.80), of that they have a 20% chance to beat UF (0.20).

Now, you might be thinking, "how do you project a team's winning percentage?"  This chart can help:

Point Spread Money Line
-2 -120/+120
-2.5 -130/+130
-3 -145/+145
-3.5 -175/+175
-4 -185/+185
-4.5 -200/+200
-5/-5.5 -215/+215
-6 -240/+240
-6.5 -260/+260
-7 -290/+290
-7.5/-8/-8.5 -330/+330
-9/-9.5 -350/+350
-10 -385/+385
-10.5 -415/+415
-11 -445/+445
-11.5 -475/+475
-12/ -12.5
-13 -525/+525
-13.5 -550/+550
-14 -580/+580
-14.5 -610/+610
-15/ 15.5 -640/+640
-16/16.5 -665/+665
-17 -690/+690
-18/ -18.5/ -19/ -19.5 -740/+740
-20 -770/+770
-20.5 -800/+800
-21 -815/+815
-21.5 -830/+830
-23 -845/+845
-24 -875/+875


You might be a bit lost right now, but that's okay.  Here's the idea.  A 3 point underdog, has a moneyline value of "+145".  In numerical terms, that comes out to 245, because you add 100.  Still with me?  If not, it's okay.  Keep following.  To determine a team's projected winning percentage, based on the vegas line, simply take the moneyline value in numerical terms, and divide it into one.

  • Team A is favored over Team B by 3 points.
  • Thus, Team B is an underdog of 3 points.
  • Team B can be referred to as +3
  • Using the chart above, we can see that an underdog of +3 is "+145" moneyline value.
  • Remember to add 100 to the "145", to get "245".
  • Then, divide 100 (always 100 here) by 245.
  • 100/245= 0.408, which we will round to 0.41
  • 0.41 is the same thing as 41%.
  • So, Team B (the 3 point underdog) has a 41% chance of winning this game.
  • If Team B has a 41% chance of winning, then Team A must have a 59% chance of winning (because these numbers must add up to 100%) 

Why does any of this matter?  Let's get back to our friend who picked the games using the win/loss method.  I asked him how certain he was that FSU would lose the North Carolina game, or how certain he was that FSU would win the Georgia Tech game.  Did he think FSU would lose the Carolina game 100% of the time?  No.  Did he think FSU would win the Georgia Tech game 100% of the time?  Definitely not.  I got him to admit that he thought these games were slightly better than tossups, or coin flips if you will.  He was beginning to realize why his (and most preseason) predictions could be seriously wrong:  because they are dealing in absolutes.

That's where the more advanced method really comes in handy.  I asked him to project a winning % for each FSU game.  Here's what he came back with

Sep. 7 Miami-FL 75%
Sep. 12 Jacksonville St. 100%

Sep. 19 at BYU 45%
Sep. 26 South Florida 80%
Oct. 3 at Boston College 85%
Oct. 10 Georgia Tech 60%
Oct. 22 at North Carolina 40%
Oct. 31 NC State 65%
Nov. 7 at Clemson 65%
Nov. 14 at Wake Forest 75%
Nov. 21 Maryland 95%
Nov. 28 at Florida 0%

Already, he could see that this new method was more realistic, though harsh.  He had projected the Noles to win 7.9 games by this method, a full game less than he had using his win/loss method.  But there was still a problem.  He couldn't see it.  Can you?  Scroll down.  





Realistic expectations.

I presented these  ideas to my friend and he agreed with most of them.  See what you think:

  • FSU won't be favored by more than a touchdown against Miami.  5 is the most it's been in the past half decade.
  • Jacksonville State is not a 100% lock after the Appalachian State- Michigan game.  Call it 99%
  • He called BYU a loss, but gave FSU a 45% chance to win.  That's a pretty definitive call to make on what is a de facto coin flip.  Ditto the UNC game and the Georgia Tech game.
  • Boston College isn't an 85% type game.  The last time FSU traveled that far and was that heavily favored?  Syracuse, 2004.  10 point favorites seem a lot more likely than 15. 
  • FSU won't be favored by 30 against Maryland, regardless of last year's score, but that's what a 95% projected winning % implies. 17 points is enormous for a conference game (87%); 30 is unfathomable.  
  • Finally, UF.  Will FSU lose this game?  Almost certainly.  Is there any chance FSU wins?  Of course.  Think injuries or good bounces, or both!  What's reasonable?  Probably somewhere between 17 and 20 point underdogs, giving the 'Noles between a 10 and unlucky (for the gators) 13% chance of winning.

After accepting my recommendations, here's what his final looked like:

Sep. 7 Miami-FL 68%
Sep. 12 Jacksonville St. 99%

Sep. 19 at BYU 45%
Sep. 26 South Florida 80%
Oct. 3 at Boston College 80%
Oct. 10 Georgia Tech 60%
Oct. 22 at North Carolina 40%
Oct. 31 NC State 65%
Nov. 7 at Clemson 65%
Nov. 14 at Wake Forest 75%
Nov. 21 Maryland 87%
Nov. 28 at Florida 13%

Even though he had the 'Noles favored to win 9 of thier 12 games, his final tally came out to 7.77 wins, which implies that the 'Noles are more likely to win 8 than 7, more likely to win 9 than 6, etc..  The reason, of course, is that most of the games will feature the 'Noles as small favorites.  In the ACC, with their conservative, defensive natured head coaches and defensive talent rich rosters (most NFL talent over last 5 years, and overwhelmingly on the defensive side), games are often close.  Blowouts are rare.  With FSU's schedule particularly, there is a distinct lack of Gimme's.  A team like Texas, playing four directional schools, likely would garner 4 games in which they have a 95+% chance to win.  Those games (or the lack thereof) really add up.

We can look to the past and use it to guide us.  After a while, you can begin to sense when you are incorrectly gauging a team's chance to win a game.  Ask yourself, "would Team A really beat Team B 75 out of 100 times?"  If the answer is "probably not", then your 75% projected winning percentage for team A is too high and doesn't mesh with your beliefs.     Hopefully this exercise will help you to better handicap your team's chances in the upcoming season.  I'm not ready to give my exact predictions yet and I'd be skeptical of anyone who is offering definitive predictions at this point as there is so much yet to happen this offseason, but I will certainly try to use the best method possible when handicapping the upcoming season.  I hope you do as well. 

On that note, let's take a poll.  We'll have a question every day through the end of May.  Then we will follow up in June, and at the end of July.  It should be interesting to see how the opinions of our readers change over the course of these three short months.

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