## McShay vs Kiper : Who won?

For the last two months all we've been hearing is Todd McShay's and Mel Kiper Jr.'s draft projections. It's like that every year around this time, but I realized we never hear the results. All the debates and opinions thrown around, and then we completely forget about them. Not anymore, here are the results of the 1st round of the 2013 NFL Draft, along with final scores for each guy.

Pick
Team
McShay
Kiper
Acutal
1Kansas CityEric Fisher (OT - Central Michigan)Eric Fisher (OT - Central Michigan)Eric Fisher (OT - Central Michigan)
2JacksonvilleDion Jordan (DE - Oregon)Luke Joeckel (OT - Texas A&M)Luke Joeckel (OT - Texas A&M)
3OaklandSharrif Floyd (DT - Florida)Sharrif Floyd (DT - Florida)Dion Jordan (DE - Oregon)
4PhiladelphiaLane Johnson (OT - Oklahoma)Lane Johnson (OT - Oklahoma)Lane Johnson (OT - Oklahoma)
5DetroitEzekiel Ansah (DE - BYU)Ezekiel Ansah (DE - BYU)Ezekiel Ansah (DE - BYU)
6ClevelandGeno Smith (QB - WVU)Dee Milliner (CB - Alabama)Barkevious Mingo (DE - LSU)
7ArizonaJonathan Cooper (G - UNC)Dion Jordan (DE - Oregon)Jonathan Cooper (G - UNC)
8BuffaloRyan Nassib (QB - Syracuse)Jonathan Cooper (G - UNC)Tavon Austin (WR - WVU)
9New York JetsTyler Eifert (TE - Notre Dame)Barkevious Mingo (DE - LSU)Dee Milliner (CB - Alabama)
10TennesseeDee Milliner (CB - Alabama)Sheldon Richardson (DT - Missouri)Chance Warmack (G - Alabama)
11San DiegoLuke Joeckel (OT - Texas A&M)DJ Fluker (OT - Alabama)DJ Fluker (OT - Alabama)
12MiamiDJ Fluker (OT - Alabama)Chance Warmack (G - Alabama)DJ Hayden (CB - Houston)
13New York JetsChance Warmack (G - Alabama)Tavon Austin (WR - WVU)Sheldon Richardson (DT - Missouri)
14CarolinaStar Lotulelei (DT - Utah)Star Lotulelei (DT - Utah)Star Lotulelei (DT - Utah)
15New OrleansBarkevious Mingo (DE - LSU)Jarvis Jones (LB - Georgia)Kenny Vaccaro (S - Texas)
16St. LouisTavon Austin (WR - WVU)Kenny Vaccaro (S - Texas)EJ Manuel (QB - FSU)
17PittsburghJarvis Jones (LB - Georgia)Tyler Eifert (TE - Notre Dame)Jarvis Jones (LB - Georgia)
18DallasSheldon Richardson (DT - Missouri)Sylvester Williams (DT - UNC)Eric Reid (S - LSU)
19New York GiantsBjoern Werner (DE - FSU)DJ Hayden (CB - Houston)Justin Pugh (OT - Syracuse)
20ChicagoManti Te'o (LB - Notre Dame)Manti Te'o (LB - Notre Dame)Kyle Long (G - Oregon)
21CincinnatiEddie Lacy (RB - Alabama)Eddie Lacy (RB - Alabama)Tyler Eifert (TE - Notre Dame)
22St. LouisKenny Vaccaro (S - Texas)Cordarrelle Patterson (WR - Tennessee)Desmond Trufant (CB - Washington)
23MinnesotaSylvester Williams (DT - UNC)Robert Woods (WR - USC)Sharrif Floyd (DT - Florida)
24IndianapolisDJ Hayden (CB - Houston)Xavier Rhodes (CB - FSU)Bjoern Werner (DE - FSU)
25MinnesotaAlec Ogletree (LB - Georgia)Alec Ogletree (LB - Georgia)Xavier Rhodes (CB - FSU)
26Green BayJustin Pugh (OT - Syracuse)Datone Jones (DE - UCLA)Datone Jones (DE - UCLA)
27HoustonJustin Hunter (WR - Tennessee)DeAndre Hopkins (WR - Clemson)DeAndre Hopkins (WR - Clemson)
28DenverDatone Jones (DE - UCLA)Tank Carradine (DE - FSU)Sylvester Williams (DT - UNC)
29New EnglandXavier Rhodes (CB - FSU)Desmond Trufant (CB - Washington)Cordarrelle Patterson (WR - Tennessee)
30AtlantaDesmond Trufant (CB - Washington)Robert Alford (CB - SE Louisiana)Alec Ogletree (LB - Georgia)
31San FranciscoEric Reid (S - LSU)Eric Reid (S - LSU)Travis Frederick (OL - Wisconsin)
32BaltimoreMatt Elam (S - Florida)Kevin Minter (LB - LSU)Matt Elam (S - Florida)

So here are the final scores, purely for reference:

Mel Kiper Jr. : 8/32 (25%)

Todd McShay : 7/32 (22%)

Note: Obviously during the draft teams trade picks; this is not accounted for in the projections. However, the projected picks should be recognized. For example, St. Louis was scheduled to have the 16th overall pick, but they traded with Buffalo to move that up to the 8th pick. They ended up picking Tavon Austin then, who Todd McShay projected they would pick when their pick came around. Taking these situations into account here are the adjusted scores for the two "experts" in the first round; adjusted players in parentheses:

Mel Kiper Jr. : 9/32 (28%) (Eric Reid)

Todd McShay : 10/32 (31%) (Tavon Austin, Eric Reid, Desmond Trufant)

## How To Quickly Defrost Frozen French Fries

Seeing as hot dogs are my favorite food, I often like to indulge with some french fries on the side. However, also seeing as how I'm cheap, I buy the frozen ones and reseal them and put them back in the freezer when I'm done. Anyone else who has done this knows that every time you go to make fries you get some frozen mess that looks something like this:

Now what am I supposed to do with that? For decades I had struggled with this and ended up with soggy fries, until one day I thought of it. Here are the steps that will save your life one day (don't ask me how).

## How to win your NCAA bracket with math!

I love sports. I watch a lot of sports. But there is no way I'm going to sit here and tell you I've even seen half of these teams in the NCAA tournament play, and yet I will fill out a bracket and swear up and down that I have it right. I am probably describing a lot of bracket-filler-outers here, and I am proposing a new way to fill one out to maximize your chances of winning your office pool. I'm not picking by seed, not picking by mascot color, not even picking against the schools that those annoying kids in high school went to. We're talking math here folks.

Math, specifically Bayesian Statistics. Assuming you have a machine that can pit any two teams against each other and determine a probability of winning (this is a very large assumption, I know, more on this later), you can actually determine the probability that any team makes it to any round of the tournament.

Example: The odds that a 1 seed makes it to the Sweet 16 (these might be lower than you think).
What needs to happen for this is a couple of things, first of all, the 1 seed has to win it's opening matchup (1 vs 16). Then, the 1 seed needs to win its second round matchup, which will be either against the 8 seed or the 9 seed. So in this case, we will need to run two probabilities, the one that 1 beats 8 and the one that 1 beats 9, and then weight them with the probability that each opponent makes it there (we know this because we know P(8 beats 9)). So we end up with the following formula for the probability (P) that the 1 seed makes it through the opening weekend to the Sweet 16 (let W(X,Y) be the probability that X beats Y):

$\mathfrak{\mathit{P\ =\ W(1,16)\ [W(8,9)\ W(1,8)\ +\ W(9,8)\ W(1,9)]}}$

Obviously, this equation will get quite long for the later rounds so it's probably best if you write or use a program to create these calculations for you. What you end up with is a list of every team and the probability that each team makes it to each round of the tournament.

Here's where it gets fun. ESPN is nice and puts out a list of the percentage of people that pick each team to make it to each round, so we can directly compare these percentages. The theory behind this being that if a team has a 30% shot of making it to the Elite 8, but 45% of people pick that team to get there, your expected value by picking them is pretty low. We are looking to find (especially in a season full of upsets like we had this year) the teams that have a decent shot that no one is picking for some reason or another. You can check out the full list and breakdown on this spreadsheet but I'll give you the highlights here.

Final Four - Probability of making it vs. the number of people who think they will

Team
Actual Probability
Pick Percentage
Difference
(1) Louisville38.8751.50-12.63
(1) Indiana37.4744.80-7.33
(1) Gonzaga29.9826.903.08
(1) Kansas27.0834.50-7.42
(3) Florida26.4317.409.03
(2) Ohio State21.3143.10-21.79
(2) Duke20.1224.10-3.98
(2) Miami (FL)17.8036.60-18.80
(2) Georgetown16.2924.70-8.41
(4) Syracuse13.398.504.89
(4) Michigan12.8514.00-1.15
(3) Michigan St12.5015.10-2.60
(3) New Mexico10.969.301.66
(5) Wisconsin8.799.60-0.81
(3) Marquette8.773.804.97
(4) Saint Louis6.983.503.48
(8) Pittsburgh6.780.905.88
(6) Arizona6.312.204.11
(4) Kansas State6.154.102.05
(5) UNLV5.050.804.25
(5) VCU4.753.601.15
(5) Oklahoma St4.361.303.06
(7) Creighton4.330.703.63
(6) Butler4.142.401.74
(8) NC State3.911.002.91
(6) Memphis3.531.302.23
(7) Notre Dame3.271.501.77
(8) UNC3.252.300.95
(7) Illinois3.220.702.52
(7) San Diego St2.810.302.51
(9) Missouri2.470.501.97
(6) UCLA1.981.100.88
(11) Minnesota1.960.601.36
(10) Iowa State1.960.501.46
(11) MTSU/SMC1.910.101.81
(10) Cincinnati1.660.301.36
(9) Wichita State1.540.301.24
(11) Bucknell1.260.201.06
(12) Ole Miss1.220.900.32
(12) Oregon1.220.700.52
(9) Temple1.200.201.00
(12) California1.080.200.88
(10) Oklahoma1.050.200.85
(11) Belmont0.990.200.79
(9) Villanova0.930.500.43
(13) BSU/LaSalle0.580.100.48
(14) Davidson0.560.200.36
(12) Akron0.480.100.38
(14) Valparaiso0.180.100.08
(15) Pacific0.130.100.03
(13) N Mexico St0.120.100.02
(15) Iona0.090.10-0.01
(13) SD State0.080.10-0.02
(14) Harvard0.070.20-0.13
(13) Montana0.050.10-0.05
(15) Florida Gulf0.030.10-0.07
(15) Albany0.020.10-0.08
(14) NW State0.020.10-0.08
(16) LIU0.010.30-0.29
(16) NCAT/Lbrty0.000.30-0.30
(16) W Kentucky0.000.40-0.40
(16) Southern U0.000.30-0.30

Notice that even though the four 1-seeds have the highest actual probability of making it, they also have some of the highest pick percentages, making them not a very good value for you. If one of them makes it, whoopdie-do, you got it right, so did everyone else. Remember, we're going for expected value here. A team like (3) Florida may be a great Final 4 pick, they've got better than a 1 in 4 shot of making it but only 1 in 6 people are picking them to go there. You can do the same thing for the earlier rounds, check out the spreadsheet linked above. Spoiler alert: (7) Creighton and (8) Pitt in the Elite-8.

Now obviously the biggest problem with this method is the reliance on these "actual probabilities." If someone could come up with a fool-proof method of computing these they'd probably be rich and living on an island by now. But that doesn't mean people aren't trying. The beauty of this method is that you can plug in any formula for probability that you like. A quick Google search will yield you dozens of people that will attempt to do it. For this example, I used TeamRankings and their matchup predictor. They take several factors into account and normally make you pay for it, but due to some lazy programming on their end you can pretty much find any matchup you want if you know what you're doing. You can modify the program used to gather all the matchups if you want.

This is just a concept, I have never actually used this (but I will be using it this year, hopefully no one who is in my pool is reading this...). I'm open to suggestions, let's see what happens. Cross your fingers for no 1-seeds in the Final 4!

## Sinful Lyrics - A First Look at the Genesis Framework

Well, it's up! The new site I've been working on for the last couple weeks in my spare time (Sinful Lyrics) is officially live. It basically follows a blog format with each post featuring a lyric from a popular song with some seriously bad lyrics. The site has "7 Deadly Sins of Lyrics" and each song violates one or more of the sins.

The most interesting part of the project for me was getting exposure to the Genesis Framework for WordPress. I had researched both Genesis and Thesis (these seem to be the two front-runners in the industry) and ultimately settled on Genesis. I will probably post more details and specific experiences with the framework down the road but I have to say my overall experience was a positive one.

## Welcome Back

So if you are one of the 30 people that visited my site last year, you will notice the new design. I'm going for something a little simpler and plan to actually update this site occasionally now. In fact, I'm so committed that I deleted all of my previous blog posts (except for my most popular one of course). Check back, subscribe, and definitely tell me how much you love the site in the comments.