The Next Great QB Debate

For what seems like 20 years now, the QB debate has been between Brady and Manning. Sure, Aaron Rodgers and Drew Brees have snuck into conversations when looking at an individual season, but Manning and Brady in some form or another been at the top of mountain when discussing great QBs. The debate has always centered around Manning’s video game numbers against Brady’s lack of supporting offense and Super Bowl rings.

The Picture of Tom Brady...

A stud on and off the field.

Interestingly enough, there are two young stud QBs who are starting to shape the next great debate. Hell, one of them even plays for the team Manning did! Already, the debate is taking a very similar narrative to that of the Brady vs Manning debate. We are going to look at these two QBs and see if the debate is warranted.

By the way, if you didn’t know it was Andrew Luck vs Russell Wilson, you do now.

Andrew Luck

He’s happy to be here.

Rookie Year

Lets start off by looking at the respective signal caller’s rookie campaigns. As always, I love the stats used from Football Outsiders. DYAR (defense adjusted yards above replacement) offers a look at total value, while DVOA (defense adjusted value over average player) gives us a glimpse at value on a per play basis. Both of these ranks above an average play.

Andrew Luck for BodyArmor Superdrink photo by Monte Isom #monteisom

Already a damn good QB.

Andrew Luck posted a 54.1% completion percentage while throwing 23 TDs to 18 INTs, his rookie year. Pretty good numbers for a rookie thrown into an immediate head of the offense role. Luck also had a nice number of 5 rushing TDs. While these are nice numbers on their own, we need more context, and this is where the DYAR and DVOA come into play.

Luck ranked 19th with 194 DYAR and 19 with a -5.1% DVOA. Not so hot. While Luck did put up some nice numbers and lead his team to the playoffs, he was pretty much an overall league average QB for his rookie year. This isn’t a bad thing because he was a rookie against 10 year veterans at the hardest position in sports.

Now, onto Wilson. Wilson had a 64.1% completion percentage while throwing 26 TDs against 10 INTs. That is pretty impressive. Although, we must point out Luck had over 200 more attempts than Wilson. Wilson also added in 4 rushing TDs. This looks very impressive, but alas, we need to look at advanced metrics.

Wilson posted an 872 DYAR for an impressive 8th ranking and absurd 19.7% DVOA, which is good for 6th…in the entire league! Not to mention, Wilson also went to the playoffs. While Wilson was not the main guy for his offense, he was already on par for league elite efficiency.

Rookie Year Edge – Wilson, by a fair margin.

Sophomore Compaign

Andrew Luck saw his completion percentage jump to the elite company level of 60.2%. He also cut way down on his interceptions from 18 to 9, while throwing for 23 TDs again. Luck ran for about 80 more yards and added in 4 more rushing TDs. Again, pretty impressive numbers that seem to mark improvement. So onto the advanced metrics.

Andrew Luck saw some improvement in his advanced stats, as he saw in his normal ones. He now ranked 14th in DYAR with 650. His DVOA also rose to 16 with a DVOA of 4.6%. Again, Luck has shown improvement, but the league overall showed some improvement as well at the QB position. However, he is getting better and turning the ball over less. It must also be noted Luck throws the ball a ridiculous amount and is saddled with Trent fucking Richardson as a running back. Needless to say, he doesn’t have the talent Wilson has. Still, you have to be efficient. But his progress is what you look for in the 2nd year.

Lets just get this out of the way, Wilson won a Super Bowl and was pretty good in the game. This automatically gives him the edge. But, lets look at the stats to see if he improved upon his already top 10-QB-in-the-league performance.

RUSSELL WILSON

Wilson telling Manning to have a seat.

Wilson had a 63.1% completion percentage while throwing 26 TDs to 9 INTs. Basically, he had the same exact year throwing the ball. He did rush for more yards but only added 1 rushing TD.

Wilson saw his DYAR of of 770 for a ranking 0f 12th in the league. His DVOA was 25.4% for a ranking of 8th. While he had the same season, the league got better around him. This isn’t really the worst thing, as he is still performing as a top 10 QB. Oh yeah, who also happened to win the Super Bowl.

Sophmore year winner – Wilson, by a fair margin, again.

RUSSELL WILSON

Yeah, he is pretty good at reading a defense.

This Year

Through 3 games, Luck is completing a ridiculous 68.3% completion percentage while throwing 9 TDs and 3 INTs. He also added in a rushing TD for good measure.

His advanced stats are still climbing, and he is poised to be in top 10 territory. His DYAR is 225 for a rank of 6. His DVOA is 13.4 for a ranking of 11. Again, Luck has improved every year while unquestionably being the only reliable option on offense. This is what you look for in a superstar. It took him 3 years, but he is now in the top 10 and has shown signs of getting better and better.

Wilson is also passing for a ridiculous 69% completion percentage. Throwing for 6 TDs and 1 INT while not yet running for a TD.

Russell Wilson

Great, Wilson is catching passes now.

His DYAR is 103, falling to 16th. And his DVOA 5.2% falling him all the way to 18th. While he has been good at face value, his advanced metrics say he has falling to the middle of the pack so far.

This year leader: Luck.

Colts QB Andrew Luck avoids LB Perry Riley and looks to throw.

So, Who is the Winner?

As of right now, Wilson owns this debate. He has had the better numbers and has won a Super Bowl. However, Luck is showing a pattern of getting better and better every year. I have a striking feeling Luck may even the playing field by years end or by next year. This is going to be awesome going forward. One thing is for sure, we are all winners being able to watch the next 2 Great Quarterbacks.

Expectations and Realities: Week 4 AP Top 25 College Football Teams

Welcome to the 4th week of breaking down the top 25 teams’ performance compared to their expectations as predicted by vegasinsiders.com. Results from previous weeks can be found at the bottom.

This week Louisville and Virginia Tech fell out of the top 25 and will not be included in this week’s results. Instead they will be replaced with Nebraska and Oklahoma State.

Week 4 Results

In the Table 1 and Figure 1 below you will find the 25 teams ranked in the AP preseason poll, the predicted spread, the actual result, and the percent error. The teams are sorted based on how well the team performed based on the spread for that game. Teams with a positive percent error performed better than expected, or covered the spread, while teams with a negative percent error underperformed, or did not cover the spread. Note: this is not a measure if a team won or lost a game, rather a measure of how well the team won or lost the game.

Rank Team Opponent Spread Actual %Error
1 Florida State Clemson -9.5 -8 -16%
2 Oregon Washington State -23.5 -7 -70%
3 Alabama Florida -14 -21 50%
4 Oklahoma West Virginia -8 -12 50%
5 Auburn Kansas State -7.5 -6 -20%
6 Texas A&M Southern Methodist -34.5 -52 51%
8 LSU Mississippi State -7 5 -171%
11 Michigan State Eastern Michigan -43.5 -59 36%
13 Georgia Trojans -41.5 -66 59%
14 South Carolina Vanderbilt -22 -14 -36%
18 Missouri Indiana -15 4 -127%
19 Wisconsin Bowling Green -26.5 -51 92%
20 Kansas State Auburn 7.5 6 20%
21 Brigham Young Virginia -15 -8 -47%
22 Clemson Florida State 9.5 8 16%
24 Nebraska Miami-Florida -8 -10 25%

Baylor, Notre Dame, Ole Miss, UCLA, Arizona State, Stanford, USC, and Ohio State each had bye weeks. They are not included in the Table 1 or Figure 1. Wisconsin beat the spread by the largest margin at 92%. LSU did not beat the spread with the worst margin at -171% after being upset by Mississippi State. Week 4 was important for the SEC rivalry between Alabama and Auburn. Week 4 was the first week that Alabama beat the spread at a 50% error and the first week that Auburn did not beat the spread at -20% error.

Weekly Summary

Now that we are past the 3rd week of college football we have enough data for some statistics. Every team has played at least three games, which is the minimum amount of data required for statistics. A single factor analysis of variance (ANOVA) reveals that there is no statistical difference in mean percent error across the first four weeks of play (p=0.829). The results of head to head Tukey multiple comparison statistical matchups can be found here. This means that, on average, all teams have performed in a similar manner relative to their expectations. This isn’t unexpected due to the variable nature of the data.

While there may not be any differences now, there might be some practical information to be taken from the data. Below are five boxplots to aid in understanding the data. Each boxplot contains five of the top 25 teams in order to reduce crowding.

Figure 2 reports the percent error for the first five teams. As stated earlier, this is the first week that Alabama has beaten the spread. Will they continue or revert back to their previous three weeks? Will Auburn continue to beat the spread after failing to do so for the first time this season? Baylor had a bye week but expect them to continue their trend of beating the spread this week vs Iowa State. Arizona State and Brigham Young are not consistently beating the spread.

Figure 2 – Boxplots of Percent Error for Alabama, Arizona State, Auburn, Baylor, and Brigham Young.

There are three important details in Figure 3. Firstly, Florida State has yet to beat the spread this season. However it should be noted there percent error for Florida State has increased over their three games indicating they might beat the spread in the near future. The performance of Clemson, Georgia, and Kansas State has been too variable. This is the first week that LSU did not beat the spread.

Figure 3 – Boxplots of Percent Error for Clemson, Florida State, Georgia, Kansas State, and LSU.

The data in Figure 4 is more straightforward. This group of teams has a variable percent error. Michigan State is scoring close to the spread each week. Missouri and Notre Dame are mostly beating the spread. Ohio State beat the spread in two of their three games, but the week they didn’t beat the spread was by a large margin (-240%) skewing their plot.

Figure 4 – Boxplots of Percent Error for Michigan State, Missouri, Nebraska, Notre Dame, and Ohio State

Figure 5 has two groups. Oklahoma, Ole Miss and Oregon have performed consistently each week. Meanwhile, Oklahoma State and South Carolina have performed inconsistently. Oklahoma has beaten the spread the past three weeks while only not beating the spread during week one with a -4% error. Ole Miss has beaten the spread by 52% or more this season.

Figure 5 – Boxplots of Percent Error for Oklahoma, Oklahoma State, Ole Miss, Oregon and South Carolina.

Figure 6 is an interesting group. Firstly, Stanford beat the spread in weeks one and three but fell short of the spread in week two by 200%. Texas A&M has beaten the spread by 51% or more in every week but week three. UCLA has not beaten the spread this season. Furthermore, UCLA hasn’t surpassed the -58% mark. USC beat the spread by more than 100% in weeks one and two but failed to beat the spread by more than 200% in week three. Wisconsin failed to beat the spread by -14% and -17% in weeks one and two, but after coming off a bye in week three smashed the spread by 92% in week 4.

Figure 6 – Boxplots of Percent Error for Stanford, Texas A&M, UCLA, USC, and Wisconsin.

This week’s takeaways: If Baylor, Oklahoma, and Ole Miss keep the same pace, expect them to beat the spread. UCLA won’t cover the spread if they continue the same pattern. Auburn and Alabama have broken their streak. The rest of the top 25 teams are not demonstrating any patterns after four weeks.

 

Important notes:

  1. Spreads can be found at vegasinsider.com.
  2. Percent error is calculated as (Spread-Actual)/Abs(Spread)
  3. I understand that spreads are typically used for gambling purposes and that the lines move. However, it is important for the spreads to reasonably accurate in order for the house or bookie to make money. Lines are a consistent source of weekly predictions.

 

Previous results – week 1 week 2 week 3

Top 5 Reasons to Quit Your Job (and Yet Remain Employable)

Photo: http://janeencarlberglaw.com/

Photo: http://janeencarlberglaw.com/

If you have followed my career at all, you are well aware that I have been around the block a few times when it comes to employers.  Most of that has to do with the short-term and long-term repercussions of changing careers two years after college because of the M-word—marriage (which I thoroughly enjoy, by the way).

This career change has taught me a lot about recruiting, interviewing, vetting, and networking.  But it has also taught me a whole lot about quitting.  Fancier people may call it “resigning” or “seeking new opportunities,” but regardless, there is an art and science to being able to quit without it being seen as a negative attribute on your resume.  So without further ado, here are the top 5 most acceptable and commendable reasons to quit your current job.

(1) Unethical and Unsafe Work Environment

This is my number one because it has the biggest impact on your future employment.   If you are with an employer that does not truthfully prohibit unethical and unsafe characteristics then you will probably be hurt more by staying than if you quit.  Please turn in your two-week notice immediately if your boss or a significant portion of management are guilty of doing or accepting the following:

  • lying to customers and suppliers
  • using sexual or suggestive language
  • touching coworkers sexually or inappropriately
  • drinking alcohol or doing drugs on the job
  • consistently paying workers late or not paying at all
  • making racist comments or jokes
  • letting jealousy and anger affect decision-making
  • endangering workers with poor safety practices or no safety practices
  • doing other inappropriate behavior

(2) Becoming a Stay-at-Home Parent

This is a very tough (or very easy) decision for many families to make.  If this decision is something you and your spouse are going through currently, then please do not be pressured into feeling you have to work outside the home to be a fully developed human being.  Being a stay-at-home parent is perfectly acceptable as long as you can pay your bills on-time and not accumulate debts.

In order to prepare for this season in life, try living on only one income for 3 months while you are still working.  If you succeed at this task, then go ahead and let your employer know your family’s decision for you to become a stay-at-home parent.  And again, please do not feel pressured into staying at work.  And please, only come back to work when you want to come back to work.

(3) Spouse Works Significantly Far Away

Often this affects newly married couples and military couples the most.   It also affects couples who have a spouse that has received a dream job offer in a distant city.   If you and your spouse work with employers that are hundreds and thousands of miles apart, then you have a pretty arduous decision ahead of you: determining which one of you has to quit.

This can be very difficult because both spouses may love their jobs; however, spouses need to love each other more than their jobs.  Firstly, seek to see if you can just transfer within your current company.  Secondly, if this is not possible or takes too much lead-time, then you will have to quit.  This does not have to be an immediate resignation, but you definitely need to get the ball rolling in that direction.

(4) Becoming an Entrepreneur

Do not do this on a whim.  Only do this if your hobby or “side hustle” has become lucrative enough that you can afford to quit your day job.  The romanticism of being a business owner fades quickly if you cannot put food on your dinner table.  However, if your business is capable of paying you similarly to or more than what you are making currently, then by all means, quit!

Careful: Just be sure not to burn any bridges with your current employer. You may need them to hire you back in the future if your business flops.

(5) Seeking More Pay or More Opportunity

Sometimes you reach the proverbial glass ceiling.  Many large companies do not give pay increases very often, or they give pay increases yearly but at a 1% or 2% rate.  Meanwhile, many smaller companies only have a handful of employees so opportunities for promotion are pretty slim.  In order to grow and reach your potential, you are going to have to quit.  However, make sure you have a new job first!

Depending on the situation, some people may call you greedy for making a move.  Take their opinion with a grain of salt though—while your mentors may have your best interest at heart, other people may just be green-eyed with envy.

ARE THERE ANY OTHER VALID REASONS TO QUIT BESIDES THESE?

Expectations and Realities: Week 3 AP Top 25 College Football Teams

Welcome to the 3rd week of breaking down the top 25 teams’ performance compared to their expectations. Here are the results of week 1 and week 2 if want to see previous performance comparisons. In that article, you will find comparisons of vegasinsider.com’s lines for the AP top 25 teams to the actual scores for that week’s games. Here are the results of week 3.

This week Nebraska and North Carolina fell out of the top 25 and will not be included in this week’s results.

In the Table 1 and Figure 1 below you will find the 25 teams ranked in the AP preseason poll, the predicted spread, the actual result, and the percent error. The teams are sorted based on how well the team performed based on the spread for that game. Teams with a positive percent error performed better than expected, or covered the spread, while teams with a negative percent error underperformed, or did not cover the spread. Note: this is not a measure if a team won or lost a game, rather a measure of how well the team won or lost the game. For example, Oklahoma was expected to beat Tennessee by 21 but outscored them by 24 points. Oklahoma performed 14% better than predicted.

Rank Team Opponent Spread Actual %Error
24 South Carolina Georgia 6.5 -9.5 246%
20 Missouri Central Florida -10.5 -28 167%
22 Ohio State Kent State -31 -66 113%
14 Ole Miss LA-Lafayette -27 -41 52%
8 Baylor Buffalo -33.5 -42 25%
15 Stanford Army -30 -35 17%
4 Oklahoma Tennessee -21 -24 14%
10 LSU Louisiana Monroe -31 -31 0%
3 Alabama Southern Miss -46 -40 -13%
7 Texas A&M Rice -32.5 -28 -14%
16 Arizona State Colorado -16.5 -14 -15%
2 Oregon Wyoming -43.5 -34 -22%
21 Louisville East Carolina -14.5 -10 -31%
11 Notre Dame Purdue -30 -16 -47%
25 Brigham Young Houston -17 -8 -53%
12 UCLA Texas -8.5 -3 -65%
9 USC Boston College -17 23 -235%
6 Georgia South Carolina -6.5 9.5 -246%
17 Virginia Tech East Carolina -10 17 -270%

Spreads come from vegasinsider.com.

Florida State, Auburn, Michigan State, Wisconsin, Clemson, and Kansas State each had bye weeks. They are not included in the table. LSU is the first team in 3 weeks to push the spread. South Carolina exceeded predictions by the largest margin with the upset over Georgia. Virginia Tech had the worst performance after being upset by East Carolina.

Now that we are in the 3rd week of college football we have enough data for some statistics. Teams with byes this week will not be included in this analysis due to insufficient data. Georgia is also excluded since they had a bye week last week. A single factor analysis of variance (ANOVA) reveals that there is no statistical difference in percent error across the first three weeks of play (p=0.556). The results of head to head Tukey multiple comparison statistical matchups can be found here. This means that, on average, all teams have performed in a similar manner relative to their expectations.

While there may not be any differences now, there might be some practical information to be taken from the data. Below are four boxplots to aid in understanding the data. Figure 2 shows the percent error for top 25 teams that have played at least three games. Typically, I would not show this sort of figure. The graph is crowded. However, notice how BYU’s average percent error dwarfs the other teams. This is skewed due to their week two game vs Texas. They were expected to lose by one point but ended up winning by a convincing 34 points. For now, this is considered an outlier and BYU is removed from the analysis. The remaining 17 teams are portrayed in Figures 3 through 5.

Figure 2 – Boxplots of Percent Error for AP Top 25 Teams that Have Played 3 or More Games

There are three important details in Figure 3. Firstly, that the percent error is relatively variable, except for Baylor. Baylor has a median error rate of 36% and has exceeded expectations for all three weeks. Next notice that, so far, Alabama has been underperforming without a single positive error rate in the first three weeks. Finally, LSU has been meeting or exceeding expectations in all of three weeks.

Figure 3 – Boxplots of Percent Error for Alabama, Arizona State, Baylor, Louisville and LSU

The data in Figure 4 is more straightforward. Of the six teams pictured, only Ole Miss is consistently winning against the spread with percent errors of 120%, 105%, and 52% for weeks one, two and three respectively. The percent errors for the other teams in Figure 4 are too variable for any discernible patterns.

Figure 4 – Boxplots of Percent Error for Missouri, Notre Dame, Ohio State, Oklahoma, Ole Miss, and Oregon

With the exception of UCLA, the percent error for teams in Figure 5 is too great. Each team has had weeks were they beat the spread and others where they did not. However, UCLA has consistently not beaten the spread with a median percent error of -65%.

Figure 5 – Boxplots of Percent Error for South Carolina, Stanford, Texas A&M, UCLA, USC, and Virginia Tech

This week’s takeaways: If Baylor, LSU, and Ole Miss keep the same pace, bet against the spread. Bet that Alabama or UCLA won’t cover the spread if they continue the same pattern.

 

Important notes:

  1. Spreads can be found at vegasinsider.com.
  2. Percent error is calculated as (Spread-Actual)/Abs(Spread)
  3. I understand that spreads are typically used for gambling purposes and that the lines move. However, it is important for the spreads to reasonably accurate in order for the house or bookie to make money. Lines are a consistent source of weekly predictions.

Vaccines, Lightning, Lottery: What Are the Odds?

The odds of being killed in a tornado in a given year are 1 in 5,693,092.

The odds of being struck by lightning in a given year are 1 in 1,107,143.

The odds of winning the grand prize in the lottery are 1 in 175,223,510.

Thank you Mr. Lottery!

Why am I mentioning this? Why is it even relevant? Surely almost all of you have been through a tornado and survived, right? Surely every single one of you reading this has seen lightning and are still alive, right? And I am going out on a limb here, but almost certainly none of you reading this has ever won the grand prize of the lottery, correct?

I am bringing these statistics up for one simple reason: vaccines.

Yes, the scary and extremely controversial subject that somehow science doesn’t understand yet we are still pumping our kids full of them. Well, why don’t we look at some data?

Per: National Vaccine Injury Compensation Program (VICP) Adjudication Categories by Vaccine for Claims Filed Calendar Year 2006 to Present.

Vaccine Alleged by Petitioner

No. of Doses Distributed US CY 2006 – CY 2013 (Source: CDC)

Compensable

Compensable Total

Dismissed/ Non-Compensable Total

Grand Total

Concession

Court Decision

Settlement

DT

652,327

1

3

4

4

8

DTaP

75,888,233

10

17

71

98

72

170

DTaP-Hep B-IPV

43,929,797

4

6

18

28

38

66

DTaP-HIB

1,135,474

0

1

1

DTaP-IPV-HIB

39,590,896

5

5

11

16

DTP

04

1

2

3

2

5

DTP-HIB

04

0

1

1

Hep A-Hep B

11,662,755

8

8

1

9

Hep B-HIB

4,796,583

1

1

1

3

1

4

Hepatitis A (Hep A)

124,212,280

2

4

20

26

18

44

Hepatitis B (Hep B)

129,820,136

2

10

35

47

34

81

HIB

83,517,849

1

4

5

4

9

HPV

67,250,524

10

62

71

80

151

Influenza5

944,000,000

36

67

728

831

165

996

IPV

58,019,052

4

4

2

6

Measles

135,660

1

1

1

Meningococcal

58,412,363

1

1

22

24

3

27

MMR

73,441,556

15

13

52

80

69

149

MMR-Varicella

11,028,270

8

7

15

8

23

Nonqualified6

N/A

0

21

21

OPV

0

1

1

3

4

Vaccine Alleged by Petitioner

No. of Doses Distributed US CY 2006 – CY 2013 (Source: CDC)

Compensable

Compensable Total

Dismissed/ Non-Compensable Total

Grand Total

Concession

Court Decision

Settlement

Pneumococcal Conjugate

132,932,107

1

5

6

13

19

Rotavirus

70,719,103

1

3

15

19

6

25

Rubella

422,548

1

1

1

Td

55,742,830

4

5

49

58

15

73

Tdap

155,106,848

11

6

74

91

11

102

TETANUS

3,836,052

3

17

20

10

30

Unspecified7

N/A

1

2

3

541

544

Varicella

90,425,492

3

5

20

28

10

38

Grand Total

2,236,678,735

114

142

1,225

1,480

1,144

2,624

Guys, this is it. This is all of the actual cases taken to court that has found vaccines accountable for an injury. All of them.

I honestly don’t want to hear,”What about the shots that the parents never took the kids to trial over!” That is a terrible argument. If your kid were “vaccine injured” and “regressed to autism,” would you not seek out legal help? There are ambulance chasers plastered over every city that work for free if no money is won, are you telling me they won’t do the same in HUGE money cases like this?

Rant over. What we see here is this: There is a 0.0000013% chance of your kid suffering an injury from a vaccine. You have a 1 in 1,300,000 chance of being injured from vaccines. Sure, you have better chance of being injured by vaccines than winning the lottery and being killed by tornadoes. Lets throw lottery out. Lets look at tornadoes. You are a little less than 5 times more likely to be injured by vaccines than you are to be killed by a tornado. That is not much. Are you fleeing tornado zones in mass exodus? No.

You are MORE likely to be injured in a lightning strike than you are by a vaccine. Do you cry foul and petition to the government to end lightning? No!

The numbers do not lie. They simply do not. If you are against vaccines, you have a 99.9999987% reason to not be. And after that, well, you are simply pleading ignorance.

Expectations and Realities: Week 2 AP Top 25 College Football Teams

Last week I reported how top 25 teams performed relative to their expectations. In that article I compared vegasinsider.com’s lines for the AP top 25 teams to the actual scores for that week’s games. Here is week 2’s comparison.

During the first week of college football, Washington was the only team to drop from the top 25. Louisville replaced them for the 25th spot. Because of this, Washington was not included this week.

In the table below you will find the 25 teams ranked in the AP preseason poll, the predicted spread, the actual result, and the percent error. The teams are sorted based on how well the team performed based on the spread for that game. Teams with a positive percent error performed better than expected while teams with a negative percent error underperformed. Note: this is not a measure if a team won or lost a game, rather a measure of how well the team won or lost the game. For example, Texas A&M was predicted to beat Lamar by 46.5 points but outscored them by 70 points. Texas A&M performed 50% better than predicted.

Relative Performance of Week 2 AP Top 25 College Football Teams

Rank Team Opponent Spread Actual %Error
16 Notre Dame Michigan -4 -31 675%
24 Missouri Toledo -3.5 -25 614%
14 USC Stanford 3 -3 200%
15 Ole MIss Vanderbilt -18.5 -38 105%
23 Clemson South Carolina State -34 -66 94%
4 Oklahoma Tulsa -24.5 -45 84%
12 LSU Sam Houston State -32 -56 75%
9 Texas A&M Lamar -46.5 -70 51%
17 Arizona State New Mexico -24.5 -35 43%
3 Oregon Michigan State -13.5 -19 41%
10 Baylor Northwestern State -46.5 -64 38%
5 Auburn San Jose State -34 -46 35%
25 Louisville Murray State -35.5 -45 27%
6 Georgia Bye 0 0 0%
2 Alabama Florida Atlantic -42 -41 -2%
18 Wisconsin Western Illinois -41 -34 -17%
21 South Carolina East Carolina -14.5 -10 -31%
7 Michigan State Oregon 13.5 19 -41%
1 Florida State Citadel -56.5 -25 -56%
20 Kansas State Iowa State -12 -4 -67%
11 UCLA Memphis -22.5 -7 -69%
22 North Carolina San Diego State -14.5 -4 -72%
19 Nebraska McNeese State -35.5 -7 -80%
13 Stanford USC -3 3 -200%
8 Ohio State Virginia Tech -10 14 -240%

Use the following chart to help visualize the data in the table.

Many teams played easy opponents during week 2 as you can tell by the number of 30+ point spreads. However, there were some games that were predicted to be close. The most surprising win this week, for a top 25 team, comes from Notre Dame’s 31-0 shutout over Michigan. Notre Dame was favored by 4 points. This indicates that it was expected to be a close game that instead resulted in a blowout.

The first 14 teams in the table exceeded expectations while the bottom 11 underperformed.The top 3 overachievers this week were Notre Dame (675%), Missouri (614%), and USC (200%). The top 3 underperformers this week were Ohio State (-240%), Stanford (-200%), and Nebraska (-80%).

 

Important notes:

1. Spreads can be found at vegasinsider.com.

2. Percent error is calculated as

3. I understand that spreads are typically used for gambling purposes and that the lines move. However, it is important for the spreads to reasonably accurate in order for the house or bookie to make money. Lines are a consistent source of weekly predictions

How Good is Cam Newton?

Cam Newton is an overall number 1 pick, and he now can add quarterback of a playoff team to his resume’. Newton is already being credited for the Panthers’ 2013 success where they finished 12-4.  In this same season, Newton is credited for his increase in productivity compared to the year before. This is how it goes in football. QBs get all the chicks but also lose the chicks when the team play suffers.

When the Panthers were disappointing the previous years, all you heard were stories about his immaturity and how he doesn’t take the game seriously. Fast forward one incredible defensive season later, Cam is now the next Tom Brady and about to ring off a series of Super Bowl wins. The narrative changes with team very quickly.

Cam Newton training with Chris Weinke at IMG Academy

Superstar? The numbers say average.

I personally found that the turnaround had more to do with the Panther’s incredible defense. Per Football Outsiders, the Panthers defense ranked 3rd in DVOA. DVOA, in this instance, measures just how good a defense is on a per play basis. The Panthers ranked 3rd allowing -18.0% less value per play than the average team. The Seahawks were number one with a legendary DVOA of -30.0%. While the Panthers weren’t the Seahawks, they were pretty damn good. The Panthers were the number 1 overall pass defense on DVOA, even better than the vaunted Seahawks. When we are talking about a clear top 3 defense, you are going to win games.

Carolina Panthers defense tackles RB Alfred Morris (46).

Here are the real superstars of the Panthers.

Back to Cam Newton. How much of a help was he in obtaining this 12-4 turnaround? And how does he stack up against others? Lets have a look shall we.

Defense-Adjusted Yards Above Replacement

DYAR tells us exactly that. How many yards, adjusted for defense, is a QB worth over a league average replacement. Newton places a very pedestrian 17th with a DYAR of 421. It definitely speaks well that he is an above average player, but at a 17 ranking, he seems to be only that, slightly above average. Andy Dalton and Carson Palmer are just ahead of Newton in these rankings. Hardly superstar status (although Cincy feels the need to pay Dalton like he is one).

Andy Dalton

To say Dalton didn’t deserve his contract is an understatement.

Defense-Adjusted Value Over Average

DVOA represents a per play measurement of how good a QB is over an average QB in the same situation. Newton actually falls back a little bit to a 19 ranking with a small 1.7% more value than an average player. Again, above average but ever so slightly. These rankings put Newton behind Josh McCown and in a league with Dalton, Palmer, and Ryan Fitzpatrick. If we are giving Cam credit, the credit seems to be vastly overstated.

Cam Newton

Cam needs to hone his passing skills.

Cam’s Passing

Cam Newton training with Chris Weinke at IMG Academy

Having seen Cam’s passing numbers, he honestly looks like a very league average QB. However, he does do some extras to bump up his passing value and overall value (which we will get to). He had a very strong 24TDs to only 13 INTs. That’s a positive ratio that is more indicative of a top 10 QB. He needs to throw more TDs, but as long as his INTs are down, it’s a major plus.

At this point, Newton probably sits as the 15th best passer in the league. I would place Andy Dalton ahead of him, but Palmer and Fitzpatrick don’t quite bring his low INT rate skill. C+ passing grade.

Cam’s Running

Now here is where Cam shines a little bit more. Cam has a DYAR of 102 for a rank of 5th. No matter how you slice it, picking up extra yards on the ground is a valuable skill and he excels at it. His DVOA falls to 24th, however, that is a case of him taking off too much. He can get the yards, but he needs to reel it back in from time to time and make sure each play is getting maximum value. Newton had 6 TDs running it, which is a huge plus. He also had 2 fumbles, but that is to be expected. Still a nice ratio of scoring to turnovers.

Newton is a good runner. I would give his rushing a B+.

Cam Newton Jersey

So Where Does He Sit?

Cam Newton is no superstar, and he had minimal to do with the Panthers turnaround. He shouldn’t receive the praise and credit, but that doesn’t mean he doesn’t bring value. Overall, I would say Cam Newton is somewhere between the 12th and 16th best QB in the league. He is good but only slightly good. You see a lot of positives in his game and you hope that he continues to grow.

But please, hold the superstar praise for when he actually deserves it.

Are You Really the Luckiest Woman in the World?

I see it every single day. Someone gets a pretty sweet gift and proclaims, “I am the luckiest woman in the world for getting gift x!!!” Sure, we are elated to get gifts and surprises and may be slightly hyperbolic when we get these things. But is there any truth to the claims? I have decided to put some of these claims under the scrutiny of data and see if you really have a claim to being the luckiest woman in the world.

(Please keep in mind this is a tongue-in-cheek piece. I am sure everything about you is simply splendid. Do your thing, girl.)

Claim: I am the luckiest woman in the world to have such a great job.

Doctor Claire

According to Forbes, the happiest job for a woman (factoring in salary, job growth, and job satisfaction) is a diagnostic medical doctor. The median income for this job is $121,000 and has an estimated job growth of 27% through 2020. Pretty sweet gig.

So how many women are doctors? There are approximately 202,000 female doctors in the United States. Out of those, only 11,000 earn in the top 10% ($233,000) of doctors. These salaries are based off of a general practitioner.

Conclusion: Unless you are a doctor earning in excess of $233,000, you do not have a valid claim.

Claim: I am the luckiest woman in the world because my kids are so amazing.

Gregory Smith could read by 2, enrolled in college by 10, is a children’s rights activist, and was nominated for a Nobel Peace Prize at the tender age of 12.

Michael Kearney graduated college at 10, was a teacher at age 17, spoke his first words at 4 months, was once the youngest post graduate, diagnosed his own ear infection at the age of six months, and is a millionaire.

Alexis Martin was one of the youngest people to ever be accepted into Mensa, at the age of 3. She has the same IQ as Stepehn Hawking and Albert Einstein.

And just for good measure, literally everyone on this list:

http://www.thebestschools.org/features/worlds-50-smartest-teenagers/

Conclusion: Are one of these kids yours? Claim invalid.

Claim: I am the luckiest woman in the world because I am married to the most handsome man  in the world.

Omar Borkan Al Gala was deported from his country because he was so handsome, officials thought he would give women immoral thoughts. Hold on, I am going to re-type something: HE WAS DEPORTED FROM A COUNTRY FOR BEING TOO FUCKING HOT.

Ok, just wanted everyone to be clear on that.

Conclusion: Your husband is not Omar Borkan Al Gala

Omar Borkan Al Gala...Deported From Saudi Arabia 4 Being To Handsome (Panties Drop)

Claim: I am the luckiest woman in the world because my husband is the smartest man alive

This is easy. Is your husband Stephen Hawking (160 IQ), Christopher Langan (205) , Kim Ung-Yong (210), Paul Allen (170), Rick Rosner (192), Gary Kasparov (190), Andrew Wiles (170), Judit Polgar (for you ladies who love the ladies, 170), Christopher Hirata (225), Terrance Tao (230), or Evangelos Katsioulis (198)?

Only 0.5% of the population have an IQ over 140.

Conclusion: Probably not.

Claim: I got diamonds. I am the luckiest woman in the world.

In 1905 a man named Frederick Wells discovered a rough diamond that was 3,106 carats. Named the Cullinan, it was later cut into 100 smaller diamonds. The largest of those being 530 carats.

Actual-size replica of Cullinan Diamond.

Actual size replica of the Cullinan

In 2012, the Taj Mahal diamond sold for 8.8 million dollars.

The Elizabeth Taylor Diamond sold for $265,697 per carat and 8.8 million for the whole stone.

The total amount that Elizabeth Taylor jewelry collection sold for was 137.2 million dollars.

Conclusion: You do not have any of these diamonds.

Regardless of what I say, having happiness and love makes all of us the luckiest people on earth.

Expectations and Realities: Week 1 AP Top 25 College Football Teams

Week 1 of college football has come and gone. While we wait for the polls to update, let us take a moment and see how each of the teams in the AP top 25 poll performed relative to their predictions.

In the table below you will find the 25 teams ranked in the AP preseason poll, the predicted spread, the actual result, and the percent error. The teams are sorted based on how well the team performed based on the spread for that game. Teams with a positive percent error performed better than expected while teams with a negative percent error underperformed. Note: this is not a measure of if a team won or lost a game, rather a measure of how well the team won or lost the game. For example, Oregon beat South Dakota 62-13. Oregon won their game in convincing fashion. However, Oregon was expecting to win by 54 points, but won by 49 points.

Relative Performance of AP Top 25 College Football Teams

Rank Team Opponent Spread Actual %Error
21 Texas A&M South Carolina 10 -24 340.0%
12 Georgia Clemson -9.5 -24 152.6%
22 Nebraska Florida Atlantic -20 -48 140.0%
18 Ole Miss Boise State -10 -22 120.0%
15 USC Fresno State -18.5 -39 110.8%
17 Notre Dame Rice -19.5 -31 59.0%
6 Auburn Arkansas -17 -24 41.2%
10 Baylor Southern Methodist -33 -45 36.4%
5 Ohio State Navy -13.5 -17 25.9%
13 LSU Wisconsin -3.5 -4 14.3%
8 Michigan State Jacksonville State -34.5 -38 10.1%
11 Stanford UC Davis -42.5 -45 5.9%
4 Oklahoma LA Tech -33.5 -32 -4.5%
20 Kansas State Stephen F. Austin -42 -39 -7.1%
3 Oregon South Dakota -53.5 -49 -8.4%
23 North Carolina Liberty -31 -27 -12.9%
14 Wisconsin LSU 3.5 4 -14.3%
24 Missouri South Dakota State -25.5 -20 -21.6%
19 Arizona State Weber State -46 -31 -32.6%
2 Alabama West VA -23 -10 -56.5%
7 UCLA Virginia -19 -8 -57.9%
1 Florida State Oklahoma State -20.5 -6 -70.7%
25 Washington Hawaii -17.5 -1 -94.3%
16 Clemson Georgia 9.5 24 -152.6%
9 South Carolina Texas A&M -10 24 -340.0%

I’ve added the following chart to help you visualize the data.

The first 12 teams in the table exceeded expectations while the bottom 13 underperformed. Texas A&M, ranked 21, tops the table exceeding predictions by 340% outscoring number 9 South Carolina 52-28. Expectedly, South Carolina underperformed by 340%. Defending national champions Florida State struggled in their opener underperforming by 70.7% against Oklahoma State. Georgia/Clemson and LSU/Wisconsin games were other notable games as it marks the only other two Ranked teams that lost their opener. The Georgia/Clemson game had an error of 152.6% while the LSU/Wisconsin game had an error of 14.3%. While Georgia trumped Clemson in a 2nd half shut out, LSU rallied in the second half to edge out their spread by half a point against Wisconsin.

On average, the ACC underperformed by 78.8% while the SEC exceeded expectations by an average of 31.3%. Below are the conference averages.

ACC          -78.8%

PAC 12     -12.8%

Big 10       18.0%

Big 12       30.1%

SEC           31.3%

IND           59.0%

Important notes:

1. Spreads can be found at vegasinsider.com.

2. Percent error is calculated as (Spread-Actual)/Abs(Spread)

3. If you like what you see here (or don’t) let me know below. You can also point out mistakes or criticize the article.