Category Archives: Uncategorized
Bob Smizik wrote something mind bogglingly stupid
This article contains one of the dumbest paragraphs I have ever seen a sports writer write [emphasis added]:
Those who love to blame everything that happens in the NFL on Roger Goodell are yelping about the fact investigators have yet to interview Brady. Trust me, he will be interviewed. In depth. The NFL has called upon excellent people to handle this investigation. It knows it must get this right after it so badly mishandled the Ray Rice investigation.
Yes, everyone who was upset with the NFL for botching the Ray Rice investigation will realize all of their anger at the NFL over the Ray Rice scandal will not have been in vain if the NFL gets the Ballghazi investigation right. #sarcasm
Even speaking about Ballghazi and the Ray Rice situation in the same breath is insulting and ignorant. Sports writers are the worst.
Cheers.
Here’s what @statsbylopez did on the first day of statistics class
Ample literature has gone into what teachers should do on the first day of class. Should they do an ice-breaker? Dive right into notes? Review a few example questions to motivate the course?
I don’t really have control groups to use as a comparison, but I think these two activities were helpful and engaging, and I figured it was worth passing along.
Introduction to Statistics (Intro level, undergrad)
I stole this one from Gelman and Glickman‘s “Demonstrations for Introductory Probabiity and Statistics.”
When the students come in, I split the course (appx 25 students) into eight groups. Each group was given a sheet of paper with a picture on it, and the groups were tasked with identifying the age of the subject in question. I had some fun coming up with the pictures – I went back to the 90’s with T-boz from TLC and Javy Lopez of the Atlanta Braves…
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A better place kicking measure
I was watching the football games last weekend and one of the announcers said something like “This kicker is 16/17 on the season.” I absolutely hate this. 16/17 means nothing if you don’t factor in how long the field goals are (I’ve talked about this before here.) So I spent a little bit of time thinking about what would be a better metric and I’ve come up with my first iteration of an improved kicking metric. So let me introduce you to the Booting Individual Rating Objective Numeric Accuracy Statistic (B.I.R.O.N.A.S.) #awesome.
The deets
Let 
BIRONAS = 
So the only detail left to fill in is how to estimate E[
What does this mean?
Using these expected points we can calculate BIRONAS, which is the ratio of the total points scored on field goals to the total number of expected points scored. Thus, BIRONAS could be interpreted as the percentage of excess points that a kicker provided to his team above an average NFL kicker. So if a kicker has a BIRONAS of 1 it means that the kicker scored exactly the same number of points that was expected based on average kicking. A BIRONAS of 1.25 means that a kicker score 25% more points than expected compared to an average kicker. Likewise a BIRONAS of .75 means a kicker scores 25% fewer points than expected. So who had a good year according to BIRONAS?
2014 BIRONAS
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We’re going to ignore Garrett Hartley who only had 3 attempts in 2014 and award the BIRONAS award to Sebastian Janikowski. The “Polish Cannon” is a great example of why field goal percentage is terrible. His field goal percentage in 2014 was around 86% whereas Adam Vinatieri had a percentage of about 97%. Looking at that Vinatieri had a better year, but BIRONAS has Janikowski about 2% better than Vinatieri this year. The difference between the two kickers can clearly be seen when you look at their average yardage for an attempt: Janikowski’s – 44 yards and Vinatieri 35 yards. Janikowski’s average kick was almost 10 yards further than Vinatieri’s.
Cowboys kicker Dan Bailey, ranked 9th, is another interesting case. While his field goal percentage was only 84%, his BIRONAS was 1.11, tied with 3 other kickers who had percentages of 87%, 92%, and 94%. What is holding him up? His average attempt was from 41 yards and he made 5 of his 7 kicks from over 50 yards.
Cheers.
Going beyond the mean to analyze QB performance
A few months ago, my friend & writer Noah Davis asked me a question that was bothering him. I’ll paraphrase, but this was roughly what he said:
Does consistency matter for quarterbacks? Like would you rather have an average QB who is never really great, or a good QB who occasionally sucks?
Well, fortunately there are ways to measure performance consistency, and one of them is standard deviation. QB’s with high standard deviations in their game-by-game metrics are the less consistent ones, and visa versa.
But perhaps an even better idea than just measuring each QB’s standard deviation of a certain metric is to compare the overall distribution of performance. This can be done using many tools, and we chose density curves, which are just rough approximations of the smoothed lines that one would fit over a histogram.
The culmination of our project into looking at QB density curves is summarized here on FiveThirtyEight. In addition, I…
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NFL Picks – Conference Championship
Total (weeks 1-17) – SU: 170-85-1 ATS: 126-124-6 O/U: 135-118-3
Playoffs – SU: 6-2, ATS: 5-3, O/U: 7-1
Week 1 – SU: 9-7-0 ATS: 8-8-0 O/U: 13-3-0
Week 2 – SU: 10-6-0 ATS: 10-6-0 O/U: 10-6-0
Week 3 – SU: 12-4-0 ATS: 9-6-1 O/U: 8-8-0
Week 4 – SU: 7-6-0 ATS: 5-7-1 O/U: 5-8-0
Week 5 – SU: 14-2-0 ATS: 6-9-0 O/U: 9-6-0
Week 6 – SU: 11-3-1 ATS: 8-7-0 O/U: 6-9-1
Week 7 – SU: 11-4-0 ATS: 7-8-0 O/U: 8-7-0
Week 8 – SU: 11-3-0 ATS: 8-7-0 O/U: 8-7-0
Week 9 – SU: 9-4-0 ATS: 8-5-0 O/U: 4-8-1
Week 10 – SU: 9-4-0 ATS: 4-9-0 O/U: 6-7-0
Week 11 – SU: 9-5-0 ATS: 8-6-0 O/U: 7-7-0
Week 12 – SU: 10-5-0 ATS: 7-8-0 O/U: 8-7-0
Week 13 – SU: 11-5-0 ATS: 8-8-0 O/U: 7-9-0
Week 14 – SU: 7-9-0 ATS: 9-6-1 O/U: 11-5-0
Week 15 – SU: 11-5-0 ATS: 6-8-2 O/U: 10-6-0
Week 16 – SU: 8-8-0 ATS: 10-6-0 O/U: 9-7-0
Week 17 – SU: 12-4-0 ATS: 5-10-1 O/U: 6-9-1
Week 18 – SU: 3-1-0 ATS: 2-2-0 O/U: 3-1-0
Week 19 – SU: 3-1-0 ATS: 3-1-0 O/U: 4-0-0
Week 20 – SU: 2-0-0 ATS: 1-1-0 O/U: 1-1-0
New England at Indianapolis
Prediction: Patriots 29-23 (65.3%)
Pick: Colts +7
Total: Under 54
Green Bay at Seattle
Prediction: Seahawks 24-21 (60.3%)
Pick: Packers +7.5
Total: Under 46.5
NFL Picks – Divisional Round
Total (weeks 1-17) – SU: 170-85-1 ATS: 126-124-6 O/U: 135-118-3
Playoffs – SU: 6-2, ATS: 5-3, O/U: 7-1
Week 1 – SU: 9-7-0 ATS: 8-8-0 O/U: 13-3-0
Week 2 – SU: 10-6-0 ATS: 10-6-0 O/U: 10-6-0
Week 3 – SU: 12-4-0 ATS: 9-6-1 O/U: 8-8-0
Week 4 – SU: 7-6-0 ATS: 5-7-1 O/U: 5-8-0
Week 5 – SU: 14-2-0 ATS: 6-9-0 O/U: 9-6-0
Week 6 – SU: 11-3-1 ATS: 8-7-0 O/U: 6-9-1
Week 7 – SU: 11-4-0 ATS: 7-8-0 O/U: 8-7-0
Week 8 – SU: 11-3-0 ATS: 8-7-0 O/U: 8-7-0
Week 9 – SU: 9-4-0 ATS: 8-5-0 O/U: 4-8-1
Week 10 – SU: 9-4-0 ATS: 4-9-0 O/U: 6-7-0
Week 11 – SU: 9-5-0 ATS: 8-6-0 O/U: 7-7-0
Week 12 – SU: 10-5-0 ATS: 7-8-0 O/U: 8-7-0
Week 13 – SU: 11-5-0 ATS: 8-8-0 O/U: 7-9-0
Week 14 – SU: 7-9-0 ATS: 9-6-1 O/U: 11-5-0
Week 15 – SU: 11-5-0 ATS: 6-8-2 O/U: 10-6-0
Week 16 – SU: 8-8-0 ATS: 10-6-0 O/U: 9-7-0
Week 17 – SU: 12-4-0 ATS: 5-10-1 O/U: 6-9-1
Week 18 – SU: 3-1-0 ATS: 2-2-0 O/U: 3-1-0
Week 19 – SU: 3-1-0 ATS: 3-1-0 O/U: 4-0-0
Indianapolis at Denver
Prediction: Broncos 29-22 (68.8%)
Pick: Colts +7
Total: Under 54
Dallas at Green Bay
Prediction: Packers 27-22 (64.0%)
Pick: Cowboys +6.5
Total: Under 53
Baltimore at New England
Prediction: Patriots 27-22 (63.7%)
Pick: Ravens +7
Total: Over 48
Carolina at Seattle
Prediction: Seahawks 24-17 (68.7%)
Pick: Panthers +10.5
Total: Over 40
NCAA Basketball Top 25 – 1/4/2015
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NFL Picks – Week 18 (Wildcard Round)
Total (weeks 1-17) – SU: 170-85-1 ATS: 126-124-6 O/U: 135-118-3
Week 1 – SU: 9-7-0 ATS: 8-8-0 O/U: 13-3-0
Week 2 – SU: 10-6-0 ATS: 10-6-0 O/U: 10-6-0
Week 3 – SU: 12-4-0 ATS: 9-6-1 O/U: 8-8-0
Week 4 – SU: 7-6-0 ATS: 5-7-1 O/U: 5-8-0
Week 5 – SU: 14-2-0 ATS: 6-9-0 O/U: 9-6-0
Week 6 – SU: 11-3-1 ATS: 8-7-0 O/U: 6-9-1
Week 7 – SU: 11-4-0 ATS: 7-8-0 O/U: 8-7-0
Week 8 – SU: 11-3-0 ATS: 8-7-0 O/U: 8-7-0
Week 9 – SU: 9-4-0 ATS: 8-5-0 O/U: 4-8-1
Week 10 – SU: 9-4-0 ATS: 4-9-0 O/U: 6-7-0
Week 11 – SU: 9-5-0 ATS: 8-6-0 O/U: 7-7-0
Week 12 – SU: 10-5-0 ATS: 7-8-0 O/U: 8-7-0
Week 13 – SU: 11-5-0 ATS: 8-8-0 O/U: 7-9-0
Week 14 – SU: 7-9-0 ATS: 9-6-1 O/U: 11-5-0
Week 15 – SU: 11-5-0 ATS: 6-8-2 O/U: 10-6-0
Week 16 – SU: 8-8-0 ATS: 10-6-0 O/U: 9-7-0
Week 17 – SU: 12-4-0 ATS: 5-10-1 O/U: 6-9-1
Week 18 – SU: 3-1-0 ATS: 2-2-0 O/U: 3-1-0
Arizona at Carolina
Prediction: Panthers 23-19
Pick: Cardinals +6.5
Total: Over 38
Detroit at Dallas
Prediction: Cowboys 24-23
Pick: Lions +7
Total: Under 50
Cincinnati at Indianapolis
Prediction: Colts 24-22
Pick: Bengals +3.5
Total: Under 50
Baltimore at Pittsburgh
Prediction: Steelers 23-21
Pick: Ravens +3.5
Total: Under 46.5
Stat pundit rankings: 2014 NFL win over/unders
TeamRankings really crushed it this year. Also, my mean absolute error was 2.25 and mean squared error was 7.05.
Cheers!
We are back for another edition of the stat pundit rankings, where we rank the accuracy of different predictions for team wins from statistics or simulation based websites. Team Rankings boasted the best performance last year, outperforming competitors and the totals set by sportsbooks as far as predicting 2013 regular season win totals.
Let’s meet our competitors for 2014:
Team Rankings (TR), predictions listed here
Accuscore (AS), predictions emailed by a loyal reader
FiveThirtyEight (538), predictions extracted the week before the regular season began (missing link)
Prediction Machine (PM), predictions listed here, released just after the season began
Football Outsiders (FO), projections listed here from just before the season began
Aggregate, the average statheads predictions from the five sites above
Finally, we will want to compare all the projections to lines set by sportsbooks. To do so, I used the implied lines used by Seth Burn in his…
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2014 blog in review
The WordPress.com stats helper monkeys prepared a 2014 annual report for this blog.
Here’s an excerpt:
The concert hall at the Sydney Opera House holds 2,700 people. This blog was viewed about 24,000 times in 2014. If it were a concert at Sydney Opera House, it would take about 9 sold-out performances for that many people to see it.
Click here to see the complete report.
Cheers!
Stats in the Wild 