Overall against the spread: 77-62
Divisional: 3-1
Wildcard: 3-1
Week 17: 8-8
Week 16: 11-4
Week 15: 7-9
Week 14: 6-9
Week 13: 10-6
Week 12: 8-6
Week 11: 9-5
Week 10: 6-7
Week 9: 6-6
Here are my division round predictions, with the current line in parentheses:
Green Bay Packers at Seattle Seahawks (-7.5): Predicting 21.4-25.0. Bet on the Green Bay Packers.
Indianapolis Colts at New England Patriots (-6.5): Predicting 22.8-27.9. Bet on the Indianapolis Colts.
Thinking, Fast and Slow
by Daniel Kahneman, 2011
This is a great book that hits on all the research in behavioral economics and cognitive biases. It’s also a devilishly slow read. 400+ pages, with each page probably averaging 4+ minutes for me as I read it and contemplated its significance. I’ve been reading it slowly over the last 2 years.
Here’s the list of topics it will discuss at length, in alphabetical order:
affect heuristic
anchoring
associative memory
availability heuristic
Bayesian statistics
causal base rates
certainty effect
cognitive strain
confirmation bias
conjunctive fallacy
decision utility
decision weights
denominator neglect
disposition effect
duration neglect
ego depletion
endowment effect
experienced utility
expert intuition
focusing illusion
halo effect
hindsight bias
illusion of understanding
insufficient adjustment
intensity matching
law of small numbers
loss aversion
mental accounts and keeping score
mental shotgun
narrative fallacy
narrow/broad framing
negativity dominance
optimistic bias
outcome bias
overconfidence
overestimation of rare events
pattern seeking
peak-end rule
planning fallacy
preference reversals
priming and associations
prospect theory
regression to the mean
remembering self
risk aversion/seeking
stereotypes
substitution
sunk cost fallacy
System 1/2
what you see is all there is (WYSIATI)
Learning about these terms and recognizing when your human brain is leading you astray will improve your future decision making.
I’ve started to keep the first page of each academic paper that I read in a binder, marked with my notes about the paper’s content and usefulness. I started doing this in June 2014. Between June and December, I read 89 academic papers. 40 of those were for Kurt Bretthauer’s Service Operations class.
By Decade:
1960’s: 1
1970’s: 3
1980’s: 9
1990’s: 16
2000’s: 24
2010’s: 35
(I’m surprised the 2010’s beat the 2000’s by that much)
Journals (with more than 1 paper read):
Production and Operations Management: 11
Management Science: 10
Manufacturing & Service Operations Management: 9
Operations Research: 8
Harvard Business Review: 4
Journal of Sports Economics: 3
Applied Economics: 2
Decision Sciences: 2
Interfaces: 2
Journal of Marketing: 2
Total citations among 89 papers: 47,531
Max citations: 15,588
Total citations among top 9 papers: 40,318
Mean citations: 573
Median citations: 54
Papers with less than 5 citations: 20, though some are very new
If interested, the full Excel list is here.
Overall against the spread: 74-61
Wildcard: 3-1
Week 17: 8-8
Week 16: 11-4
Week 15: 7-9
Week 14: 6-9
Week 13: 10-6
Week 12: 8-6
Week 11: 9-5
Week 10: 6-7
Week 9: 6-6
Here are my division round predictions, with the current line in parentheses:
Baltimore Ravens at New England Patriots (-7.0): Predicting 20.8-26.1. Bet on the Baltimore Ravens.
Carolina Panthers at Seattle Seahawks (-11.0): Predicting 15.9-25.3. Bet on the Carolina Panthers.
Dallas Cowboys at Green Bay Packers (-6.5): Predicting 24.4-28.7. Bet on the Dallas Cowboys.
Indianapolis Colts at Denver Broncos (-7.0): Predicting 24.2-29.0. Bet on the Indianapolis Colts.
My model says the lines are all too high, which was my intuition when looking at them. It’s only Monday though, maybe they’ll move down by game time. I would bet on the home teams if the lines were -5, -9, -4, and -4.5, respectively.
Eric. Bengals Fan.
Maria. Colts Fan.
Rematch, Sunday 1pm, in Indy. Round 1, week 7, did not go super well for the Bengals.
Vegas has the line at Colts -3.5. My model says that is a little low. Bengals are super unpredictable though, so who knows.
I would like to see a Cincinnati team win a playoff game/series for the first time since 1995. That would be nice.
Come watch it with us.
Living with Water Scarcity
by David Zetland, 2014
Living with Water Scarcity gives an economical evaluation of the state of water in the U.S. and abroad. The premise of the book is that water should be treated as a valued, scarce commodity. In reality, consumers are given poor incentives toward the limited use of water and social planners/politicians often poorly allocate water when faced with varied water demands from households, businesses, farmers, and the ecosystem. The book asks plentiful questions about the treatment and allocation of water and suggests answering the questions economically.
I was hoping to like the book more than I did. The first few chapters, on personal, household economics, read well. However, the second half of the book, about the public allocation of water flows, became both whiny and preachy. Whiny in that it complains of corrupt politicians and lazy government water managers. Preachy in that it speaks of the effect of mismanagement of ecosystems in light of climate change. There were also a stream of stick figure illustrations throughout that made the book seem amateur and sarcastic. I think the topic of water economics is of value, but I hope that there are better books out there to learn of the subject. If still interested, the book can be downloaded in .pdf form for free from http://livingwithwaterscarcity.com/.
People ask me all the time what I’m working on. While the Current Projects page has a little bit of relevant information, it is intentionally incomplete. I have a list of the multitude of projects that I am working on at this time.
Hopefully leading to academic papers:
-Prehospital Triage paper
-NFL betting model
-Sunk Costs in Call Centers Project
-Energy research (beginning in January)
-Forecasting Sports Attendance to aid in staffing decisions
-End-game decision making in basketball
-Anchoring effect of online advertisements
Conferences:
-Sloan Sports Analytics Conference in February, as a spectator
-Potentially POMS, INFORMS Healthcare, and MSOM, depending on funding and talk submission
Interesting projects (most of which do not have a defined goal or end-state at this time):
-Compiling list of seminal papers in operations management/research
-Applying network-based ranking system to sports leagues
-Writing and recording video lectures based on my graduate studies (for website and for future student reference)
Courses (Spring 2015):
-4 Operations Management/Decision Science topical courses (half-semester each)
-Data Mining course (half-semester)
-Information Economics (half-semester)
(Expect to read 3-5 academic papers per class per week. 3 classes each half-semester, so 10-15 papers per week.)
Personal Projects:
-Plan wedding
-3-5 website posts per week
-Fantasy Football (just finished season)
–Watch Sports
-Work out or exercise 3-4 times per week, keeping track of lifting improvements
-Read lots of books (currently reading: Thinking Fast and Slow by Kahneman, Blackett’s War by Budiansky, Common Errors in Statistics by Good, It Works by Evans, Microeconometrics by Cameron, Master and Commander by O’Brian)
-Keep personal lists (books read, movies watched, etc)
-Have lots of dinner parties and other parties
I worry that I have too much on my plate, and I am very busy. But I enjoy the variety, and neither my coursework nor research seems to be suffering. So I carry on.
Eric
I finished my regular season 10-3, in first place in my league, despite scoring only the 6th most points in my 12 team league. I had the fewest points scored against me. I got a bye in the playoffs, won my first matchup, and lost (in excruciating fashion 74-73) in the finals. So a 2nd place finish.
I won in spite of my awful draft. My first 5 picks in my snake-draft (with the last pick in the first round): Doug Martin, Montee Ball, Keenan Allen, Vincent Jackson, Trent Richardson. All busts. I did some fancy maneuvering to put myself in a position to win each week. I made 4 of the approximately 7-8 trades in my league. My final roster included only 3 players that I drafted (Emmanuel Sanders (6th round), Jeremy Hill (10th), and Trent Richardson (5th)). My final roster included Matthew Stafford (traded Kaepernick for Stafford), Jeremy Hill, Boom Herron (free agent), Odell Beckham Jr (traded Zach Ertz for Beckham, great trade), Emmanuel Sanders, Kenny Stills (free agent), Deandre Hopkins (complicated 3 for 3 trade), Dwayne Allen (complicated 3 for 3 trade), and Dan Bailey. I plug and play at Defense.
Maria
Maria was the 2 time defending champion in her league. This year, she was 1st in her regular season, going 10-4 with the most points in her league. She had a tough week in the first week of her playoffs and lost, however. She won the 3rd place game the next week to finish in third place. Her league is an auction draft that allows for up to 5 keepers each year. She has some great keeper options for next year, including:
Relatively expensive options: Peyton Manning, Antonio Brown, Arian Foster
Very cheap options: Kelvin Benjamin, Deandre Hopkins, Christine Michael, Devonta Freeman, Bishop Sankey, Kenny Stills, Jordan Reed, Boom Herron, and Alfred Blue
Altogether, a pretty successful year. Always frustrating to lose in the playoffs, though.
Overall against the spread: 71-60
Week 17: 8-8
Week 16: 11-4
Week 15: 7-9
Week 14: 6-9
Week 13: 10-6
Week 12: 8-6
Week 11: 9-5
Week 10: 6-7
Week 9: 6-6
0-3 in games highlighted last week. 11-16 overall. Well, that experiment proved not too promising. I was hoping that I would be able to pick the best games to bet on. But my model, used in every game, vastly outperformed my choice of which 3 games to bet on each week. So I’ll stop highlighting games to bet on in the future.
Here are my wildcard predictions, with the current line in parentheses:
Arizona Cardinals at Carolina Panthers (-7.0): Predicting 19.3-20.6. Bet on the Arizona Cardinals.
Baltimore Ravens at Pittsburgh Steelers (-3.0): Predicting 23.2-25.1. Bet on the Baltimore Ravens.
Cincinnati Bengals at Indianapolis Colts (-3.5): Predicting 21.4-26.5. Bet on the Indianapolis Colts.
Detroit Lions at Dallas Cowboys (-8.0): Predicting 19.1-24.9. Bet on the Detroit Lions.
This isn’t a particularly high-tech post, but it helped me out in tricking innocent bystanders of a cell’s true intention. Suppose you are using Excel and want to show someone a nonsensical output from a cell evaluation. You type in something innocuous, like =rand(), which should give a random number between 0 and 1. If you want the “random” number to always be between .5 and .75, however, you could type =rand()*.25+.5. In my case, I wanted to show someone the equation “=rand()” but the output from “=rand()*.25+.5”, so that whenever I updated, it would give a number between .5 and .75. The observer would be confused and hilarity would ensue as the “random” number always falls between .5 and .75. To do this, type “=rand()” at the far left of the cell equation box, like normal. Then put a bunch of spaces until you get to the middle of the equation box, and put “*”. Then put more spaces until you are off the initial screen and type the rest of the equation “.25+.5”. Now, when the equation is viewed, the observer will only see the “=rand()”, unless they are looking very closely and notice the odd multiplication sign in the middle of the line. In my experiments, I have found that Excel will delete your excessive spaces if you only put “=rand()” on the far left and “*.25+.5” off the screen. For some reason, the spaces are not deleted if you type something in the middle of the equation box. Use this information as you will.
