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NFL Picks – Week 12 of 2016

New output format this week, showing each team’s offense and defense coefficients. Negative spreads mean the home team is favored. Remember that there is a 3 point home field advantage.

Overall Against the Spread: 65-71
Week 2: 8-8
Week 3: 10-6
Week 4: 6-9
Week 5: 5-8 (1 push)
Week 6: 7-6 (2 pushes)
Week 7: 3-11 (1 game not bet)
Week 8: 6-7
Week 9: 5-6 (1 game not bet, 1 push)
Week 10: 8-6
Week 11: 7-4 (1 game not bet, 2 pushes)

week-12-of-2016

Book Review – The Marshmallow Test

The Marshmallow Test: Mastering Self-Control
by Walter Mischel, 2014

the-marshmallow-test

The marshmallow test was an experiment that checked whether kids would hold out eating a visible treat in order to get two of the treat after a wait. Turns out that this self-control was highly predictive of success in life. This book is by the architect of the original experiment and discusses ways to increase self-control to improve outcomes in life. Pairs well with Willpower.

The audiobook version is read by Alan Alda! Which makes everything better.

NFL Picks – Week 11 of 2016

Overall Against the Spread: 58-67
Week 2: 8-8
Week 3: 10-6
Week 4: 6-9
Week 5: 5-8 (1 push)
Week 6: 7-6 (2 pushes)
Week 7: 3-11 (1 game not bet)
Week 8: 6-7
Week 9: 5-6 (1 game not bet, 1 push)
Week 10: 8-6

Here are my week 11 predictions, with the current line in parentheses:
New Orleans Saints at Carolina Panthers (-3.0): Predicting 25.6-27.9. Bet on the New Orleans Saints.
Tennessee Titans at Indianapolis Colts (-3.0): Predicting 25.6-27.6. Bet on the Tennessee Titans.
Arizona Cardinals at Minnesota Vikings (even): Predicting 17.8-20.6. Bet on the Minnesota Vikings.
Chicago Bears at New York Giants (-7.0): Predicting 16.8-23.8. Line is correct; do not bet.
Buffalo Bills at Cincinnati Bengals (-3.0): Predicting 23.8-23.9. Bet on the Buffalo Bills.
Baltimore Ravens at Dallas Cowboys (-7.0): Predicting 17.8-24.9. Bet on the Dallas Cowboys.
Pittsburgh Steelers at Cleveland Browns (+7.5): Predicting 25.8-22.3. Bet on the Cleveland Browns.
Jacksonville Jaguars at Detroit Lions (-6.5): Predicting 19.6-26.3. Bet on the Detroit Lions.
Tampa Bay Buccaneers at Kansas City Chiefs (-7.0): Predicting 19.2-25.6. Bet on the Tampa Bay Buccaneers.
Miami Dolphins at Los Angeles Rams (+1.5): Predicting 19.3-20.6. Bet on the Los Angeles Rams.
New England Patriots at San Francisco 49ers (+13.0): Predicting 27.5-21.4. Bet on the San Francisco 49ers.
Philadelphia Eagles at Seattle Seahawks (-6.5): Predicting 19.6-21.2. Bet on the Philadelphia Eagles.
Green Bay Packers at Washington Redskins (-2.5): Predicting 22.4-26.7. Bet on the Washington Redskins.
Houston Texans at Oakland Raiders (-6.0): Predicting 19.5-25.6. Bet on the Oakland Raiders.

Book Review – Zero to One

Zero to One: Notes on Startups, or How to Build the Future
by Peter Thiel, with Blake Masters, 2014

zero-to-one

Good short book about the importance of businesses being actual improvements over what came before. Thiel is focused on technology, and his advice is not generalizable to all industries. He says that any new product should be a 10x improvement over the previous offering in order to gain acceptance. 10x easier to use, cheaper, better, and/or faster. Anything less won’t overcome the switching costs of moving to the new product.

I really liked the discussion of society’s optimism/pessimism and beliefs about whether the future is determinate or indeterminate. The US used to be deterministic optimists. We knew the future would be better than today and specific projects were undertaken to bring about this improvement. Somewhere along the lines, the determinate became indeterminate in the US. People still thought the future would be better than the present, but they weren’t really sure how. In a determinate world, many of the brightest minds become inventors, scientists, and engineers striving to create the future. In an indeterminate world (like today in the US), many of the brightest minds become attorneys, consultants, and bankers in order to profit from a better world without really creating it themselves. This is part of the reason why many of the technology thought leaders (Elon Musk comes to mind) seem so eccentric nowadays. They often have a view of the future that they want to create, and this clashes with an indeterminate populace that is not really sure how to move progress forward. At least we’re not pessimists like much of the rest of the world.

NFL Picks – Week 10 of 2016

Overall Against the Spread: 50-61
Week 2: 8-8
Week 3: 10-6
Week 4: 6-9
Week 5: 5-8 (1 push)
Week 6: 7-6 (2 pushes)
Week 7: 3-11 (1 game not bet)
Week 8: 6-7
Week 9: 5-6 (1 game not bet, 1 push)

Here are my week 9 predictions, with the current line in parentheses:
Cleveland Browns at Baltimore Ravens (-8.0): Predicting 18.1-26.0. Bet on the Cleveland Browns.
Denver Broncos at New Orleans Saints (-2.5): Predicting 23.8-24.9. Bet on the Denver Broncos.
Houston Texans at Jacksonville Jaguars (+1.0): Predicting 20.7-21.9. Bet on the Jacksonville Jaguars.
Minnesota Vikings at Washington Redskins (-3.0): Predicting 20.1-21.8. Bet on the Minnesota Vikings.
Atlanta Falcons at Philadelphia Eagles (even): Predicting 24.7-28.3. Bet on the Philadelphia Eagles.
Green Bay Packers at Tennessee Titans (+2.5): Predicting 23.5-25.1. Bet on the Tennessee Titans.
Chicago Bears at Tampa Bay Buccaneers (-1.0): Predicting 21.0-23.7. Bet on the Tampa Bay Buccaneers.
Kansas City Chiefs at Carolina Panthers (-3.0): Predicting 22.2-23.2. Bet on the Kansas City Chiefs.
Los Angeles Rams at New York Jets (-2.0): Predicting 19.9-22.3. Bet on the New York Jets.
Miami Dolphins at San Diego Chargers (-4.0): Predicting 22.3-27.9. Bet on the San Diego Chargers.
Dallas Cowboys at Pittsburgh Steelers (-2.5): Predicting 22.9-22.5. Bet on the Dallas Cowboys.
San Francisco 49ers at Arizona Cardinals (-13.5): Predicting 18.2-28.4. Bet on the San Francisco 49ers.
Seattle Seahawks at New England Patriots (-7.5): Predicting 16.9-23.4. Bet on the Seattle Seahawks.
Cincinnati Bengals at New York Giants (-2.5): Predicting 19.6-23.9. Bet on the New York Giants.

Links 20161109

Trump Rode a Wave of Economic Angst. Will He Harness America’s Greatest Economic Opportunity? There are now more jobs in the solar industry than in oil/gas/coal extraction. The clean energy market (solar, wind, electric vehicles, energy storage, etc) is job opportunity and a future leadership opportunity. While I don’t expect him to subsidize clean energy, I hope Trump’s presidency won’t actively harm this sector.

Re-regulation on the horizon? Could we actually see states move from de-regulated utilities back to regulated? It’s hard to imagine, but market mechanisms are making base load generation impossible in many cases. The marginal prices aren’t covering the fixed costs.

Dept of Transportation unveils national electric vehicle charging network. Helps solve the chicken and egg problem.

INFORMS 2016 Presentations

Come show me some love in Nashville. Here are my presentations:

1. Session MC29 – Issues in Energy Efficiency and Renewable Energy
November 14, 2016, 1:30 – 3:00 PM, 202A-MCC
3rd Presentation (of 3): Mind The Gap: Coordinating Energy Efficiency And Demand Response
Authors: Eric Webb, Owen Wu, Kyle D. Cattani, Kelley School of Business, Indiana University
Abstract: Traditionally, energy demand-side management techniques, such as energy efficiency (EE) and demand response (DR), are evaluated in isolation. We examine the interactions between long-term EE upgrades and daily DR participation at an industrial firm. We find that EE and DR act as substitutes in terms of reduction of peak electricity demand, and the long-studied energy efficiency gap between firm-optimal and societal-optimal levels of EE is smaller when DR is considered. We suggest three approaches to reducing the energy efficiency gap, including an original suggestion that relies upon the interactions between EE and DR.

2. Session TC34 – Public Policy and Healthcare Operations
November 15, 2016, 1:30 – 3:00 PM, 204-MCC
2nd Presentation (of 3): Predicting Nurse Turnover And Its Impact On Staffing Decisions
Authors: Eric Webb, Kurt Bretthauer, Kelley School of Business, Indiana University
Abstract: Nurse turnover remains a significant problem in skilled nursing facilities across the United States. High turnover leads to two important questions: (1) Hiring decisions – What applicant attributes should be valued when hiring nurses, in order to hire nurses that are effective at their jobs and likely to stay for a long duration? (2) Staffing decisions – How should nurse workload be managed in order to prevent burnout and decrease turnover? Based on a large dataset from skilled nursing facilities in the United States, we first use a survival model to predict nurse turnover. For this talk we then focus on staffing and incorporate these empirical results into analytical models for nurse staffing decisions.

3. Session WC31 – Consumer Behavior in Services
November 16, 2016, 12:45 – 2:15 PM, 202C-MCC
4th Presentation (of 4): Linking Customer Behavior And Delay Announcements: Are Customers Really Rational?
Authors: Eric Webb, Qiuping Yu, Kurt M. Bretthauer, Kelley School of Business, Indiana University
Abstract: We empirically explore customer abandonment behavior in the presence of delay information using data from a call center. Previous work has assumed that customers are at least partially rational in responding to announcements. In contrast, we relax all rationality assumptions. Our findings indicate that customers exhibit loss aversion behavior. In addition, customers may update their announcement-induced reference point as they hear subsequent announcements. Our results also indicate that customers may fall for the sunk cost fallacy while waiting in the queue. We show the impact of these effects on staffing decisions using a classic staffing model.

4. Session WE32 – Sports and Entertainment
November 16, 2016, 4:30 – 6:00 PM, 203A-MCC
3rd Presentation (of 4): Using Past Scores And Regularization To Create A Winning NFL Betting Model
Authors: Eric Webb, Kelley School of Business, Indiana University, and Wayne L. Winston, Bauer College of Business, University of Houston
Abstract: Is the National Football League betting market efficient? We have devised a profitable betting model that would win 52.7% of the 7,705 bets against the spread it would have made over 34 seasons. Scores from previous weeks are used to estimate the point value of each team’s offense and defense. These values predict next week’s scores, and a bet is placed against the advertised spread. The sum of squares of offensive/defensive point values are constrained to be less than a regularization constant.