Monthly Archives: December 2014

Fantasy Football Results, 2014 Season

fantasy football eric 2014

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.

NFL Picks- Wildcard Round of 2015 Playoffs

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.

Code Monkey Monday- Hiding Excel Equations in Cells

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.

excel hiding equations

NFL Picks- Week 17 of 2014

Overall against the spread: 63-52
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

1-2 in games highlighted last week. 11-13 overall.

Here are my week 16 predictions, with the current line in parentheses:

Carolina Panthers at Atlanta Falcons (-3.0): Predicting 21.2-26.6. Bet on the Atlanta Falcons.
Cleveland Browns at Baltimore Ravens (-13.5): Predicting 16.7-25.1. Bet on the Cleveland Browns.
Detroit Lions at Green Bay Packers (-7.5): Predicting 18.6-25.4. Bet on the Detroit Lions.
Jacksonville Jaguars at Houston Texans (-9.5): Predicting 14.4-25.7. Bet on the Houston Texans.
San Diego Chargers at Kansas City Chiefs (-1.0): Predicting 18.7-23.9. Bet on the Kansas City Chiefs.
New York Jets at Miami Dolphins (-6.5): Predicting 17.3-26.5. Bet on the Miami Dolphins.
Chicago Bears at Minnesota Vikings (-6.5): Predicting 19.8-26.8. Bet on the Minnesota Vikings.
Buffalo Bills at New England Patriots (-5.0): Predicting 18.7-26.8. Bet on the New England Patriots.
Philadelphia Eagles at New York Giants (-2.5): Predicting 26.1-26.6. Bet on the Philadelphia Eagles.
Cincinnati Bengals at Pittsburgh Steelers (-3.5): Predicting 22.1-26.1. Bet on the Pittsburgh Steelers.
New Orleans Saints at Tampa Bay Buccaneers (+4.0): Predicting 23.9-23.2. Bet on the Tampa Bay Buccaneers.
Indianapolis Colts at Tennessee Titans (+6.5): Predicting 27.6-21.0. Bet on the Indianapolis Colts.
Dallas Cowboys at Washington Redskins (+3.5): Predicting 26.4-21.6. Bet on the Dallas Cowboys.
St Louis Rams at Seattle Seahawks (-11.5): Predicting 16.4-25.4. Bet on the St Louis Rams.
Oakland Raiders at Denver Broncos (-14.0): Predicting 17.9-31.4. Bet on the Oakland Raiders.
Arizona Cardinals at San Francisco 49ers (-7.0): Predicting 18.3-19.3. Bet on the Arizona Cardinals.

Each week I’ll show all the predictions, as above, and I’ll pick three games that I feel most confident about, as I look at my model and think about what I’ve seen watching football. Here are the 3 teams I would actually bet on ATS (against the spread):
Falcons, Dolphins, Raiders

Book Review- Who Moved My Cheese?

Who Moved My Cheese?
by Dr. Spencer Johnson, 1998

who moved my cheese

A short silly parable to teach you to change and adapt with new circumstances. Don’t be like Hem, the little person who can’t get over the fact that his prosperity seemed to dissipate overnight when his Cheese disappeared. Instead, adapt to good and bad circumstances to make yourself flexible and resilient. Find new Cheese.

When I joined Booz Allen Hamilton in 2011, I went to a multi-day orientation. On the first day, we were asked what adjective best described each of us as we started our new job. There were 8ish options, including proficient, responsive, and conscientious. I chose “adaptable”, because, frankly, I didn’t know what I was supposed to do in my job and I just had a lot of general intelligence-based skills. I was 24. The older new employees scoffed at my stupid answer. Being adaptable served me well, though, as I learned a ton of new skills, led projects in areas in which I was previously ignorant, and responded well to setbacks. Point is: this book wasn’t really written for me, I already knew its message. I don’t want to give it a bad review for that reason, but I didn’t get a whole lot out of it. I listened to it on CD on the same trip I listened to Superman Versus the Ku Klux Klan.

Amazon Link: Who Moved My Cheese?: An Amazing Way to Deal with Change in Your Work and in Your Life

Forecasting Attendance at Baseball Games

Here is a pdf of my most recent school project: Predicting Day-to-Day Variability in Baseball Attendance to Support Staffing

It details how I used 30 years of attendance data at MLB games to determine what is important in predicting attendance. A lot of businesses surrounding stadiums rely upon accurate forecasts of attendance in order to staff their business appropriately. If the effect of short-term factors (weather, recent performance) dominate, schedulers would do well to wait until the last minute to put out a staff schedule. However, it seems that long-term factors (date/time of game, opponent, performance in past seasons) dominates the attendance regression, giving schedulers the ability to put out schedules well in advance of gameday. A missing short-term regressor in my paper is pitching matchup. If star starting pitchers really bring more fans to the game, that might increase the importance of the short-term factors.

Two Links Tuesday- December 23, 2014

The Conventional Wisdom on Oil is Always Wrong: Interesting piece about oil in the 2000’s. The U.S. is on track to pass Saudi Arabia in crude oil production.

Cherry Picking Probably Won’t Work in the NBA: But teams should definitely try it occasionally. I’d like to see a team that loses the ball and has a player down on the offensive end leave that player on offense as a cherry-picker instead of trying to catch up to the 5 on 4 break. I feel like there is more value in that than in being back late on defense, especially in the fast-moving NBA.

Code Monkey Monday- Transferring a MySQL Database with MySQL Workbench

I have a desktop work computer and a home laptop. For a recent project, I needed access to the same MySQL database from both computers, as I worked on the project at both locations. The database was hosted locally on my work computer. One option would be to VPN to my work computer, but that wasn’t an attractive option for various reasons. I decided that I wanted the database hosted on both computers locally.

To move a MySQL database to another computer,
1. Open MySQL Workbench on the computer currently hosting the database.
2. Goto Server -> Data Export in the menu
3. Select the database you want to copy, and select a destination in the “Export to Self-Contained File” field.
4. Click Start Export
5. Once done exporting, transfer the dump file to the other computer
6. Open MySQL Workbench on the second computer
7. Goto Server -> Data Import in the menu
8. Select “Import from Self-Contained File” and the dump file just transferred.
9. Click Start Import.

You should be good to go. Copying multiple databases or giant databases might be trickier, but this works in most cases.

Good day for basketball

UNC (ranked #24) over-powered OSU (#12) inside to win 82-74. Indiana held Butler (#23) to poor shooting inside and outside and won 82-73.

And Kentucky (#1) held UCLA to 7 points in the first half in route to an 83-42 blowout. Smothering defense.

Big wins for all three of my favorite teams, even if the losers were my 4th, 7th, and 9th favorite teams.

uk ucla

Betting on Underdogs

This week the lines-makers seem to have gone a little too far for almost every NFL game. My model picks the underdog in each matchup (against the spread, obviously), except the Titans-Jags game. Surprisingly, it picks the favorite, the Jaguars, in that game (and they covered).

According to oddsshark.com, underdogs are 110-111-4 against the spread this season. So it seems unlikely that the line-makers are consistently off. Perhaps my model is over-regulated and holding predicted scores too close to the mean score. I will do more analysis, but know that this is a model that would win almost 53% of its bets over the past 30 years if it bet on every game.