Thursday, November 24, 2011

2011-11-24: 2011 NFL Season Week 12

Happy Thanksgiving!

I apologize for posting these a little late but I have been cooking food for the past three days. When I was not cooking I was reading papers about modifications to Support Vector Models to get some ideas to improve the accuracy of our predictions.
Adapting Ranking SVM to Document Retrieval concentrated on a modification of the hinge loss function when training the model to increase accuracy. Training a Support Vector Machine in the Primal points out that much literature jumps right to the dual optimization aspect of SVMs and does not pay enough attention to the primal problem. A portion of the paper mentions replacing the hinge loss function with one that is differentiable such as the Huber loss function.

While experimenting with SVM training I observed an interesting data point. Using NFL statistics from 2002 to 2010, one of the training methods assigned the following weights to the teams.
1.1276 Indianapolis Colts
1.1055 New England Patriots
0.5704 Philadelphia Eagles
0.4269 Pittsburgh Steelers
0.3317 Tennessee Titans
0.3184 San Diego Chargers
0.2922 Baltimore Ravens
0.2248 New Orleans Saints
0.1976 Green Bay Packers
0.1718 Jacksonville Jaguars
0.1621 Tampa Bay Buccaneers
0.0957 Carolina Panthers
0.0946 Atlanta Falcons
0.0877 New York Jets
0.0704 Chicago Bears
0.0504 New York Giants
-0.0569 Dallas Cowboys
-0.0689 Buffalo Bills
-0.0740 Miami Dolphins
-0.0812 Houston Texans
-0.1085 Denver Broncos
-0.1752 Cincinnati Bengals
-0.2420 Kansas City Chiefs
-0.3457 Cleveland Browns
-0.3631 Minnesota Vikings
-0.3634 Seattle Seahawks
-0.4150 Arizona Cardinals
-0.5037 St. Louis Rams
-0.5121 Oakland Raiders
-0.5633 Washington Redskins
-0.6925 San Francisco 49ers
-0.7623 Detroit Lions

Well it is time for me to break out the whipping cream and make some homemade whip cream for the pies I baked the other day. Here are the picks for this week.

Favorite Spread Underdog Discrete Pagerank
GB 6 at DET GB GB
at DAL 8 MIA DAL DAL
at BAL 3 SF BAL BAL
at STL 5 ARI STL STL
at NYJ 1 BUF NYJ BUF
at CIN 8 CLE CIN CIN
HOU 4 at JAX HOU HOU
CAR 7 at IND CAR IND
at TEN 20 TB TEN TEN
at ATL 11 MIN ATL ATL
at OAK 6 CHI OAK CHI
at SEA 5 WAS SEA SEA
NE 6 at PHI NE PHI
at SD 6 DEN SD DEN
PIT 11 at KC PIT PIT
at NO 3 NYG NO NO


-- Greg Szalkowski

Thursday, November 17, 2011

2011-11-17: 2011 NFL Season Week 11


Thursday Night Football, this week the NY Jets play at Denver. The Jets have a number of players on the injured list this week. Even with those injuries all three of our algorithms picked the Jets to win on Thursday.

The Jets injury list is not as bad as some of the other teams. Philadelphia's quarterback, Vick has two broken ribs and has not been at practice all week. Kansas City's quarterback Matt Cassel underwent hand surgery and will probably be out for the rest of the season.

A weakness of our algorithms is that they are heavily based on this years performance to date. A major injury to an important player that may or may not have an impact of game performance is not really taken into account. That is one of the reasons we have incorporated the Line data this year. Hoping that the "Collective Intelligence" of the crowd would help to point out teams that may not perform differently.




Favorite Spread Underdog Discrete Pagerank
NYJ 4.5 at DEN NYJ NYJ
at ATL 4 TEN ATL TEN
BUF 3.6 at MIA MIA BUF
at BAL 5 CIN BAL BAL
JAX 7 at CLE JAX JAX
at MIN 5 OAK MIN OAK
at DET 11 CAR DET DET
at GB 18 TB GB GB
DAL 8 WAS DAL DAL
at SF 8 ARI SF SF
at STL 2 SEA SEA SEA
at CHI 5 SD CHI CHI
at NYG 7 PHI NYG PHI
at NE 8 KC NE NE


-- Greg Szalkowski

Thursday, November 10, 2011

2011-11-10: 2011 NFL Season Week 10

Thursday Night Football is back! The match-up for tonight features the San Diego Chargers at home vs the Oakland Raiders.

This is a very close matchup according to the stats. San Diego has a offensive pass efficiency of 7.2 and Oakland 6.7. Oakland has a better run game but not by much. The defensive ratings are almost exactly the same with San Diego leading by a little bit.

The SVM and Neural Network both chose San Diego to win but the PageRank algorithm decided Oakland was a better choice.

Favorite Spread Underdog Discrete Pagerank
At SAN 8.5 OAK SAN OAK
PIT 1.5 At CIN PIT PIT
At KC 5 DEN KC KC
At IND 4 JAX JAX JAX
At DAL 3 BUF DAL DAL
HOU 7 At TB HOU HOU
At CAR 6 TEN Car TEN
At MIA 5 WAS MIA WAS
At ATL 6 NO ATL NO
At CHI 6 DET CHI CHI
At CLE 4 STL CLE STL
At PHI 11 ARI PHI PHI
BAL 4 At SEA BAL BAL
NYG 3 At SF SF SF
NE 10 At NYJ NE NYJ
At GB 14 MIN GB GB

-- Greg Szalkowski

2011-11-10: Day in the Life of a Computer Scientist

Old Dominion University has a freshmen computer science course that focuses on what it means to be a computer scientist. This course discusses career opportunities, current research being performed, and serves to debunk myths and misconceptions about the field of computer science. Such myths include: we never talk to humans, we code our entire lives away, and we are nocturnal. I was invited to be a guest lecturer for the class last night. Even though the last myth is sometimes true, I did my best to touch on each of these talking points during the presentation embedded below.




The first topics I spoke about in the presentation generated the majority of questions and discussion. I spoke first about the digital preservation work being performed in the WS-DL group at ODU. This, of course, included discussing the ArchiveFacebok, Warrick, and Memento projects at a cursory level. During our discussion, we hit on the issues of copyright and web crawling, and why, as computer scientists, we find these problems interesting. We briefly talked about revisitation policies and change-rate studies of web pages that are important for search engines and archival methods. (Interested readers should direct their attention to Cho and Garcia-Molina's work (1999) for a canonical study on recrawl and page change rates.) We also discussed why computing theory (not just development) is important in the current research being performed in the academic and industrial communities.

The remainder of my talk was a description of what I do on a daily basis as a professional computer scientist. I mentioned that I worked at The MITRE Corporation as a developer and researcher, and discussed what my job entails. For example, I practice Agile engineering, work with people on a daily basis, and probably only spend less than a quarter of my time in actual development. The remainder of my time is spent in testing cycles, working with customers to find direction for products, writing documentation, and other "non-coding" aspects of software development. Further, I discussed that MITRE is unique company in that it is a Federally Funded Research and Development Center (FFRDC), and supports the US government in an advisory roll. This point illustrated that there are variety of opportunities available to computer scientists, and not all of them are at traditional corporations.

My lecture was meant to illustrate that a professional developer doesn't sit in a dark cubicle all night hammering out code, and goes weeks without human interaction. More importantly, this presentation provided examples of work being done in industry and academia, and how the degree they are earning will benefit them in their career.


--Justin F. Brunelle

Saturday, November 5, 2011

2011-11-4: 2011 NFL Season Week 9

Week 9 is the last of the bye weeks for this year. Two games that have a higher level of chatter this week and should be good games to watch are the New England vs Giants game and the Pittsburgh vs Baltimore game.

The Patriots with Brady and the Giants with Manning, both have potent veteran quarterbacks and these game will probably play on the passing efficiency of both teams. The offensive passing efficiency of both teams is comparable at about 7.8 yards, however the Giants pass defense is better with only 5.9 yards given up compared to 7.5 for New England.

The rhetoric for the Baltimore vs Pittsburgh game has been rather lively. The Baltimore defense is possibly one of the best this year with a pass defense of only 4.8 yards given up although the offense is has not been stellar with a pass efficiency of 5.8 yards. Pittsburgh's pass offense is better, rated at 7.02 yards while their pass defense, while still decent, is not as good as Baltimore's with a rating of 5.1 yards.

Favorite Spread Underdog Discrete Pagerank
ATL 0.5 At IND ATL ATL
At NO 12 TB NO NO
At HOU 9 CLE HOU HOU
At BUF 4 NYJ BUF BUF
At KC 3 MIA KC KC
SF 4.5 At WAS SF SF
At DAL 6 SEA DAL DAL
At OAK 5 DEN OAK OAK
At TEN 3 CIN TEN TEN
At ARI 7 STL ARI STL
At NE 6 NYG NE NYG
At SD 2 GB GB GB
At PIT 3 BAL PIT BAL
At PHI 8 CHI PHI PHI

-- Greg Szalkowski

2011-11-05: Agile Engineering - ODU's ACM Meeting

I was invited to present an overview on Agile Development to Old Dominion University's ACM chapter. More specifically, I gave an overview of the Scrum method. My work in MITRE's Agile Engineering department has allowed me to practice Agile methodologies in the work force. Through this presentation, I shared my experiences with the members of the ACM.







Agile engineering's main focus is a shift from a linear development model. The Waterfall model is the classic example of a linear process model. Agile focuses on a cyclic and adaptive model. One of the main focuses of Agile is to receive and incorporate user feedback into the development process in order to produce a better product for the user. Also, it allows the product owner to garner greater control over a project.

Each cycle in Agile includes all of the traditional development steps: Requirements, Design, Implementation, Verification, and Assessment/Maintenance. These cycles are sometimes called sprints. At the conclusion of each sprint, a fully releasable product should be available. That is, the end of the sprint produces a product that has been through all of the necessary development steps and can be sold as a subset of the end-goal product. This provides the benefit of having a complete and deliverable product even if funding is cut or production must be halted.

An Agile development model provides the benefit of Failing Early. This means the development team can encounter and solve errors earlier in the development process and solve them when the costs are lower. An overly simplistic example would be the selection of a database. If MySQL is chosen at the beginning of a project using Agile, the development team would know earlier in the process if it was suitable for the solution. However, in the Waterfall model, it is possible to not understand the requirements until too late in the process to make a cheap switch.

An ODU WS-DL alumnus (Carlton Northern) has been instrumental in releasing a handbook for implementing Agile methods. This handbook provides guidelines for implementing Agile methods in the government (specifically the DoD) environment.

These resources should serve as an introduction to Agile methods and the benefits of using this development model.


-- Justin F. Brunelle