The main rating software is written in C++. Data is stored in a MySQL database, and rendered on the web with PHP and Javascript. If you would like to write your own rating software, Octave is a good high-level mathematical language.

Why don't the pages display correctly?

The site is written and tested for the Firefox web browser. Limited resources prevent extensive research on compatability issues with other browsers.

Where do you get your data?

Most scores are collected electronically from a variety of publicly domain sources. Many individuals have graciously shared the results of their own data collection efforts. When convenient, basic consistency checks are run on multiple independent sources to verify the data's accuracy. Corrections and hard-to-find scores are entered manually.

How do you deal with forfeits?

Forfeited results are not factored into the computer ratings. If an on-the-field outcome was later forfeited, the original score is used in the calculations, but the result is stricken from the win-loss records.

How do you deal with exhibition games?

My policy is that a game doesn't count as an exhibition unless both participating teams deem it so. If one team counts it as an official game, but their opponent doesn't, it gets marked exhibition since I can't judge the sincerity of strategy and effort in such contests.

Does conference affiliation affect the ratings?

I don't do any prior weighting of conferences, and therefore conference affiliation plays no direct role in the ratings. Schedule differences are implicit in the model. Conferences that perform well in inter-conference matchups will naturally be rated higher. Since these games provide a reference point for the entire conference, the rising tide lifts all boats. For this reason, non-conference games are in some sense more significant than conference games.

Are you satisfied with the BCS formula?

Over the years, the BCS has gotten criticized for fine-tuning its formula. Recent changes have simplified the system for the better and removed extraneous redundancies. The current setup is a good balance of the traditional human polls, which the fan base is most comfortable with, and the objective computer component. Over the years, the two methods have tended to converge as the computers have revealed to the human voters the dangers of regional bias and misunderstanding of schedule strength. There will always be controversy when the formula must split hairs between #2 and #3, but the system is stable and beginning to be accepted by the media and fans.

What would you change?

I think the biggest thing that is hurting college football is the lack of quality inter-conference games. Due to the premium placed by the media on win-loss records, most athletic directors are trying to assure themselves of 3-4 easy home wins each year in their out-of-conference schedule. Great matchups like Texas vs Ohio St in 2005 are few and far between. I would like to see something like an ACC-SEC challenge, whereby teams are matched up for 12 games over one weekend. This would get fans and media excited, and also provide a more solid basis for comparing teams from different conferences.

An increase in good matchups would require a shift in philosophy by the human polls. Currently they start with a preseason notion of who will be good, and adjust each week according to a predictable pattern. They are reluctant to go back and re-evaluate earlier results in light of new information, and thus prior biases are likely to compound as the season goes on. One result is that a 8-3 team that played a brutal schedule is often penalized, while and 11-0 team with a weak schedule is rewarded. Sometimes this strategy backfires (e.g. Auburn 2004), but in general padding ones record with wins means a higher poll ranking. Delaying the release of human polls until mid-season would help minimize bias and develop more respect for teams that play challenging early season non-conference schedules.

Do you favor a college football playoff?

The BCS system is the best college football has ever had to determine an undisputed champion. It is really a two team playoff. So the correct question is whether I favor expanding the number of teams in the playoff. College football is unique among all sports in that every regular season game is vital. Also, the bowl system provides a great reward to players and fans, allowing many schools to finish the year on a high note. A playoff should not ruin this. I would favor a 4 team playoff (the so called "plus one" system), or possibly 8 teams if it was done right, but no more than that.

What is the purpose of this web site?

I maintain this web site primarily as a hobby which creatively combines my interests in math, sports, and computer programming. I enjoy sharing my work with the visitors to my site. The Massey Ratings also serve an official purpose, most notably as a component of college football's BCS.

How long have you done ratings?

My college football ratings were initially posted in 1995 at RSFC. Since then, I have produced ratings for many pro, college, and high school sports. I continually work to improve the content and quality of my ratings and web site. The Massey Ratings have been part of the BCS since 1999.

What is the purpose of the computer ratings?

In any competetive league, there should be an objective and robust method to measure the performance of each team/individual. Win-loss records may be misleading if teams play disparate schedules, and polls suffer from human limitations and subjectivity.

After devising a mathematical model for the sport, an algorithm is implemented, and the resulting computer ratings objectively quantify the strength of each team based on the defining criteria.

How does your rating system work?

There is really no simple answer to this question (although I was once asked to provide one during a live interview on ESPN). Basicly, the ratings are the solution to a large system of equations, which comes from a statistical model and actual game data. For more details, see the Massey Rating Description.

Do you get paid for this?

No, I currently have no paying arrangements with advertisers or sponsors. The BCS does not pay for the rights to use my ratings, but I consider it an honor that they choose to use them in the formula. Click here if you would like to make a donation to support the maintainance of the web site, or email me if you would like to discuss a formal sponsorship or publication rights.

How much time does it take?

I have written a fairly robust software to automate the calculations and web page generation. Daily updates require little intervention on my part. The bulk of my time is spent maintaining data files and writing computer code.

Can I get a copy of your software?

My software is a work in progress, and is not very user-friendly. I hope to one day have a version suitable for the public domain.

How big is your operation?

It's pretty much a one man show. I am researcher, programmer, database manager, webmaster, and marketer. This is all done in my spare time from an apartment office in Roanoke, VA. My computer is a Systemax built system with an AMD 64 bit 3200+ processor and 1G of RAM running Mandrake 9.2 Linux.

Where do you get your data?

I get data from various online sources, and appreciate the efforts of colleagues who are willing to share their data. Daily scores for major sports are obtained from USA Today. I have written software that parses these web pages and saves the game scores to a data file. To minimize errors, scores are crosschecked with alternate sources when possible.

How often do you update your pages?

Recently I automated the daily updates. Ratings are updated each morning around 6:30 EST, and the prediction pages are updated each hour until noon. Some sports, such as college football or the NFL are updated weekly.

Is the Massey computer system the best?

This depends on what goals you feel a rating system should meet. Should the rating system be predictive, or should it only measure and reward past performance (such as to determine who deserves the college football national championship)? What data is available? How is the model defined? Basicly any rating system can claim to be the best with respect to what it sets out to accomplish.

That said, I believe that the Massey Ratings satisfy all of the desirable properties of a rating system. The sophistication of the model and algorithm is beyond any other method I'm aware of. Every feature of my system is based on sound statistical assumptions regarding the nature of sports and games. There are rarely any skewed or highly abnormal results, and the Massey Ratings are highly correlated with the consensus.

My rating model has undergone several revisions. These changes are necessary to improve the quality of my ratings in light of new ideas, gained experience, and access to more historical data with which to refine the method.

What's the difference between "rating", "ranking", and "poll"?

A "ranking" is simply an ordinal number (such as 1st, 2nd, 3rd,...) that indicates a team's placement in a strictly non-quantitative sense. In contrast, a team's "rating" is generally a continuous scale measurement and must be interpretted on a scale by comparing it with other teams' ratings. For example, I can rank three teams as follows: (1) Team A, (2) Team B, (3) Team C. This tells me that according to my ranking criteria, A is better than B, and B is better than C. However, it does not tell me how much better. If ratings are assigned as (A = 9.7, B = 9.5, C = 1.2), then it is easy to see that in fact A and B are quite competitive while C is significantly inferior.

A poll is fundamentally different from a rating. Polls typically result from the tabulation of votes. For example, each ballot in college football's AP poll is the opinion of one writer who should be #1,#2,#3, etc. So a poll is really a composite of many opionions or preferences. In contrast, a computer ranking is obtained from a single "measurement" of how good each team is based on the defining criteria.

Team A beat Team B, so why do your ratings still have B ahead of A?

This situation is usually called and "upset." It is generally impossible order the teams to eliminate all inconsistencies in actual game outcomes. Teams are not evaluated on the basis of one game, in which there is potential for high deviation from typical performance levels. Instead, a team's rating is based on its "average" level of performance over the entire season.

Your ratings stink! Why isn't my team ranked higher?

The implementation of a computer rating algorithm is completely objective. So if the computer gives your team a bad (or good) rating, it shouldn't be taken personally. You have the right to disagree with the computer, but more than likely this is evidence of your own subjectivity. I do not meddle with the algorithm to "fix" the ratings. The model defines certain criteria that determine a team's rating, and the results are published on this web site without any human intervention.

What about predictions?

For many sports, I post predictions of upcoming games and moniter their success. In most cases, I would trust a computer's prediction over a human's. However, while this is often the most popular and entertaining application of computer ratings, it is not my primary purpose.

Predictions are obtained by extrapolating the analyisis of past performance to estimate future performance. Usually, the past is a resasonable indicator of what to expect in the future. However sporting events are to a great extent random, so upsets will occur. Furthermore, computer ratings are ignorant of many important factors such as injury, weather, motivation, and other intangibles. With this in mind, it is not wise to hold unrealistic expectations of the predictions.

Do you encourage sports wagering using your numbers?

Absolutely not! Please read the disclaimer.

Why do you post three different rating systems?

While the algorithms that produce computer ratings are objective, the choice of the model itself is not. Multiple systems provide the opportunity to compare alternative interprettations of the same data. Although there is general agreement, computer ratings are also quite diverse. The Massey Ratings are my creation, while the Markov and Sauceda models were developed with help from friends of mine.

How did you get involved with the BCS?

I started working on college football ratings as an honors project in mathematics while at Bluefield College in 1995. Continuing this interest as a hobby, I developed a web page and helped pioneer the organization of college football rankings via my comparison. The BCS, which started in 1997, realized the need to expand its sample of computer ratings from three to seven. My web site became a central resource point as the BCS officials searched for quality, respected, and well-established computer ratings. I received a phone call from SEC commisioner Roy Kramer in the spring of 1999 to discuss the prospect of adding my ratings to the BCS formula. Mine were chosen because of their demonstrated accuracy and conformance to the consensus, and my personal expertise in the field.