<commit_before># goodrating

> An attempt to rate college football teams (good).

## Consumer Warning

I enjoy college football and I enjoy lists. This rating system is, more than anything else, for my own enjoyment. Much of the "information" presented here is anecodtal, at best. 
That's intentional. Football is chaos. Football is simulated warfare. Any attempt to seriously quantify if should be met with tremendous skepticism.

## Summary

*goodrating* is an attempt to rate college football teams using the fewest number of statistics as possible. Like people, statistics have biases. 
In using a small number of factors, I hope to mitigate the effect of their bias.

> But David, how can a number be biased?

It's all about context. E.g. a team can have a 0.950 winning percentage, but that number doesn't account for the teams they played. A high winning percentge could be an indicator of 
greatness, but it can also be an indicator of their opponents weakness.

> Ok, what are you going to so about it then?

...

Just like any statistics-driven system, the rating (theoretically) will improve as the sample size increases.

## Methodology (wip)

1. Winning percentage (45%)
2. Adjusted Offense rating (15%)
3. Adjusted Defense rating (20%)
4. Adjusted Player rating (20%)

Finally, take the sum of above and adjust using the team's performance relative to expectation, i.e. (+/-) against the spread.

## Assumptions

Head-to-head doesn't matter in this rating. This is an attempt to quantify the "goodness" of team, not a predictor of game outcomes. Therefore, it is possible that a team will be rated above a team that beat them. Sorry.<commit_msg>Adding some more summary items<commit_after># goodrating

> An attempt to rate college football teams (good).

## Consumer Warning

I enjoy college football and I enjoy lists. This rating system is, more than anything else, for my own enjoyment. Much of the "information" presented here is anecodtal, at best. That's intentional. Football is simulated warfare + shoulder pads. Any attempt to *seriously* quantify it should be met with tremendous skepticism.

## Summary

*goodrating* is an attempt to rate college football teams using the fewest number of statistics as possible. Like people, statistics have biases. In limiting the number of statistical factors, I hope to control the effect of their bias.

> But... how can a number be biased?

It's all about context. E.g. a team can have a 0.950 winning percentage, but that number doesn't account for the quality of teams they played in achieving that number. A high winning percentge could be an indicator of greatness, but it could also be an indicator of their opponents' collective weakness.

> Ok, what are you going to so about it then?

Glad you asked!

Here are the four main pillars of goodrating:

1. Winning percentage
2. Offense rating
3. Defense rating
4. Player rating

#### Winning percentage

A lot of rating systems will adjust a team's winning percentage based on their "strength of schedule (SOS)," i.e. *how good were the teams they played?* I don't like using SOS, though, because although it rewards successful teams that play difficult schedules, it also tends to reward bad teams that play difficult schedules. Instead, I plan on adjusting based on the team's cumulative performance versus expectation, aka "the spread." If a team wins a lot of games, but not as convincngly as they should, they are adjusted down. If a team has an average record, but a lot of close losses, they are adjusted up, and so on.

#### Offense rating

For now, this is purely a team's average yards per play. There is a wide variety of offensive styles in the NCAA, but all of them have the same goal: gain as many yards as they can and score points.

#### Defense rating

Much like the `Offense rating`, this is the team's average yards allowed per play.

#### Player rating

This is the team's combined recruiting scores during the previous four years, as provided by [247 Sports' Composite Rankings](http://247sports.com/Season/2017-Football/CompositeTeamRankings). Although the scores are entirely based on projections, there is a strong correlation between recuiting well and winning football games. See the recent SBNation article [The 2016 Blue-Chip Ratio: How close is your CFB team to having title-level talent?](http://www.sbnation.com/college-football-recruiting/2016/8/18/12530108/ncaa-football-best-recruiters-2016) for more explanation on that. (Spolier: Alabama gets good players)

## Methodology (wip)

## Assumptions

Head-to-head doesn't matter in this rating. This is an attempt to quantify the "goodness" of team, not a predictor of game outcomes. Therefore, it is possible that a team will be rated above a team that beat them. Sorry.

## Another Warning

Just like any statistics-driven system, the rating will (theoretically) improve as the sample size increases. This means that there is a strong posibility that the ratings will be less-than-accurate during the first few weeks. Please be patient (also, see the note about this being for fun at the top).

## Finally

If you have any questions/comments please feel free to open an Issue or email me at davenich at gmail.
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