Roundup 1/22/11

How good has Aaron Rodgers been in his 3 playoff starts? Before we get too excited about Rodgers' place among the game's greats, keep in mind just how much friendlier the league has become to passers over the years. Even over a one year span, 2010 was measurably easier to throw in than 2009.

Are playoff byes worthless, or even bad? (Helmet-knock: Tango) Tango nails it. We're looking at too small a sample to tell anything, and what we do see is not far off from what we'd expect. Keep in mind that in the regular season since 1994 (a fairly big sample) teams coming off byes win 53% of the time. Also, keep in mind that a bye is essentially an automatic playoff win! It nearly doubles a team's chances of making it to the Super Bowl over any other team without a bye.

Are NFL coaches finally catching on to advanced stats? Yes, they are. I know first hand that multiple teams use advanced analysis. Kovash, who is now with the Cowboys, is a smart guy and Jason Garrett would do well to listen to him.

Football Outsiders' Starter-Games-Lost stat for 2010.

Phil Birnbaum says that box-score formula player metrics are too flawed to be useful. I'm sure Dave Berri will have a response. Individual stats for football are 100 times more flawed, but I do it anyway!

You can add one more game to this list.

What if we observed Tom Brady's career in reverse? Choker. (Awesome essay.)

The Jets have been letting to much WP slip through their fingers this season. One of the keys against Pittsburgh tomorrow night might be going for it on 4th down more often. (This is the kind of article I love most. I get to have fun doing the number-crunching, and someone else writes it up.)

Visualizing the Jets special teams. I just love a good graph. By the way, Brad Smith should be active tomorrow after missing last week's NE game.

Who do today's young QBs most resemble?

Visualizing team performance trends. This is almost exactly what I do to fine-tune the prediction model early in the season, except I do it with each team stat.

Why does sport performance appear to be so streaky?

How many playoff games should a QB have won, given his individual passing performance? The Rivers Index-Playoff Edition tells us.

I really appreciate things like this. Andrew Das takes a look back at the errant predictions of the NYT's writers and commenters got wrong at the Fifth Down. Going back and evaluating previous predictions is a very healthy thing. It reminds us just how wrong we usually are when trying to predict the future. One of my favorite articles of the year is Gregg Easterbrook's bad predictions column. He deserves a Pulitzer for it.

First down means a lot according to Cade Massey, an economist of note and co-author of the Massey-Thaler NFL Draft study. (h/k - Smart Football) Massey also discovered that an offense needs at least 4 yards on 1st down to be successful. My reaction is no kidding. We've known this since the earliest days of football-metrics. Just read Hidden Game of Football from the mid-1980s. Besides, one reason 1st downs are so important to team success is that there are so many more of them than any other down. Think about it.

Some academics who do sports research ignore very sound previous research by those outside the university. One of the very first steps in research is to do a thorough literature review of the topic. If it's not in JSTOR, that doesn't mean it hasn't been done or that it's not reliable.

That said, there is something to be said about reinventing the wheel in scientific research.  Replication verifies previous results and is critical to scientific progress. Several people pointed me to this article about the Decline Effect. Effects discovered in original research tend to decline as other researchers attempt to duplicate the results. The suspected culprit in this caper is human bias toward successfully verifying our own theories. (This is one reason I freely share play-by-play data.)

Plus, there is a mathematical reason why much of what is accepted as fact just might be wrong. According to John Ioannidis, the majority of published research is probably false. Say there are 1000 possible hypotheses to be tested about a subject. There are many more possible false hypotheses than true ones. (For example, on the subject of what causes heart disease, we can guess it's due to vitamin B deficiency, vitamin C deficiency, cholesterol, an array of environmental effects, and so on...., but only a few of the causes tested are actually true.) Say of the 1000 hypothesis tested, 800 are false and 200 are true. Based on the commonly accepted threshold of statistical significance and Bayes Rule, of the 200 true hypotheses, researchers will get 120 significant results. Of the 800 false hypothesis, researchers will get 40 significant results. So of the total 160 significant results only 120 (75%) are true. Given the very real bias against publishing findings that fail to show significance despite being valid research, it's plausible that most of what gets published in peer-reviewed journals is wrong.

Additionally, the entire concept of statistical significance has been under debate for years. My own take is that all research should be taken with a grain of salt. You'll notice I almost always preface my findings with mealy-mouthed 'softeners' like, "This result suggests that..." Before something is accepted as fact, there should be a mountain of evidence for it. But in terms of making decisions on the football field, things can be far more clear cut. It's true there may be an error band around the resulting values of WP or EPA or whatever, but those are the best estimates we have. And we've got to make a decision one way or the other. Pass or run. Go for it or punt. You get the idea. We're not curing cancer here.

And those who occasionally wager on an NFL game will enjoy this 60 Minutes story on betting legend Billy Walters.

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1 Responses to “Roundup 1/22/11”

  1. Ian Simcox says:

    That's a great video. Loved his point about betting more the more you think the bookie is wrong. I never thought about it like that before, but it makes sense, just the same as you'd buy more stock the more underpriced you think it is.

    Well.... time to go lose more money :)

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