San Diego's strange season continues, but they lose their #1 spots on offense and defense. NE now owns the offensive honors while Pittsburgh owns the defensive title.
The team rankings below are in terms of generic win probability. The GWP is the probability a team would beat the league average team at a neutral site. Each team's opponent's average GWP is also listed, which can be considered to-date strength of schedule, and all ratings include adjustments for opponent strength.
Offensive rank (ORANK) is offensive generic win probability, which is based on each team's offensive efficiency stats only. In other words, it's the team's GWP assuming it had a league-average defense. DRANK is is a team's generic win probability rank assuming it had a league-average offense.
Team Efficiency Rankings - Week 14
Advanced NFL Stats Coach of the Week
This week's COW is none other than Raiders coach Tom Cable. The Raiders beat the heavily favored Chargers on the road yesterday, mostly by virtue of two unconventional but statistically favorable decisions. Oakland built a 14-0 lead by the end of the 1st quarter, and both scores came courtesy of 4th down conversion attempts.
On 4th and 1 from the SD 9, Jason Campbell ran a play fake naked bootleg in for a TD. Later, on 4th and 1 from the SD 21, Cable made no hesitation. As soon as the measurement came in, he just gestured 'go' at Campbell. No timeout. No challenge. No try-to-sucker-the-defense-into-off-sides-then-call-timeout-and-kick nonsense. Just a QB plunge for 3 yards. The Raiders went on to score their second TD of the day, putting SD into a hole from which they never could dig out.
The Weekly League: Notes and Ideas for Week Thirteen
This week's edition of The Weekly League features:
1. Rapture-inducing previews of the Cleveland-Miami, Dallas-Indianapolis, Pittsburgh-Baltimore, and New York Jet-New England games.
2. A quiz!
and
3. Another quiz, right after the first one!
The Four Factors you see for each game represent each team's raw performance thus far in four important categories (pass and rush efficiency, pass and rush efficiency against) relative to league average (where 100 is league average and anything above is good).
Along with the Four Factors, you'll see two other numbers: Generic Win Probability (GWP) and Game Probability (PROB). The GWP is the probability a team would beat the league average team at a neutral site. It can be found for all teams here. The PROB is each respective team's chance of winning this particular contest. Your host, Brian Burke, provides PROBs to the New York Times each week, and those numbers (along with methodology) can be found here.
Finally, a glossary of all unfamiliar terms can be found here.
Cleveland at Miami | Sunday, December 05 | 1:00pm ET
Four Factors
Notes
• This game features two of the league's most interesting cases: Peyton Hillis and Cameron Wake.
• Wake, who began his professional career in Canada, is either second or tied for first in sacks, depending on whose numbers you use.
• He's also first in QB Hits, with 21.
• As for Hillis, he's third among all running backs in WPA (0.96) and and seventh in EPA/P (0.09).
• This, from a player who was traded for Brady Quinn this past offseason.
Washington Post: Returner Brandon Banks' Impact
Today's post at the Washington Post's Redskins Insider looks at the Redskins' recent loss to the Vikings.
-Why kick two field goals down by 10 in the 4th quarter?
-How big has return specialist Brandon Banks' impact been?
-LaRon Landry's absence really hurts the Redskins' D.
-The 'Skins are now 5-6. Do they still have a shot at the playoffs?
-The upcoming Giants game is a statistical uphill battle.
Weekly Game Probabilities
Weekly game probabilities are available now at the nytimes.com Fifth Down. This week I take a closer look at Monday night's Jets-Patriots match-up.
Roundup 12/4/10
Quantifying the importance of the Jets-Patriots game. I suppose many of the same insights could apply to the Steelers-Ravens game.
Is John Elway really the comeback king?
The Patriots are a second-half team this year. Last year they were a first-half team. I wonder if it's just a 'splits happen' phenomenon or something more?
Peyton Hillis and one of the most lopsided trades in recent memory.
Weekly playoff projections from NFL-Forcast.com.
Which is the better team, the one that's 7-4 or the one that's 4-7? Or is it a team that's 2-9?
Deep vs. Short Passes
Over the past couple years, we've learned that passing well is more important than running well in terms of winning games. We've learned that passing has become more and more lucrative over the years. And we've learned that offenses should pass more often, particularly outside the red zone and on 1st down. But 'passing' is a large category, encompassing everything from a screen pass 2 yards behind the line of scrimmage to a 50 yard bomb.
Beginning in 2006, the NFL classified every pass attempt as either 'short' or 'deep,' where deep means anything past 15 yards. About 19% of pass attempts are classified as deep. Unfortunately, that's all we get, so we can't tell a screen from a 14-yard down-field pass attempt. Still, it allows us to begin to pull apart different types of passes and examine them in one more layer of detail.
In normal football situations, in which the clock is not yet a factor and the score is relatively close, pass plays, including sacks, yield an average of +0.08 Expected Points Added (EPA), while run plays yield an average of +0.01 EPA. Which type of pass is more responsible for that advantage, risky deep passes or safer short passes?
Motivation
Much of statistical sports analysis is rooted in economics. Many of the statistical tools used in sports research are the same tools used in economic research, such as multivariate regression, utility theory, and game theory. Professional sports offer researchers a somewhat controlled labratory to examine more general economic principals.
But there is an unarticulated question at the heart of sports research: What is the point? What’s the bottom line? What are the athletes we study trying to accomplish? Making sense of any activity requires an understanding of the ultimate goal. To many economists, who have a financial orientation, the bottom line is quite literally the bottom line. To fans like me, the bottom line is winning, not revenue or profit. But economists often see professional sports in terms of financial gains and losses. I think researchers like me, who focus on wins, and professional economists, who focus on profit, are both missing a very large part of the picture.
If there is one thing that economics teaches us, it’s that incentives matter. The real question becomes, what are the incentives? For most of the history of economics, money was treated as the only important motivator. After all, money obviously does motivate nearly all people, plus it’s easy to measure. But there is far more to motivation and incentives than money, and economists would be the first to admit that. But just like how we admit measuring individual player performance is flawed and incomplete, it's done anyway simply because it can be measured.