It Could've Been Worse, Saints and Giants Fans

by James Sinclair

All the talk about the fairness, or lack thereof, of Seattle hosting a first-round game after a 7-9 season, while New York and Tampa Bay went 10-6 and missed the playoffs, made me wonder what would be the most "unfair" scenario possible, in terms of both the records of the home and away teams in a round one matchup, and the record of the best team that doesn't make the playoffs. So here goes. Obviously, highly improbable (but not impossible) assumptions abound.

First of all, it's fairly intuitive that the worst possible record for a division winner (and, by extension, any playoff team) is 3-13, which would happen if and only if all four teams go 3-3 within the division and 0-10 against everyone else. So let's say the Seahawks, Rams, Cardinals, and 49ers have four identically-awful 3-13 seasons. On the last tiebreaker, a complex series of coin tosses, Seattle wins the division.

Completion rates aren't the complete story

by Denis O'Regan

In a follow up to my post about interception rates for quarterbacks corrected for air yards per throw, I've taken a similar look at completion rates.

A completion rate taken in isolation can be a very misleading indicator of a player's real skill level. For example Michael Vick's average completion rate for his last season in Atlanta and his first year in Philadelphia was just 58%. By contrast the 2006 version of David Carr had a success rate of over 68% and tied the record for most consecutive completions in a game. Two rates at polar extremes, but whereas Carr's passes on average only travelled just over 5 yards per attempt, Vick's went nearly twice that distance.

To try to introduce air yards per attempt into the equation I firstly regressed air yards against completion rates for ever primary starting QB since 2006. This produced a fairly smeared out scatterplot and although increased pass length per attempt reduced the completion rate, correlation was very low at 0.09.

Probability Isoclines in the WP Model

by Andrew Foland

I have been asking myself an amusing question about the WP graphs the last few weeks, and it will take a couple of little pieces of work to set up to answer it. This writeup is one of these pieces.

Given a probability to win at time T0, how must the score differential change as time passes to a later time T to maintain the same probability of winning? Note that the score differential to maintain a constant winning percentage goes down as the game progresses—a ten point lead early in the game is often less likely to win than a one point lead late in the game.

I decided to set a fixed situation, namely 1st and 10 from own 20—and see how the score differential evolved at constant win probability. I did this using the win probability calculator and lots of trial and error. I evaluated this at 6 difference values of WP: 55, 60, 65, 70, 75, and 80. I evaluated the WP at 6 different time points: five minutes into the game, at the end of the first quarter, at half, at the end of the third quarter, with 7 minutes in the 4th, and with 3:30 in the 4th. At around 3:30, point differential starts behaving very idiosyncratically. It’s also worth noting that Brian probably has little data for some point differentials early in the game, so there will be some systematic dependence on the form of his functional extrapolations into that region.

"Clutch” playoff teams

by Steven Buzzard

It seems the same questions get brought up every year during the playoffs. Which quarterback do you trust with your playoff lives on the line? What team is full of the most clutch players? Coach “X” just can’t win in the playoffs, normally Norv Turner but not this year. I don’t know of any study that has been able to prove such an existence of a clutch player or team and I am not going to try to do so here. What I wanted to do was to simply give a quantitative value to how much each team has actually over/under performed in the last decade.

Total team luck points and no luck power through week 17

by Bruce D

Team luck points = (bad luck points)-(good luck points), so negative numbers are the luckiest
For a more in-depth explanation of what "luck" points are, go to a previous post here.
Luck is tracked to better analyze a team's true ability and to help predict results of upcoming games where some may not know what portion of a team's record and points performance was due to just luck.

Luck points are valued as follows:

Points for(+) the unlucky team, are the same amount of points against(-) the lucky team.

punts blocked=3
interceptions=2.5
fumbles lost=2.5
field goal miss/block=2.5
punt returns for a TD=4.5
ko returns for a TD=4.5

Quarterback Interceptions

by Denis O'Regan

This is an attempt to attach a fairer number to a quarterback's interception rate. Raw interception numbers are naturally improved by taking into account the number of passing attempts a player makes in throwing those picks. However, this still does not differentiate between players who are being asked to throw deeper more often,thus increasing the risk of being picked off. I therefore decided to use play by play data to measure the distance each quarterback's throws travel in the air and divided this by his number of interceptions thrown.I'll call the resulting number airyards per pick. I did this no only for completions, but also for non completed passes.

I've initially just looked at the previous five seasons and I've analysed the quarteback who threw the most passes for each team during each season.As a comparison I've ranked each player for airyards per pick and also for the conventional interception per pass attempt percentage.

Kickoff or Receive?

by Ed Anthony

A little known fact is that the team losing the initial cointoss has the option of electing to receive the ball at the beginning of the second half to electing which side to defend. THis means that if the home team loses the cointoss and begin the game with a kickoff they can then elect to kickoff at the start of the second half.

Conventional wisdom is that there is an advantage to have first possession in a half. For this reason teams always elect to receive the ball at least once during the game. But the rules are clear that the game need not develop this way.

Over the years there has been much discussion whether a team should has an advantage receiving in the first half. An argument can be made that receiving to open the second half gives a team the advantage of knowing whether they are in the lead and can play accordingly. arguments have also been made that first possession puts pressure on the kicking team to "catch up."