With 12 games under our statistical belts, I thought it's a good time to check in on a new concept I unveiled in the off-season. Tackle Factor (TF) is a stat that tries to make better sense of the NFL's tackle numbers. Let's see how this season's top defenders are faring in TF. If you're already familiar with TF, skip down to the tables of top players.
You might think that more tackles is always better for a player, but it's not that simple. Some positions simply get more tackles by their nature, especially linebackers. Plus, some defenses are worse than others, allowing more 1st downs, more plays, and by definition, more tackles to be had.
TF begins to untangle tackle stats by looking at a defender's share of his team's tackles. This accounts for the number of plays (and tackles) allowed by each defense. It then compares each defender's share of team tackles to the expected share of tackles by a player at his position. TF excludes special teams tackles and offensive tackles on turnovers. A TF of 1.0 would theoretically be average, but only if a defender has played in all of his team's snaps. TF is also adjusted for games played, so a player who has missed a few games due to injury isn't penalized.
One other additional benefit of TF, one that I did not even think of when I first implemented it, is that it normalizes for hometown scorer tendencies. Tackles are technically not considered official stats by the NFL. Each team has its own scorer for home games, who decides whether each tackle is recorded as a solo or who, if anyone, gets credited with an assist. So tackle stats are not purely objective. (This is not to suggest the scorers are biased in any way. Rather, the point is there are 32 slightly different standards for what qualifies as an assist.) Because TF is based on a share of team tackles, scorer tendencies are mitigated.
Checking in on Tackle Factor
Jamaal Charles
I need a new post to drop the semi-nude picture of Tom Brady down off the front page, so I thought I'd chime in on the Jamaal Charles re-signing. The Chiefs inked (if you're a sportswriter you're supposed to say 'inked' ...or sometimes 'locked-up' when it's a re-signing) the RB to a 5-year deal with $13 million guaranteed. Is Charles really a top back worth top money?
Yes, he is. (You're supposed to make readers wait to the end of the article for a wishy-washy non-answer, but I'll cut to the chase.) Charles' numbers are great, and the seem to be getting better each year. Currently in his 3rd year, Charles is averaging 5.8 YPC for his career and 6.0 YPC for 2010. (4.3 YPC is average for RBs.) How good is 5.8 YPC? It's better than any 3-year span or any single year for LaDanian Tominson, Marshall Faulk, or even Erik Dickerson (not to be confused with the Bruce Dickinson, who could easily run for 5.8 YPC if he wanted.)
The Weekly League: Notes and Ideas for Week Fourteen
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.
New York Giants at Minnesota | Sunday, December 12 | 1:00pm ET
Four Factors
Notes
• True Fact: Americans are holding their collective breaths, waiting to find out whether Brett Favre or Tarvaris Jackson will start this afternoon's game.
• Other True Fact: Americans should probably stop holding their breaths, lest they suffer some sort of oxygen deprivation-related brain damage.
• As for which is the better option -- Favre or Jackson -- our host Brian Burke suggests the latter might have an edge on the former, although it's not entirely clear.
• A notable thing is that, despite what must be considered a disappointing season on the face of it, the Vikings are actually ranked tenth per GWP, with a 0.59 mark.
• They're also the NFL's fifth-unluckiest team (as you can see below in the GWP Luck table).
Interesting Posts over at the Community Site
This past week the Community site received some interesting contributions.
Jim Glass looks at whether the close-game/clutch-play narrative is backwards.
Ian Simcox measures just how big an effect strength of schedule can have on a team's regular season W-L record.
Karl Berthold looks at the effect Mike Martz has had on his teams over his career, both as head coach and as offensive coordinator.
Bruce D. introduces a novel type of team-rating system. It's based on points scored and allowed, adjusted for strength of schedule and for lucky plays. Bruce has also been keeping us up to date on which teams have benefited the most by lucky and unlucky plays. That is, high-impact plays that tend to be non-repeatable, such as kick returns for touchdowns blocked field goals, fumble returns, etc.
Many thanks to Ed A. for editing the Community site.
Fisher's Blunder
Trailing by 6 to the Colts with under 5 minutes to play, the Titans faced a 4th and 1 from their own 34-yard line. Coach Jeff Fisher chose to punt, and the Titans went on to give up a field goal on the Colts' subsequent drive and lose the game. How much did that decision cost the Titans?
A successful conversion would give the Titans a 1st and 10 on at least their 35, giving them a 0.23 WP. A failed attempt drops their chances to a 0.06 WP. Conversion attempts with 1 yard to go are successful 74% of the time, making the total WP for going for it:
Weekly Game Probabilities
Weekly game probabilities are available now at the nytimes.com Fifth Down. This week I take a closer look at Sunday Giants-Vikings match-up.
What Proportion of Football is _______?
How much of the game is passing, running, kicking, or punting? How much of football are interceptions? Fumbles? How much do penalties impact the outcomes of games? One way to answer that is to simply add up how many of those kinds of plays occurred and divide by the total number of plays. But that’s not going to tell us much, because each kind of play tends to have a different magnitude in terms of its effect on the outcome of games.
When we talk about “how much of football is” something, we need a good definition of what football is. The essence of football, like any other sport, is about competing and winning. So when we ask how much of football is passing, we want to know the impact of passing plays on the outcomes of NFL games compared to other types of plays.
Win Probability can provide the answers. In each game, the WP of each team starts at 0.5, but must end at 1 or 0, for a net total of 0.5 WPA. But between the first kickoff and the final whistle, the WP can swing up and down, traveling far more than the net 0.5. To calculate the total movement, we just need to add up the absolute value (7th grade flashback) of each play’s Win Probability Added (WPA).
EPA by Pass Depth and Down
In response to the recent post about the comparative success of short and deep passes a few readers asked for a break out of the results by down. Some suggested the advantage of deep passes might only due to unsuccessful check downs on 3rd down, which is certainly plausible. The numbers are going to be slightly different here because I neglected to exclude red zone attempts in the original post. (Please read the original post for definitions and caveats.)
Here is the break out by down. It appears that the advantage exists on all downs, and the advantage is not significantly greater for 3rd downs than for 1st or 2nd downs. But that doesn't necessarily rule out the check-down effect, as they are a common tactic on all downs.