Old Mother Hubbard 2012: Detroit Lions Team Needs

Old Mother Hubbard 
               Went to the cupboard,
               To give the poor dog a bone:
             When she came there,
              The cupboard was full of talented young football players,
             which was pretty awesome.

Yes, it’s time once again for The Lions in Winter’s annual roster analysis/team needs thing, Old Mother Hubbard. Last season’s edition added Pro Football Focus grades and statistics, plotting them on radar charts for easy understanding. This was well received.

I highly value PFF data, they do fantastic work that nobody else is doing. As I said, if I had the time to grade out every Lion on every snap of every game for these breakdowns I would—but PFF already did, so I stand on their shoulders.

However, I don’t think PFF data is the only valuable way of describing a player or season. I’m a big fan of the work Brian Burke does at Advanced NFL Stats, and I’m going to be including (at least) his  Win Probability Added stat, WPA. Burke explains WPA here:

Stats are tools, and each tool has its own purpose. WPA is what I call a narrative stat. Its purpose is not to be predictive of future play or to measure the true ability of a player or team. It simply measures the impact of each play toward winning and losing.

WPA has a number of applications. For starters, we can tell which plays were truly critical in each game. From a fan’s perspective, we can call a play the ‘play of the week’ or the ‘play of the year.’ And although we still can't separate an individual player's performance from that of his teammates', we add up the total WPA for plays in which individual players took part. This can help us see who really made the difference when it matters most. It can help tell us who is, or at least appears to be, “clutch.” It can also help inform us who really deserves the player of the week award, the selection to the Pro Bowl, or even induction into the Hall of Fame.

There are two main weaknesses with PFF grades—or perhaps I should say, two main characteristics you need to keep in mind when evaluating players with them. First is a strong pull towards the mean. Since an unremarkable play—a typically decent effort—gets graded as a zero, the fewer snaps a player has the more “average” he tends to look in his grades. PFF acknowledges this with a default minimum of 25% of available snaps, but it limits their utility in describing role players and backups.

The other factor is what I call a “consistency bias.” PFF’s grading system loves players who make consistently positive down-to-down impact, and tends to pooh-pooh “home run hitters” who make a couple big plays per outing. WPA works in the opposite way: it loves players that makes plays that win games. Between the PFF data and WPA, we should get a very complete picture of how strong the Lions’ roster is, relative to itself and relative to the rest of the NFL.

Number crunching is happening now; OMH's start going up by the end of the week.

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The Lions in Winter Blue Flame Awards, 2011 season

As we head into the first weekend of the Lions’ offseason, it’s time for the second annual Blue Flame Awards. The inaugural Blue Flame Awards were a success, but I think they can be a lot bigger. I’m going to announce these one at a time, an hour or two apart, updating the post and Tweeting as I go. If you’re not @lionsinwinter on Twitter, now would be a great time to start.

The envelope, please . . .

Chris Spielman Heart of a Lion Award: Dominic Raiola, C

Given to the Lion who most profoundly exudes fire, toughness, and determination to win, Raiola could easily win this every single year. The moment that clinched it was Raiola’s statement in the wake of the Thanksgiving disaster: “Grow the f*** up.” And you know what? They did.

Bryant Westbrook Realized Potential Award: Titus Young, WR

When the Lions drafted Titus Young with the 12th pick in the second round, fans everywhere were in shock. Who? A wide receiver? From Boise State? It seemed senseless. With several pressing defensive needs, and the first round pick already spent on a "luxury," a receiver to groom behind Nate Burleson was a total head-scratcher. When he missed most of training camp and preseason with a nagging injury, fans assumed his chance to be productive this season was lost.

But the Lions knew exactly how they wanted to use Young, and Young threw himself into being a Lion. He immediately earned Matthew Stafford's trust, and hauled in 48 catches for 607 yards and 6 touchdowns. Best of all, it's clear he's just getting started.

Tom Moore Coach of the Year Award: Shawn Jefferson, WR Coach

It's a little too easy to give this award to offensive coordinator Scott Linehan for the second year in a row—though he deserves it just as much, if not more, than last season. But the job Jefferson did with the wideouts this season was phenomenal. Besides helping Calvin Johnson reach record-breaking new heights, he helped Titus Young achieve his Blue Flame-winning potential and Nate Burleson drop that #ToeDragSwag.

For a wonderful in-depth look at the job Jefferson is doing—and why the Lions will be lucky to keep him around—see Anwar Richardson’s feature on Jefferson on MLive.

Game of the Year: Week 5, Lions vs. Bears (Monday Night Football)

The Christmas Eve demolition of the Chargers that clinched the playoffs was special, but Monday Night Football was the Game of the Year and it isn’t even close. Besides being an anticipated-for-months revenge match for 2010’s season opener, besides it being a showcase game for the Lions, Lions fans, and the city of Detroit as a whole, and besides every second of the pre-game, in-game, and post-game festivities simultaneously oozing Motown and awesome, this is the game where the blue fire of Lions fandom roared so loud the Bears couldn’t play football in its presence. It was the greatest sporting atmosphere I’ve ever been a part of.

Nine false starts later, the Lions won the biggest Lions regular season game in decades—and Lions fans—you, me—were awarded a game ball by Coach Schwartz.

Mel Gray Three Phases of the Game Award: Jason Hanson, PK

At age 41, Jason Hanson entered training camp with question marks surrounding his injury—and, for the first time in nearly two decades, his job. In a legitimate kicking competition for perhaps the first time in his career, he shut out those suggesting it might be time to hang ‘em up and made 24 of 29 field goals (including blocks) and all 54 extra point tries. He proved he still has the leg, too, drilling 5 of 7 attempts from 50+ yards.

Honorable Mention: John Wendling

Mike Cofer Tecmo Super Bowl Beast Mode Award: Stephen Tulloch, MLB

After signing a one-year deal in the offseason, Stephen Tulloch stepped into the heart of the Lions defense and dominated. Besides leading the team in tackles, he led all Lions linebackers with sacks (3) and interceptions (2). He was Pro Football Focus’s seventh-highest-graded inside linebacker, at a whopping +20.8. He earned their second-best coverage grade, too: +11.2. His run-stuffing grade was the ninth-best in the NFL at +12.6.

Let’s please hope he stays.

Barry Sanders You Can Only Hope to Contain Him Award: Matthew Stafford, Quarterback

Matthew Stafford had the greatest statistical season of any Lions quarterback ever. 63.5% competions, 5,308 yards, 41 touchdowns—and only 16 INTs, almost all of which were thrown while Stafford was throwing with a glove over a broken finger. Megatron gets honorable mention here, but Stafford was asked to carry this team to the playoffs at age 23 and he did. Absolutely incredible, history-making performance.

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The Watchtower Review

The point of the Watchtower posts was to forecast the performance of the Detroit Lions against their weekly opponents. From the start, I’ve used historical performance data of the Lions coordinators against their opposition’s. By controlling for the relative talent of the players, I tried to isolate systemic advantages at the X-and-O level. I then tried to apply those advantages to the teams’ current skill levels, and project a result.

The Watchtower is one of my most popular features; people really dig it. It’s fun to write, especially researching every coordinator’s coaching tree, and picking the picture. However, after three years, I’m no longer satisfied with The Watchtower an alternative “game preview,” or as a predictive tool.

Watchtower Problem #1: heavy reliance on per-game team averages.

When I use average yards per attempt and average yards per carry, it gives a pretty accurate picture of those players’ performance levels. Whether a quarterback has 25 or 50 attempts, or 200 or 400 yards, dividing one by the other tells you at what rate the quarterback is generating offense, every time. But dividing “points scored in a season” by “games in a season” doesn’t work. A “game” is not a fixed unit of measure; there’s a wide variance in the number of possessions and plays in a “game.”

In every pass attempt, there is exactly one pass attempt, one bite at the apple. In every game, there’s a wide variance in possessions, time of possession, and plays. Example: when the Lions hosted the Vikings, they scored 34 points. When they hosted the Chargers, they scored 38. On the face of it (and in terms of the “points per game” numbers I’ve been using), the offense was very effective in both games.

However, in that Minnesota game the offense netted just 280 yards and 20 points from ten possessions. Against San Diego, the offense netted 440 yards and 31 points from eight possessions. This is a massive difference in effectiveness and it’s almost completely uncaptured by the current Watchtower methodology.

Dropping the "per game" team averages would allow me "tell the story" more effectively; I thought there was a very high chance that the first Packers game would be shockingly conservative—and the rematch a track meet. But using season average against season average, there’s no way to project either of those outcomes.

Finally, that "track meet" effect means something: there is a tendency for points to follow points, and that speaks to a very real offense/defense interaction effect that isn’t accounted for, either in traditional analysis or in The Watchtower. When one offense puts the pedal to the metal, the other one follows—and both defenses, apparently, just let it happen. Why? What’s going on here?

Watchtower Problem #2: No real accounting for turnovers or special teams.

This is one that’s bothered several readers from the get-go. The Watchtower is a study of offense-defense interaction: what happens when offensive scheme A meets defensive scheme B. But special teams and turnovers play a huge role in the final score.

In the Thanksgiving Day game, when the Lions and Packers played to a stalemate for most of the first half, a tipped pass fell into enemy hands and the Packers’ offense got to start deep in the heart of Lions territory. That was the game-changing play both teams desperately needed. Despite incredible down-to-down play by the defense, the offense was really the unit that put the Packers in position to score.

On special teams, the Lions’ coverage units struggled mightily throughout the first two thirds of the season, and it regularly hung the defense out to dry. Moreover, the iffy upfield blocking for Stefan Logan (and his own iffy fair catch decisions on kickoffs) failed to make the field shorter for the offense.

Watchtower Problem #3: The Human Element.

I project ranges for points, passing effectiveness, and running effectiveness for each side—then basically use the “Mitigating/Aggravating Factors” and “Conclusions” section to winnow those down to the final score I deem “most likely,” usually via talking-out-loud thought experiment.

There are several layers of my own bias involved here—and even though I work hard to follow where the data leads me, a little bias on top of a little bias on top of a little bias makes a big difference. I can definitely lead the statistical horse to water if I want to—and sometimes I do even when I’m trying not to.

What I’d love to be able to do is project a range of possible outcomes and their probabilities, so when I say “The most likely outcome is . . .” my a hand won’t be moving the data’s mouth.

Thoughts?

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