Rookie Quarterbacks Need To Chunk

Jon Gruden, Cam NewtonLast year, in a highly anticipated episode of Jon Gruden’s Quarterback Camp, the former NFL coach warned highly touted rookie prospect Cam Newton about one of the major adjustments facing him when he gets to the NFL. “You know, some of this verbiage in the NFL, I don’t know how it was at Auburn, but it’s — it’s long. You’ve got the shifts, the plays, the protections, the snap count, the alert, the check-with-me’s,” Gruden said. “I mean, flip right, double-X, Jet, 36 counter, naked waggle, X-7, X-quarter.”

He went on to ask the Auburn quarterback if he’d ever heard a play call like that in college, to which Newton responded, “Our method is ‘simplistic equals fast.’ It’s so simple as far as, you look to the sideline, you see 36 on the board. And that’s a play. And we’re off.” Gruden did not seem impressed, “Let me make this point, though,” the Super Bowl winning coach continued. “The number one challenge you’re gonna have right away is the verbiage. And just getting comfortable with what we’re calling formations, what we’re calling routes. The alerts. The language. Speaking the language. You’re gonna move to France, and you’re gonna have to speak French, pretty quick.”

What’s difficult about this learning process is that it’s not just learning what the terms mean but then translating those terms into a complicated series of motor skills by each player. The “36 counter” portion of Gruden’s gruesome play call takes years of practice by itself, let alone the rest of the play modifiers.
In the cognitive science world, breaking down a complicated motor task into manageable pieces is known as “chunking.” Think of your favorite band in concert. They seem to fly through 15-20 songs without mistakes or stops to look at sheet music. However, what you don’t see is the hours of practice breaking down new songs into segments, fixing parts that don’t work, memorizing each verse and each chord until the entire song is fixed in their memory. "You can think about a chunk as a rhythm," said Nicholas Wymbs, a postdoctoral researcher at UC Santa Barbara's Department of Psychological and Brain Sciences. "On one level, the brain is going to try to divide up, or parse, long sequences of movement," he said. "This parsing process functions to group or cluster movements in the most efficient way possible."

Wymbs is the lead author of a new study recently published in the journal Neuron. While at first the brain needs to simplify the task sequence by breaking into parts, eventually a different cognitive process searches for the most efficient way to process the request by stringing the sub-tasks together. "The motor system in the brain wants to output movement in the most computationally, low-cost way as possible," Wymbs said. "With this integrative process, it's going to try to bind as many individual motor movements into a fluid, uniform movement as it possibly can."

In their experiment, they asked volunteers to lie in an MRI scanner while performing a sequence of motor tasks. On a screen above them, each person would see an image of a long sequence that they had to type out on a keypad in front of them, much like playing notes on a piano. After many trials of the sequence, they would begin to learn and adapt, which improved their performance.

"After practicing a sequence for 200 trials, they would get pretty good at it," Wymbs said. "After awhile, the note patterns become familiar. At the start of the training, it would take someone about four and a half seconds to complete each sequence of 12 button presses. By the end of the experiment, the average participant could produce the same sequence in under three seconds."

With the MRI data showing the active parts of the brain during this learning process, the researchers were able to observe this dual process of parsing and concatenation. During parsing or chunking, the cortical areas of the left hemisphere seemed to be doing the most work, while the putamen, an area of the brain linked to movement was responsible for putting the pieces back together after sufficient practice.

"These regions have been linked to the manipulation of motor information, which is something that we probably do more of when we just begin to learn the sequences as chunks," Wymbs said. "Initially, when you're doing one of these 12-element sequences, you want to pause. That would evoke more of the parsing mechanism. But then, over time, as you learn a sequence so that it becomes more automatic, and the concatenation process takes over and it wants to put all of these individual elements into a single fluid behavior."

So, what Gruden was trying to tell Newton was that learning an NFL playbook and all of the movements that underlie the terminology was simply a chunking drill. After Newton’s very successful rookie season, it seems he may have taken the coach’s advice.

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Predicting NFL Success By What Draft Picks Say

Thankfully, the NFL Draft and all its hype is behind us.  The matchmaking is complete but the guessing game begins as to which team picked the right combination of athletic skill, mental toughness and leadership potential in their player selections.  Hundreds of hours of game film can be broken down to grade performance with X’s and O’s.  Objective athletic tests at the NFL combine rank the NCAA football draftees by speed and strengths, just as the infamous Wonderlic intelligence test tries to rank their brain power.  

However, despite all of this data, coaches and general managers often point to a player’s set of fuzzy personal qualities, dubbed the “intangibles”, as the ultimate tie-breaking determinant to future success in the league.

Always looking for the edge in this crystal ball forecasting, teams are turning to other technologies and methods that have been used in related assessment arenas in business and politics.  As any good self-improvement speaker will tell you, success leaves clues.  By studying established leaders, certain traits, attitudes and themes can be identified as consistent “bread crumbs” left behind for others to follow.  In the same way, potential leaders that don’t pan out also demonstrate patterns of behavior that can be linked to their less-than-hyped performance.

Now, a new tool is available to NFL front offices and, as with many high-tech innovations, they have the U.S. military to thank.  Achievement Metrics, a risk prediction service for the sports industry, now provides speech content analysis meant to give the odds of a budding superstar either rising into a leadership role or sinking into legal trouble based on just their public comments.  Their base technology grew out of the work that their sister company, Social Science Automation, has provided to the CIA and government agencies including profiles of possible terrorists, based on their use of language.

Using only the transcripts from a player’s recent college press conferences or interviews, the company’s computer algorithms find patterns in a player’s words and phrases.  Its not just a few vocabulary no-no’s that set off the alarms, but rather a pattern of selected triggers from a “hot list” of over 2000 words.  So, unlike the Wonderlic IQ test that might allow for some pre-test cram sessions to increase the score, this analysis is much more intricate and based on an athlete’s words from the past.  And, by using just the transcripts of speech, the tone, volume and pronunciation of the words don’t matter; simply the ideas and subconscious selection of phrasing.

Combining numerical text analysis stats such as word meanings and frequency with established psychological profiling theories, players can be categorized in dimensions such as need for power, level of self-centerdness, ability to affect destiny and many more.

Currently, the database includes an analysis of 592 NFL players’ speech patterns matched with their off-field behavior, both positive and negative, with a correlation algorithm.  As much as this seems like a scene from Minority Report and the fictional “Pre-Crime” department, the accuracy of the results are impressive, according to the company website:

-  89 percent (89 out of 100) of the players placed in the high-risk category have been arrested or suspended while in the NFL.
-  Even more striking, only 0.13 percent (two out of 1,522) of players categorized as low-risk have been arrested or suspended during their professional careers.
-  Of the players in the database who have been arrested or suspended while in the NFL, the models placed 98 percent (104 out of 106) in the intermediate- or high-risk category based on their football-related speech from college.

Below is the current scatter plot graph that shows the distribution of NFL subjects along a “bad behavior” continuum from their database.  Any college football player who ends up in Areas 3 or 4 after his speech analysis is not good news for his future employer.

Here is Roger Hall, Achievment Metrics’ CEO and psychologist, explaining the process at the MIT Sloan Sports Analytics Conference held in March:

As Hall notes in his presentation, quarterbacks can have a major influence on an NFL team, so there has been much focus on the 2011 crop of draft picks and their chances of success.  Not to leave us hanging, Hall recently released the analysis of this group alongside some of the established QBs in the league.  On the Y-axis is the Positive Power score, or the level of belief in self-controlled destiny and along the X-axis is Ingroup Affiliation or the level of team orientation.  If given a choice, a team would probably prefer their prospect to be in the Aaron Rodgers/ Philip Rivers quadrant rather than the Alex Smith/Matt Leinart quadrant.

Assessing off-field risk is only the beginning for this type of analysis as long as the correlation equals causation relationship is believed and backed up with more data.  While some old school scouts and evaluators will cling to their intuitions, more forward-thinking GMs will try any new angle to get the edge.  It may just turn out to be a $20 million edge.