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On Redheaded Quarterbacks and Whether Linemen Can Swim

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Quarterback in the NFL is the position that drives the franchise, sometimes into a sinkhole that swallows reasonable chances of success for years on end.


No wonder teams spend so much pre-draft time prodding, probing and analyzing quarterbacks. The decision is so costly and important that the term "pre-draft" as it pertains to the evaluation and measuring of QB prospects has been expanded to include college career, choice of high school prom date, kindergarten teamwork skills and, this year, conception.


An NFL coach doing his homework (and more) in advance of tonight's prime-time NFL draft hinted in last week's Sports Illustrated at a concern about whether TCU quarterback Andy Dalton can lead a team, seeing as how he's got red hair and not many great red-headed quarterbacks came instantly to the coach's overtaxed mind.

"Has there ever been a red-headed quarterback in the NFL who's really done well?" the coach asked. "It sounds idiotic, but is there any way that could be a factor? We've wondered."

True enough.

It does sound ridiculous.

The Brady 6

Quarterbacks are almost always the story of every draft, even when they aren't the story of the draft. Just wait a few years and they will be.

ESPN just aired a documentary on "The Brady 6," the six (mostly) failed quarterbacks who were chosen ahead of future Hall of Famer Tom Brady in the 2000 draft. Chad Pennington was the only first-rounder of the group, and he did manage to make a name for himself with the New York Jets. Marc Bulger acquitted himself well enough, too.

Pennington, Bulger, Tee Martin, Chris Redman, Giovanni Carmazzi and Spergon Wynn came off the board before the New England Patriots made Brady the 199th player chosen.

That would seem to add to the genius reputation of New England head coach Bill Belichick...once he explains why he took Adrian Klemm, J.R. Redmon, Greg Robinson-Randall, Dave Stachelski, Jeff Marriott and Antawn Harris before he got around to Brady.

The moral is quarterbacks are the greatest risk-reward position in the draft. And Andy Dalton's chromosomes aren't the only thing under the microscope this year.

Cam Newton's Fake Smile

A Pro Football Weekly evaluation of Auburn quarterback Cam Newton was hardly kind.


"Very disingenuous," writer Nolan Nawrocki wrote of Newton. "Has a fake smile, comes off as very scripted and has a selfish, me-first makeup. Always knows where the cameras are and plays to them."


"Has an enormous ego with a sense of entitlement that continually invites trouble and makes him believe he is above the law - does not command respect from teammates and will always struggle to win a locker room..."


"Lacks accountability, focus and trustworthiness - is not punctual, seeks shortcuts and sets a bad example. Immature and has had issues with authority. Not dependable."


Auburn quarterbacks coach Fred Whitfield ripped Nawrocki when he found out about the assessment.

"Nawrocki spent 10 (minutes) with Cam? Drunks can say that."

The critique of Newton could be called "damning" if the Carolina Panthers weren't expected to take Newton with the first overall pick tonight. It's difficult to go higher than first.

One NFL team threw Newton a curveball in the NFL Scouting combine interview period. Newton was asked why he changed a play from the sideline during Auburn's national championship win. The play worked. Newton supposedly got defensive about the question.

Teams test players that way. In fact, they test players so many ways they get away with inane questions because players figure there must be a deeper meaning, even when there isn't.

Questionable Questions

Washington quarterback Jake Locker told a Seattle radio show about the strangest question he was asked during the process leading to Thursday's draft.

"I was asked if I had a 16-year-old daughter whether I'd let her be on birth control or not," Locker related. "That one kind of threw me for a loop. It caught me off guard. I didn't know what to say at first."

Locker said he wouldn't.

Teams apparently give it their all when trying to come up with questions for quarterbacks. They don't waste just any questions on the men who will direct their teams for seasons to come.

It's standard to ask players if they'd rather go to five Pro Bowls or win one Super Bowl in an attempt to find out how me-oriented they are. Most players see that one coming a football field away.

Ohio State offensive lineman LeCharles Bentley, who would go on to Pro Bowl status in New Orleans, was asked if he could swim for some reason. Other players have been asked if they can sing.

Some years ago, one team official asked Ohio State offensive lineman Kirk Barton if he'd rather be a dog or a cat.

"You wonder if it's a house cat or a tiger," Barton said at the time. "If it's a tiger, then you're solid. But a dog can beat a regular cat. I always pick the dog."

And -- coincidentally -- more than one team will pick a dog in the 2011 Quarterback Class.

The Obligatory Ryan Leaf Mention

For every Hall of Famer like Peyton Manning, there's a bust like Ryan Leaf.

The Indianapolis Colts picked Manning No. 1 in the 1998 draft. The San Diego Chargers picked Leaf No. 2.

"You can go five to ten years without getting a chance to draft a quarterback like this," former San Diego GM Bobby Beathard said of Leaf that day.

As it turned out, only if you're lucky.

The Quarterback Ghosts of Past Drafts Gone Bad

As NFL teams ponder Newton at No. 1, Missouri's Blaine Gabbert in the Top 10 and other possible first-and second-rounders like Dalton, Locker, Ryan Mallett and Christian Ponder -- other names must be rattling around in the heads of personnel men along with all that information about size, mechanics, leadership and hair color.

Consider this list:

Chuck Long, Detroit (No. 12, 1986), Rick Mirer, Seattle (No. 2, 1993), Heath Shuler, Washington (No. 3, 1994), Tim Couch, Cleveland, (No. 1, 1999), Cade McNown, Chicago, (No. 12, 1999), Akili Smith, Cincinnati (No. 3, 1999), David Klingler, Cincinnati (No. 6, 1992), Andre Ware, Detroit (No. 7, 1990), Kelly Stouffer, St. Louis (No. 6, 1987), Joey Harrington, Detroit (No. 3, 2002), David Carr, Houston (No. 1, 2002), Jack Thompson, Cincinnati, No. 3, 1979, Todd Blackledge, Kansas City, No. 7, 1983 and Art Schlichter, Baltimore (No. 4, 1982).

Oh, and Todd Marinovich, Raiders (No. 24, 1991)

Come to think of it, didn't Marinovich did have red hair?

[Cam Newton image: © Gene Lower/ZUMA Press/Corbis]

Bud Shaw is a columnist for the Cleveland Plain Dealer who has also written for the Philadelphia Daily News, San Diego Union-Tribune, Atlanta Journal-Constitution and The National. You can read his Plain Dealer columns at Cleveland.com, and read all his mental_floss articles here.

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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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8 Common Dog Behaviors, Decoded
May 25, 2017
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Dogs are a lot more complicated than we give them credit for. As a result, sometimes things get lost in translation. We’ve yet to invent a dog-to-English translator, but there are certain behaviors you can learn to read in order to better understand what your dog is trying to tell you. The more tuned-in you are to your dog’s emotions, the better you’ll be able to respond—whether that means giving her some space or welcoming a wet, slobbery kiss. 

1. What you’ll see: Your dog is standing with his legs and body relaxed and tail low. His ears are up, but not pointed forward. His mouth is slightly open, he’s panting lightly, and his tongue is loose. His eyes? Soft or maybe slightly squinty from getting his smile on.

What it means: “Hey there, friend!” Your pup is in a calm, relaxed state. He’s open to mingling, which means you can feel comfortable letting friends say hi.

2. What you’ll see: Your dog is standing with her body leaning forward. Her ears are erect and angled forward—or have at least perked up if they’re floppy—and her mouth is closed. Her tail might be sticking out horizontally or sticking straight up and wagging slightly.

What it means: “Hark! Who goes there?!” Something caught your pup’s attention and now she’s on high alert, trying to discern whether or not the person, animal, or situation is a threat. She’ll likely stay on guard until she feels safe or becomes distracted.

3. What you’ll see: Your dog is standing, leaning slightly forward. His body and legs are tense, and his hackles—those hairs along his back and neck—are raised. His tail is stiff and twitching, not swooping playfully. His mouth is open, teeth are exposed, and he may be snarling, snapping, or barking excessively.

What it means: “Don’t mess with me!” This dog is asserting his social dominance and letting others know that he might attack if they don’t defer accordingly. A dog in this stance could be either offensively aggressive or defensively aggressive. If you encounter a dog in this state, play it safe and back away slowly without making eye contact.

4. What you’ll see: As another dog approaches, your dog lies down on his back with his tail tucked in between his legs. His paws are tucked in too, his ears are flat, and he isn’t making direct eye contact with the other dog standing over him.

What it means: “I come in peace!” Your pooch is displaying signs of submission to a more dominant dog, conveying total surrender to avoid physical confrontation. Other, less obvious, signs of submission include ears that are flattened back against the head, an avoidance of eye contact, a tongue flick, and bared teeth. Yup—a dog might bare his teeth while still being submissive, but they’ll likely be clenched together, the lips opened horizontally rather than curled up to show the front canines. A submissive dog will also slink backward or inward rather than forward, which would indicate more aggressive behavior.

5. What you’ll see: Your dog is crouching with her back hunched, tail tucked, and the corner of her mouth pulled back with lips slightly curled. Her shoulders, or hackles, are raised and her ears are flattened. She’s avoiding eye contact.

What it means: “I’m scared, but will fight you if I have to.” This dog’s fight or flight instincts have been activated. It’s best to keep your distance from a dog in this emotional state because she could attack if she feels cornered.

6. What you’ll see: You’re staring at your dog, holding eye contact. Your dog looks away from you, tentatively looks back, then looks away again. After some time, he licks his chops and yawns.

What it means: “I don’t know what’s going on and it’s weirding me out.” Your dog doesn’t know what to make of the situation, but rather than nipping or barking, he’ll stick to behaviors he knows are OK, like yawning, licking his chops, or shaking as if he’s wet. You’ll want to intervene by removing whatever it is causing him discomfort—such as an overly grabby child—and giving him some space to relax.

7. What you’ll see: Your dog has her front paws bent and lowered onto the ground with her rear in the air. Her body is relaxed, loose, and wiggly, and her tail is up and wagging from side to side. She might also let out a high-pitched or impatient bark.

What it means: “What’s the hold up? Let’s play!” This classic stance, known to dog trainers and behaviorists as “the play bow,” is a sign she’s ready to let the good times roll. Get ready for a round of fetch or tug of war, or for a good long outing at the dog park.

8. What you’ll see: You’ve just gotten home from work and your dog rushes over. He can’t stop wiggling his backside, and he may even lower himself into a giant stretch, like he’s doing yoga.

What it means: “OhmygoshImsohappytoseeyou I love you so much you’re my best friend foreverandeverandever!!!!” This one’s easy: Your pup is overjoyed his BFF is back. That big stretch is something dogs don’t pull out for just anyone; they save that for the people they truly love. Show him you feel the same way with a good belly rub and a handful of his favorite treats.

The best way to say “I love you” in dog? A monthly subscription to BarkBox. Your favorite pup will get a package filled with treats, toys, and other good stuff (and in return, you’ll probably get lots of sloppy kisses). Visit BarkBox to learn more.

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