Panthers' 'Riverboat Ron' Rivera backing decisions with big data
09/02/2014 6:28 PM
09/03/2014 1:27 AM
Carolina Panthers coach Ron Rivera prefers “Calculated Risk-Taker” Rivera to his “Riverboat Ron” moniker, and an offseason dinner discussion might have made the former more appropriate.
Inspired in part by a conversation at a banquet with John Young, a vice president of a software and development firm in Kansas City called DST Systems, Rivera has taken a deeper look at the analytics behind going for it on fourth down. He promises his risk-taking mentality won’t change, but Rivera is taking more factors into account.
“If I can balance risk and uncertainty by classifying and categorizing information,” Young told the Observer by phone this week, “and then understand the probability of success, and then I marry that with the expertise of an NFL football coach like Ron Rivera, who also played football, then they can make better decisions.
“They can say my gut is telling me this, and the data is telling me this, so it either supports or goes against my gut. It’s the ability to use the data to make more informed decisions.”
Rivera met Young at the NFL’s 101 Awards in Kansas City in March. Rivera sat at the sponsor’s table, where Young and his wife were guests. After being introduced to Young and learning his background in data science, Rivera wanted to know more.
Young, a former pitcher at Northern Colorado who holds a Ph.D in statistics, uses advances statistics for his 10-year-old son’s competitive baseball team to determine batting order and what pitchers to pair together. Young and Rivera talked about data, and then Rivera brought up the game that changed his outlook on fourth downs.
In the second game of last season against the Buffalo Bills, Rivera opted to kick a field goal with 1:42 remaining in the game rather than trying to convert a fourth-and-1 from the Buffalo 21-yard line. A conversion would have effectively ended the game, but instead Carolina went up by six.
The Panthers would lose by a point when the Bills scored a last-second touchdown. On the way back to Charlotte, Rivera thought about his decision. From there, Riverboat Ron was born, and Carolina went 10-for-13 on fourth-down conversions the rest of the season.
“(Young) said the thing you have to be careful about is, what are the other variables?” Rivera said. “And the first thing he said to me was, ‘There’s also one thing, Coach, that we can’t measure. That’s the flow of the game.’ ”
With 2:04 left in the fourth quarter against New Orleans, down three points, Rivera opted to punt from the Carolina 36. The Bank of America Stadium crowd booed the decision, and Rivera said even his mother was mad at him for not living up to his nickname in the Week 16 game that would get Carolina into the playoffs.
But the Panthers held the Saints to a three-and-out and forced New Orleans to punt. Rivera thought the Panthers would get close enough to kick a field goal and go to overtime, but instead Cam Newton found Domenik Hixon for a game-winning touchdown.
“That was the flow of the game,” Rivera said. “Defensively we had been playing our butts off and made some good things happen. And so everybody thought I should have gone for it. But my thought on that was, maybe we can pin them. And that’s what happened.”
The New York Times’ Fourth Down bot, an analytic model that judges coaches’ calls on fourth downs, said Rivera should have gone for it rather than punted against New Orleans. Young reviewed the bot’s analysis of Carolina’s fourth downs and emailed Rivera with his own analysis, saying that though the bot is interesting to look at, it doesn’t provide information about why it’s making the recommendations nor is there a detectable pattern in its selections.
But big data is just that – big. In the 40 seconds on the playclock between third and fourth downs, a coach has to input all the data he has on distance, personnel, field position, time of game, health of the players and more. And that’s before looking at the defense, weather and other mitigating factors.
Young says teams should collect descriptive information based on down and distance, field position and time of game and have that ready the moment the playclock begins. Then a coach can marry the other factors on the field, make the play call and have the ball snapped before the play clock expires.
The information goes deep, Rivera said, and it can go too deep.
“(You get) to the point where you have to be careful because you’re going to suffer paralysis by analysis,” Rivera said. “You’re going to sit there looking at your card looking stuff up, and before you know it, the ball’s getting snapped.
Football, and other sports, lag behind baseball in its use of advanced statistics, but Young believes as football begins collecting more data, the sport will evolve into something more.
“We see it all the time in business,” Young said. “People say, ‘Well I make $10 million a month with this product line, why do I need data? I use my gut and look at industry trends.’ But then you see emerging data science in conjunction with the gut view and understanding and direction and strategy; you see it go from a $10 million a month product to $40 million a month.
“You really have to have that strong collaboration between the data science and the people making those decisions who really love and understand the game of football like no one else.”
The first test to see if Rivera remains Riverboat Ron comes Sunday at Tampa Bay, and left tackle Byron Bell expects his coach will have to make a decision in the first game of the season.
“Being the competitor coach Rivera is, I’m pretty sure he’s going to make it happen,” Bell said. “When he dials it up and says the offense stay out there, we got to make it happen. I’m pretty sure in Week 1 we’re going to be in one of those situations where we’re on the 50 or their 45 and he’s going to go for it. He’s got faith in our defense, and he’s got faith in us to go for it.
“Whenever he puts $1,000 on black, it’s going to have to hit black.”
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