Yadier Molina Forgot How To Frame A Pitch

Yadier Molina is falling apart. It’s not his hitting, and it’s not his base running. It’s too early in the season to say much that is meaningful about those skills, which can take months of stats to become reliable.It’s the Cardinals catcher’s defense that’s a mess. Molina’s pitch framing has collapsed, dropping from third-best in 2013 to 60th in 2015.1Using Baseball Prospectus’s framing metric, Called Strikes Above Average. And the Cardinals are at real risk because of it. Framing was thought of as mythical until researchers found direct evidence for it in how umpires were calling borderline pitches. The idea is simple: A catcher receives a pitch and “frames” it so that the pitch is more likely to be called a strike. In contrast to descriptions of framing as cheating, good framing involves catching the pitch with a minimum of excess motion. In so doing, the catcher offers the umpire a clear view of the ball and thus collects more favorable strike calls.Since 2008, Molina has been the fifth-best framer in the league. In that time frame, Molina has saved more than 114 runs by flipping pitches that would have been close calls to strikes (worth about 11 wins, in aggregate). Since pitch framing isn’t yet accounted for when sabermetricians project a team’s statistics, Molina’s secret skill helps to explain the Cardinals’ outdoing their projections for the past 10 years and some of their perpetual October success (though to a lesser extent).But this year, Molina’s framing is no longer even average. Already in 2015, Molina has cost his team about four strikes, while the best framers have gained more than 15. That may not sound like much, but over the course of a season, it could add up to a gap of more than 150 strikes, worth something like 25 runs. In his best year (2013), Molina acquired roughly that many extra strikes for his team, equating to an extra couple of wins per year for the Cardinals. This is no small-sample fluke, either. Unlike hitting and pitching, whose outcomes we still measure in the dozens this early in the season, Molina has seen 800 pitches this year. That sample size is plenty big.It’s hard to know why Molina has lost his mojo. Some of Molina’s apparent decline may stem not from his own skill diminishing, but rather from other catchers becoming better. As front offices have become convinced of the importance of framing, we’ve seen many light-hitting but exceptional-framing backstops be promoted to full-time roles. Since Molina is always being compared to the average, if the average moves up, it may appear as though Molina is falling.It’s possible that the physical toll of catching has finally caught up to Molina. Notably, he showed up to spring training about 20 pounds lighter than the weight at which he played for the past 10 years. Molina gave no specific reason for the weight loss when asked, but Adam Wainwright (among others) suggested that it may have been to reduce the wear and tear on his knees.A decline by Molina, even without cryptic injuries, was not totally unexpected. Although pitch framing doesn’t appear physically demanding, research has shown that there is a clear aging pattern for the skill. Catchers improve when young but decline in their 30s. At age 32, Molina is entering the part of the curve with the most rapid decline.Still, rapid is an understatement for Molina’s framing slump. Molina’s framing has been falling off of a cliff for two consecutive years, dropping from excellent to above average from 2013 to 2014 and from above average to poor from 2014 to this year. The decline went largely unnoticed last year, as Molina struggled with injuries that limited his playing time.This year, it’s unmistakable. If you look for two-year declines as large as Molina’s since 2008, there’s only one other player with as many chances who has fallen off as much: Brewers catcher Jonathan Lucroy this year. (Strangely, Lucroy is 28 years old, still relatively young.) Age tends to reduce framing ability, but rarely as quickly as it has in Molina’s case.Regardless of the cause, Molina’s framing decline affects more than just his own stats. Normally, pitching statistics are much too variable this early in the season to say anything useful. But by learning about Molina’s decline, we may also, in a roundabout way, learn something about the Cardinals’ pitching.To do so, we can look at the recent history of pitchers who lost great framers. Molina isn’t lost, of course, but his framing skills might as well be. In the past three years, 166 pitchers have stayed on the same team but seen their framers decline in quality by a magnitude similar to Molina’s decline from last year to this year. Those 166 pitchers did 0.76 runs of ERA worse than expected.2By PECOTA’s projections. Compared to the overall population of pitchers in that time (who performed 0.47 runs of ERA worse than expected), the pitchers throwing to worse framers saw their ERAs increase3This pattern bears out if you weight ERAs by innings pitched, as well as in the opposite direction: Pitchers who go from bad framers to good see their performances exceed their projections. by 0.28 runs.4But 0.47 runs + 0.28 runs doesn’t add up to 0.76 runs, you protest! Blame rounding.To any given pitcher, a 0.28 increase in ERA is relatively minor. It could be dismissed as merely bad luck. However, Molina doesn’t just work with a single pitcher — his framing affects every pitcher on the team.5Nor will Molina’s backup, Tony Cruz, be any help in this regard. Cruz is a below-average framer as well. His newfound problems will affect each hurler to only a small extent, but the staff as a whole will be dramatically harmed. Over the course of a season, the total effect of the fall from top-tier to below-average framing is something like three wins. In a competitive NL Central, that’s a hefty price to pay. read more

Chris Paul Is A Point God

Practice makes perfect, and in an era defined by a glut of incredible point guards, Paul still stands out as one of the best of the best. His basketball portfolio is incredibly diversified; he’s an incredible passer, a creative genius, one of the game’s best midrange shooters, and he’s one of the most consistently great defenders at his position too. Still, any discussion of Paul in 2015 must address the elephant-sized trophy not in the room: As great as he and his numbers have been, he’s never played in the conference finals, and his last two playoff exits have been brutal. It weighs on him, and he doesn’t want to go down as some “statistically great” point guard who never won. “All that’s good and well, but it doesn’t matter unless it translates to wins,” Paul said.A few weeks into this new season, Paul and the Clippers remain a threat to win it all. With a reloaded roster and one of the most talented teams in the league, they have the potential for greatness. And Paul is hopeful that he and his teammates can turn their recent frustrations into motivation to finally get over the hump. “We got a lot guys with something to prove, a lot of guys that got a chip on their shoulder,” Paul said. “I think with that combination, we can make something special.”That obviously remains to be seen. But Thursday night, the Clippers host their bitter rivals from Oakland, who are led by their own superstar point guard and just happen to be the hottest basketball team on the planet right now. Paul and the new-look Clippers have an early chance to prove something. Last season, Paul assisted on 231 threes, and 98 of those went to Redick, making Paul-to-Redick the most prolific 3-point partnership in the entire league.1The top 3 partnerships: 1) Chris Paul to J.J. Redick for 98 3-pointers; 2) Stephen Curry to Klay Thompson for 88 3-pointers; 3) James Harden to Trevor Ariza for 80 3-pointers.As you can see below, Paul helped set Redick up all over the place, but those triples are clearly the pair’s signature collaboration. Paul has a bit of a reputation for getting mad at his teammates, but according to him, the only time he gets angry with Griffin is when Griffin is too passive with that improved jumper. “I’m probably harder on Blake than anybody about taking his shot,” Paul said. “I told him, the only time you’ll see me get mad if I pass it to someone is when they don’t shoot it.”Griffin’s jumper has come so far so fast that Paul seems more confident in it than Griffin does. “I think it’s going in every time,” Paul said. “And that’s a tribute to all the work he’s put in.”You don’t become the most efficient offense in the NBA without versatility, but the NBA is still a pick-and-roll league. Griffin’s emergence as one of the game’s most versatile bigs has enabled Paul to attack defenses in multiple ways. After all, it’s still Paul at the controls, and it’s his ability as a catalyst that has enabled the team to coalesce into something more than the sum of a bunch of NBA parts.While we all know that Paul is among the best distributors in the world, his ability to generate his own shots remains arguably the most unheralded section of his game. He’s one of the best unassisted scorers in the world. It’s that particular skill that lends the Clippers offense one of its most lethal — and most primitive — options. Not every possession will end with a tidy catch-and-shoot sequence, and when defenses disrupt the Clippers’ pre-orchestrated plans, they still have to deal with Paul, one of the most effective off-the-dribble scorers in the league.It’s no secret that point guards, as the chief ball-handlers of NBA offenses, dribble the ball more than any other position. In turn, they are much more likely to shoot in unassisted off-the-dribble situations, shots that we’re beginning to understand are statistically much more difficult on average. It’s not rocket science, but generally speaking, catch-and-shoot jumpers are much more likely to go in than their unassisted, off-the-dribble counterparts.League-wide, just about half of all field goal attempts qualify as unassisted. Many times, as possessions unravel over time, some offensive player will have to “create his own shot,” and any players who can do that reliably and efficiently present their teams with a huge offensive stopgap. When Paul needs to, he can create a decently efficient scoring chance at-will, meaning that when he is on the floor, the Clippers’ “last resort” is a pretty efficient option.Paul has been one of the league’s top point guards for years now. But he hasn’t been the same player the whole time. Back in his days in New Orleans, he relied more on his speed and less on his smarts. “Once upon a time, I was all downhill, you know, obsessed with getting to the basket — like Dame [Lillard] and stuff like that — but then I realized in New Orleans I need to get this midrange down,” Paul said.There’s that perfectionism again. The way he describes it, you might think he was terrible. As a rookie, Paul already had a reliable elbow jumper and hit that key shot at rates that would make players like Russell Westbrook or John Wall envious. That 3-pointer that helped beat Memphis earlier this month provides a great example. Despite the fact that Paul was careening through the paint at breakneck speed among a trio of elite defenders, he still managed to deliver Redick a perfect pass. But Paul self-identifies as a “perfectionist,” and according to Redick, it tears him up on the rare occasions when his dishes are dirty: “It’s just so precise what he does. He throws me perfect, on-time, on-target passes at all times. I joke about this with him all the time, but once every 150th pass or so, it’ll be off-target, and he’ll get so upset with himself. And I’m like, ‘Bubs, I could never get mad at you for that.’”I could never get mad at you for that? The two bitter ACC rivals have morphed into an old married couple … an old married couple that represents one of the most lethal catch-and shoot threats on planet Earth. Still, as marvelous as that is, a quick look at the league’s most dangerous duos from last season reveals that while Paul-to-Redick was the most prolific 3-point pairing in the entire league, it wasn’t even the most prolific point-scoring duo on the Clippers.Most Prolific Assister-Scorer Duos, 2014-15 Regular SeasonChris Paul to Blake Griffin: 527 pointsChris Paul to J.J. Redick: 524 pointsStephen Curry to Klay Thompson: 426 pointsIn a league with dozens of point guards, Paul was the distributor in the two highest-scoring pairings. That’s incredible. And while the Splash Brothers deserve limitless praise for what they accomplished last season, Paul’s abilities as a facilitator remain second to none, and nobody knows that better than Blake Griffin, the Clippers’ top scorer.Last season, Griffin ranked eighth in the league in scoring, averaging 22 points per contest. He was and is the Clippers’ most dangerous scorer. Still, even the league’s best scorers rely on assists on a regular basis, and last season, 67 percent of Griffin’s buckets were assisted, and 45 percent of his field goals came off assists by Paul. In other words, almost half of Griffin’s buckets are directly downstream from Paul’s passes.Griffin has come a long way since entering the NBA as a rookie in 2010; the player we’re seeing now can do a lot more than the phenom who jumped out of the gym five years ago. Griffin had all the athletic ability in the world coming out of college, but it takes more than raw athletic ability to be an NBA superstar these days, especially at the power forward position, which increasingly is becoming one of the most demanding jobs in the game. Players like Dirk Nowitzki, Kevin Garnett, Chris Bosh, Serge Ibaka and Kevin Love have changed the job description by using their reliable jump shots to open up the floor for their playmaking teammates. When Griffin landed in the NBA, he could jump over Kias, but he couldn’t shoot like those players.But Griffin is no fool, and he knew that to become great at his position, and prolong his career, he needed to develop his jumper. Griffin has worked endlessly with Bob Thate, the Clippers’ shooting guru, and all that work has paid off. As a rookie, only 15 percent of Griffin’s shots came from between 16-feet and the 3-point line; he made just 34 percent of them. So far this season, 37 percent of Griffin’s shots are coming in this zone, and he’s converted 48 percent of them. For context, the league as a whole makes 40 percent of its shots from this area. Griffin’s improvement has improved the entire Clippers offense — just ask Paul. “Blake having that shot now makes defenses worry about one more thing,” Paul told me. “You gotta worry about his roll to the basket, his passing, and now that shot. Now it’s like, ‘What can’t he do?’” Earlier this month at Staples Center, the Memphis Grizzlies were leading the Los Angeles Clippers by two points with a minute remaining in the game. The Clippers had the ball and needed a bucket. Chris Paul dribbled quickly past a DeAndre Jordan screen at the top of the arc before he turned the corner and attacked the right side of the paint. As Paul raced toward the rim, he was dogged by Tony Allen and Mike Conley, two terrific defenders creating a situation that would overwhelm most NBA point guards. But Paul isn’t most NBA point guards.As Paul reached the right block, he was met by Marc Gasol, the 2012-13 NBA defensive player of the year. Unfazed, Paul spun in the air and somehow hurled the ball 20 feet backward, all the way back to the top of the arc, which was solely occupied by an unattended J.J. Redick, one of the most reliable catch-and-shoot guys on the planet. The rest was merely a formality.You’re not supposed to get wide-open shots like that against the Grizzlies, especially in such a key late-game situation. Memphis has been one of the best defensive groups in the NBA for years. But sometimes great offense beats great defense, especially when Chris Paul is running an offense; his team almost always gets good looks. He’s led the league in assists two years in a row, and the Clippers were the most efficient offensive team in the league last season. But those simple numerical accolades fail to adequately reveal just how great Paul has been.As NBA analyses evolve, we have new means to understand how great point guards like Paul change the game. Assists are one thing. But they account only for the shots that teammates make, and that’s only part of the playmaking story. Thanks to the league’s player tracking system, we can now analyze the origin of every shot in every game. Upon closer inspection, when Paul is creating shots — either for his teammates or for himself — he blends volume and effectiveness as well as anyone in the NBA.Most NBA fans are aware that Paul is great at sharing the ball, but few know that all those assists led to 24 points per game last season. Anthony Davis tallied that exact number as a scorer — and that made him fourth in the league in scoring. In other words, not only did Paul manage to score 19 points per game himself, but as a distributor, he also created another Davis-sized contribution as well.The chart below shows the shooting efficiencies of Paul’s Clipper teammates last season immediately after they received a pass from him. As you can see, good things happen on the business end of a Chris Paul dime. The NBA is a league increasingly obsessed with creating more threes on offense, which also makes it a league increasingly obsessed with stopping them on defense. And if you’re guarding Redick these days, you know perfectly well that he is perpetually seeking out clean catch-and-shoot looks beyond the arc. You also know that it’s Paul who’s likely to deliver him the ball. But Redick is quick to point out that Paul can outwit almost any defensive approach thrown his way. “Chris is incredibly intelligent,” Redick told me. “So, a lot of times, if a defending point guard knows we’re running catch and shoot, they’ll try to shade one side (especially the left side, because I always come off the left side). But Chris is so good at keeping guys guessing, and if his man cheats, he’ll go to the basket on him. He always makes people pay if they try and cheat.” During Paul’s rookie year, just 9 percent of his shots came between 10 and 16 feet; he converted only 33 percent of them. Last year, 23 percent of his shots came from this area, and he sunk an incredible 53 percent of them.Paul is arguably the best midrange shooter on the planet right now. And, yes, that planet also includes Nowitzki and Curry. And while that may seem like hyperbole, the numbers back up the idea that nobody can blend volume and efficiency in the midrange as well as Paul can, especially when you consider that most of his attempts in that area are those unassisted, higher-level-of-difficulty shots.But Paul makes those shots look easy on a regular basis. Not only did he lead the league in unassisted midrange field goals last season, but out of 61 players who attempted at least 200 of those shots, he ranked first in field goal percentage, by a country mile. The following scatterplot leaves little doubt just how extraordinary Paul’s midrange prowess has become: A quick comparison of Paul’s rookie shot chart with last season’s reveals that the biggest upticks in his game have come from downtown. As a rookie, only 19 percent of his shots came from beyond the arc, and he converted a ghastly 28 percent of them. Last season, those numbers ballooned to 30 percent and 40 percent, respectively. read more

Significant Digits For Friday Dec 4 2015

You’re reading Significant Digits, a daily digest of the telling numbers tucked inside the news.0.12An attorney who wrote a book called “The Drinker’s Guide to Driving: The Secrets of DUI from One of America’s Top DUI Lawyers” was arrested for drunk driving Sunday, with a blood alcohol level of 0.12. Yes, it did happen in Florida — excellent guess. [The Herald Tribune]2nd-longestAfter his team trailed all night against the Detroit Lions, Green Bay Packers quarterback Aaron Rodgers threw a 61-yard game-ending Hail Mary pass for a touchdown with no time on the clock. The pass was the second-longest come-from-behind game-ending touchdown ever, and from a distance where such passes have a terrible completion rate. It was the worst thing to happen to the city of Detroit since globalization and systemic mismanagement. [ESPN Stats & Info, Brian Burke]20:24Elvira Montes, an 81-year-old grandmother, was the oldest finisher in this year’s Beer Mile World Championships, finishing four beers and running 1 mile in 20 minutes, 24 seconds. She is what we in the business call a “role model.” We should all be so lucky reach age 81, let alone sustain a reliable competitive drinking habit. [Runner’s World]44.9 percentPercentage of U.S. adults who worked for an employer at least 30 hours per week in November, as measured by Gallup’s Good Jobs rate. [Gallup]92 countsThe other shoe has dropped, people, and it is feigning catastrophic injury in order to procure a yellow card as we speak. U.S. prosecutors announced a 92-count indictment against 16 FIFA officials yesterday, following up on a raid of a Swiss hotel where several officials were staying. [CNN] 95.7 degrees FahrenheitA spokesperson for the upcoming Olympic Games said that organizers did not consider it critical to pay for air conditioning in athletes’ quarters in Rio de Janeiro and that someone else will have to handle the costs. Keep in mind that this year, Aug. 19, which would be towards the end of the events this coming year, hit 95.7 degrees in Rio. [ESPN]589 reportersIn 2014, the number of reporters from niche outlets accredited by the U.S. Senate press gallery exceeded the number of reporters from daily newspapers. As someone from a niche outlet, I guess this is cool? Go niche outlets! [Pew Research Center]220,000 jobsAshton Carter, whose name makes him sound like he is a member of One Direction but who is actually America’s secretary of defense, announced yesterday that the U.S. military will open all combat jobs to women. About 220,000 such jobs within the armed forces had been closed to women. [The Washington Post]$5 millionThat’s the amount brilliant negotiator and world-renowned dealmaker Donald Trump wanted CNN to donate to charity to ensure his participation in an upcoming presidential debate. CNN declined, but the legendary businessman and genius arbitrator, who as we all know could strike an absolutely flawless deal with anyone, especially the Chinese, relented and decided to participate in the debate anyway, because the negotiating strategy of “giving up when your primary request isn’t met” is just a tactic from page one of “The Art of the Deal,” a book Trump definitely wrote all by himself. [The Washington Post]$117 millionAmount raised on Giving Tuesday, another manufactured holiday trying to chew the crumbs left over by the capitalist orgy that is Black Friday, albeit for charity. This is frankly encouraging, because I personally had a lot of trouble getting into the Small Business Saturday spirit this year. [NBC News]If you haven’t already, you really need to sign up for the Significant Digits newsletter — be the first to learn about the numbers behind the news. read more

Dwyane Wades Father Sued Over College Loan

Dwyane Wade Sr., father of Miami Heat star and two-time NBA Champion Dwyane Wade Jr., is being sued by the U.S. government for defaulting on a $4,630.46 loan used to pursue a degree from the Environmental Technical Institute, which specializes in the heating, air conditioning and refrigeration industry.According to TMZ, the loan was approved the same year D. Wade Jr. began his first year at Marquette University. The government is seeking full repayment of the loan with interest, bringing the total to $6,221.44.We’re pretty sure Junior can spot his dad the cash. read more

Chad Ochocinco Declares He Will Play Until Hes 40

Well, it was nice while it lasted. As suddenly as a dropped pass, Miami’s Chad Ochocinco is back to being a chatter box. The one-time top flight receiver claims he has another six years left in him in the NFL, although he has not been a factor as a receiver in the last three seasons.“I’m going to play ’til I’m 40 years old, and this year I’m going to show the world I can,” the 34-year-old Ochocinco told the Sun-Sentinel newspaper.And just think: HBO’s Hard Knocks crew has not event gotten to town yet for training camp.“There is physically nothing wrong with me. I want to race Clyde (Gates) right now. I’ve asked him,” Ochocinco said, referring to Gates, whose 4.31 40-yard dash time made him the fastest receiver in the 2011 NFL draft. “I’ve still got it. I’m a lot smarter and I’m still fast.”Ochocinco’s declaration comes less than a month after he was cut by the New England Patriots.A Miami native, he made the Pro Bowl six times, most recently in 2009. He had only a minor role in his lone season with the Patriots, catching 15 passes for 276 yards.“I ate every bit of that humble pie,” Ochocinco said. “I believe it made me a better man, a better player.“The Dolphins are the right team, the right offense. I’m at the good place in my life. Everything fits perfectly for me.”In his career, Ochocinco has caught 766 passes for 11,059 yards and 67 touchdowns. All of the Dolphins’ returning receivers have less than a dozen career TDs. read more

This Week In College Football All The Wild Scenarios That Could End

This scenario is the second-most-plausible because North Carolina is more likely to upset Clemson than Florida is to upset Alabama.What would come next is complex. (Which should come as no surprise — this is college football, after all.) If Clemson loses, four teams could be vying for the fourth playoff spot: Stanford, Ohio State, the newly crowned ACC champion Tar Heels and … Clemson. That’s right, our model thinks there’s a decent chance that the Tigers could make the playoff over North Carolina even if they lose the ACC title to the Tar Heels. At 42 percent, Clemson is better-positioned than any of the other three teams. But it’s close: Stanford isn’t far behind at 34 percent, should the Cardinal win the Pac-12.How could Clemson make it over the team it just lost to? The Tigers have a more impressive schedule than UNC and a signature win against Notre Dame. The Tar Heels suffer both from a weaker schedule and an embarrassing early season loss to South Carolina. Would that really be enough to outweigh North Carolina’s conference championship and its head-to-head win? FiveThirtyEight suspects that the model is being slightly too kind to Clemson,1In particular, although the model gives a bonus to conference champions, it does not directly consider head-to-head results. but the committee would have a lot to think about. As my boss Nate Silver wrote last year, only a handful of No. 1-ranked teams have lost their conference championship game. On average, those teams were demoted to No. 4 after the loss. If the Tigers suffered the same fate, they’d still be in the playoff. Still, there’s no guarantee that the playoff committee would treat them similarly.Instead of choosing an ACC team, the committee could opt for plans C or D: Stanford, if it wins the Pac-12 championship (it’s a slight underdog), or Ohio State. In some ways, this would recall the dilemma the committee faced last year: Without clarity about whether Baylor or TCU was the superior Big 12 option, it froze the Big 12 out of the playoff.If Stanford loses, the committee still has three teams to choose from. But once again, our model thinks Clemson is as likely to make it as anyone. The Tigers are given a 46 percent shot. The Tar Heels are not far behind with a 36 percent shot. In this scenario, an emphatic win over Clemson might be enough to get the Tar Heels in, while a close one might not. Ohio State would have a 17 percent chance — but one problem for the Buckeyes is that, if the committee is OK with a one-loss team that failed to win its conference, it might decide Clemson is the superior one.Alabama loses but Clemson wins (15 percent likelihood): College football starts in September with 128 teams and billions of different paths to the playoff. Nearly all of that multiverse has been closed off — on Saturday, it’ll be sealed for good.There are four major conference titles at stake Saturday, but only two could really cause chaos for the playoff selection committee: those of the SEC and ACC. The Big Ten championship game matters less, from our perspective, because the winner is almost certainly getting in. And the Pac-12 championship only comes into play if Stanford wins and Alabama or Clemson loses (or both).To break down just how those games could affect the playoff picture, my colleague Jay Boice and I ran 20,000 simulations of FiveThirtyEight’s College Football Playoff model. This gives us greater insight into both how Saturday’s games could play out and, more importantly, how the committee might make its playoff picks based on those outcomes.Two things we know:Oklahoma is in. In all our scenarios, the Sooners are virtually certain to make the playoff.The Big Ten winner is in. Whichever team wins the championship game — Iowa or Michigan State — its probability of making the playoff also approaches 100 percent, according to the model. (Our projection favors the Spartans.) It’s very unlikely that the loser gets in under any scenario, and so throughout this analysis it’s assumed that the loser is out.I analyzed the multiverse of playoff scenarios by first looking at the two most important games: the championship games for the ACC (Clemson vs. North Carolina) and the SEC (Alabama vs. Florida). If Alabama and Clemson win, the selection committee’s job is super easy, but if one or — Bear Bryant forbid — both lose, then it’s not so clear.If there is chaos on Saturday, three teams are standing offstage: Stanford, Ohio State and North Carolina. But none of them controls its own destiny (even if UNC beats Clemson). The model can’t say with any great confidence which of those teams would take the place of the Tide and/or Tigers should those favorites fall — or whether Alabama or Clemson would be replaced at all.The possible scenariosBoth Alabama and Clemson win (42 percent likelihood): This is the simplest outcome. The Tide and Tigers are in, alongside Oklahoma and the Big Ten winner. That’s an impressive pair at the top: an undefeated ACC champion and a one-loss winner of the SEC (arguably the strongest conference in college football). This is the likeliest scenario, happening 42 percent of the time.(Stanford fans: You may notice that the model gives the Cardinal a 3 percent chance if they win the Pac-12 in this scenario. It’s not happening; the model’s just being cautious/polite.)Alabama wins but Clemson loses (32 percent likelihood): This is the committee’s nightmare scenario: unlikely to happen, but ugly if it does. All of a sudden, there would be two slots available and five teams vying to fill them.If this happens, Stanford is the best bet to make it into the playoff. But only if it wins the Pac-12 championship. The Cardinal’s odds rise to 62 percent in this scenario — their highest probability of any of the rabbit holes we sent them down.Assuming Stanford wins …Then Clemson’s odds fall to 50/50. The Tigers, as noted earlier, are still considered potentially playoff-worthy by our model even if they lose to North Carolina. The ACC champion Tar Heels, however, aren’t a bad option either and are given a 43 percent chance. Ohio State is also a viable alternative at 30 percent.Alabama is unlikely to make it; the Tide have an outside shot at 12 percent. That makes sense, as both UNC and Stanford would have conference championships over Alabama, and in the Tar Heels’ case, they’d have fewer losses, too.However, should Stanford lose to USC …Then this quagmire becomes slightly less difficult (four teams for two spots). Clemson, North Carolina and Ohio State stand somewhere between a 48 percent and 67 percent shot in this scenario. Two-loss Alabama would be a longer shot at 24 percent.But to be honest, we’d be entering uncharted territory here. From an empirical point of view, these messy outcomes would be great: We’d learn a lot more about how the committee weighs conference championships, losses, strength of schedule and other factors. For football fans, though, they would be another controversial finish to a thrilling season. Which maybe should come as no surprise — this is college football, after all. This scenario would shake things up a lot. Clemson, Oklahoma and the Big Ten winner are locks — but the fourth team is anyone’s guess.We know, though, that it wouldn’t be Florida. Beating the Tide isn’t enough for the Gators. After an awful finish to the season — a 27-2 loss to Florida State after inexcusably close calls against Florida Atlantic and Vanderbilt — the Gators have lost more ground in the playoff chase than they can make up, and the model gives them just a 2 percent chance of making the playoff even with a win over Alabama. So an Alabama loss would probably shut the SEC out of the postseason.But who takes Alabama’s place would be a complicated question, depending in large part on what happened in Stanford’s game against USC.If Stanford won …The Cardinal would then be the best-positioned team to nab the fourth slot. They’re not a lock, though — the model thinks two-loss Stanford has a 61 percent likelihood of taking Alabama’s place.Behind the Cardinal is one-loss Ohio State, which has a 25 percent chance of making it if Alabama loses but Stanford and Clemson win. The Buckeyes are the defending national champion and had won 23 games in a row before losing to Michigan State on the last play of the game two weeks ago. We think Stanford probably has the inside track — but the committee could conclude that the Buckeyes’ overall résumé outweighs Stanford’s conference championship and two losses, especially if Stanford’s win over USC is underwhelming by its “eye test.”Beyond Ohio State, another team could conceivably make it in this scenario: that same Alabama team that just lost the SEC championship! The model gives the Tide a 13 percent chance of snagging a playoff spot if they lose and both Clemson and Stanford win. It’s doubtful that the committee will be so forgiving, however, unless perhaps the SEC championship involves a controversial finish.But if Stanford lost …It would clear the way for Ohio State. The one-loss Buckeyes make it 64 percent of the time that Clemson wins but Stanford and Alabama both lose. The two-loss Tide gets a 25 percent shot in this scenario. For what it’s worth, ESPN’s Football Power Index projections say Stanford is slightly more likely to lose than to win on Saturday.Both Alabama and Clemson lose (11 percent likelihood): read more

How Our March Madness Predictions Work

Editor’s note: This article is adapted from previous articles about how our March Madness predictions work.We’ve been issuing probabilistic March Madness forecasts in some form since 2011, when FiveThirtyEight was just a couple of people writing for The New York Times. Initially, we focused on the men’s NCAA Tournament, publishing a table that gave each team’s probability of advancing deep (or not-so-deep) into the tournament. Over the years, we expanded to forecasting the women’s tournament as well. And since 2016, our forecasts have updated live, as games are played. Below are the details on each step that we take — including calculating power ratings for teams, win probabilities for each game and the chance that each remaining team will make it to any given stage of the bracket. Men’s team ratings March Madness Predictions: FiveThirtyEight’s men’s and women’s NCAA Tournament forecasting models calculate the chance of each team reaching each round. See our predictions for 2018 » Our men’s model is principally based on a composite of six computer power ratings:Ken Pomeroy’s ratingsJeff Sagarin’s “predictor” ratingsSonny Moore’s ratingsJoel Sokol’s LRMC ratingsESPN’s Basketball Power IndexFiveThirtyEight’s Elo ratings (described below)Each of these ratings has a strong track record in picking tournament games. We shouldn’t make too much of the differences among them: They are all based on the same basic information — wins and losses, strength of schedule, margin of victory — computed in slightly different ways. We use six systems instead of one, however, because each system has different features and bugs, and blending them helps to smooth out any rough edges. (Those rough edges matter because even small differences can compound over the course of a single-elimination tournament that requires six or seven games to win.)To produce a pre-tournament rating for each team, we combine those computer ratings with a couple of human rankings:The NCAA selection committee’s 68-team “S-curve”Preseason rankings from The Associated Press and the coachesThese rankings have some predictive power — if used in moderation. They make up one-fourth of the rating for each team; the computer systems are three-fourths.It’s not a typo, by the way, to say that we look at preseason rankings. The reason is that a 30- to 35-game regular season isn’t all that large a sample. Preseason rankings provide some estimate of each team’s underlying player and coaching talent. It’s a subjective estimate, but it nevertheless adds some value, based on our research. If a team wasn’t ranked in either the Associated Press or Coaches polls, we estimate its strength using the previous season’s final Sagarin rating, reverted to the mean.To arrive at our FiveThirtyEight power ratings, which are a measure of teams’ current strength on a neutral court and are displayed on our March Madness predictions interactive graphic, we make two adjustments to our pre-tournament ratings.The first is for injuries and player suspensions. We review injury reports and deduct points from teams that have key players out of the lineup. This process might sound arbitrary, but it isn’t: The adjustment is based on Sports-Reference.com’s Win Shares, which estimates the contribution of each player to his team’s record while also adjusting for a team’s strength of schedule. So our program won’t assume a player was a monster just because he was scoring 20 points a game against the likes of Abilene Christian and Austin Peay. The injury adjustment also works in reverse: We review each team to see which are healthier going into the tournament than they were during the regular season.The second adjustment takes place only once the tournament is underway. The FiveThirtyEight model gives a bonus to teams’ ratings as they win games, based on the score of each game and the quality of their opponent. A No. 12 seed that waltzes through its play-in game and then crushes a No. 5 seed may be much more dangerous than it initially appeared; our model accounts for this. On the flip side, a highly rated team that wins but looks wobbly against a lower seed often struggles in the next round, we’ve found.When we forecast individual games, we apply a third and final adjustment to our ratings, for travel distance. Are you not at your best when you fly in from LAX to take an 8 a.m. meeting in Boston? The same is true of college basketball players. In extreme cases (a team playing very near its campus or traveling across the country to play a game), the effect of travel can be tantamount to playing a home or road game, despite being on an ostensibly neutral court. This final adjustment gives us a team’s travel-adjusted power rating, which is then used to calculate their chance of winning that game.Women’s team ratings We calculate power ratings for the women’s tournament in much the same way as we do for the men’s. However, because of the relative lack of data for women’s college basketball — a persistent problem when it comes to women’s sports — the process has a few differences:Three of the six power ratings that we use for the men’s tournament aren’t available for women. Fortunately, that means three of them are: Sagarin’s “predictor” ratings, Sokol’s LRMC ratings and Moore’s ratings. We also use a fourth system, the Massey Ratings.The NCAA doesn’t publish the 68-team S-curve data for the women. So we use the teams’ seeds instead, with the exception of the four No. 1 seeds, which the selection committee does list in order.For the women’s tournament, there isn’t much in the way of injury reports or advanced individual statistics, so we don’t include injury adjustments.Turning power ratings into a forecastOnce we have power ratings for every team, we need to turn them into a forecast — that is, the chance of every team reaching any round of the tournament.Most of our sports forecasts rely on Monte Carlo simulations, but March Madness is different; because the structure of the tournament is a single-elimination bracket, we’re able to directly calculate the chance of teams advancing to a given round.We calculate the chance of any team beating another with the following Elo-derived formula, which is based on the difference between the two teams’ travel-adjusted power ratings:1.01.0+10−travel_adjusted_power_rating_diff∗30.464/4001.01.0+10−travel_adjusted_power_rating_diff∗30.464/400Because a team needs to win only a single game to advance, this formula gives us the chance of a team reaching the next round in the bracket. The probability of a team reaching a future round in the bracket is based on a system of conditional probabilities. In other words, the chance of a team reaching a given round is the chance they reach the previous round, multiplied by their chance of beating any possible opponent in the previous round, weighted by their likelihood of meeting each of those opponents.Live win probabilitiesWhile games are being played, our interactive graphic displays a box for each one that shows updating win probabilities for both teams, as well as the score and the time remaining. These probabilities are derived using logistic regression analysis, which lets us plug the current state of a game into a model to produce the probability that either team will win the game. Specifically, we used play-by-play data from the past five seasons of Division I NCAA basketball to fit a model that incorporates:Time remaining in the gameScore differencePregame win probabilitiesWhich team has possession, with a special adjustment if the team is shooting free throwsThe model doesn’t account for everything, however. If a key player has fouled out of a game, for example, the model doesn’t know, and his or her team’s win probability is probably a bit lower than what we have listed. There are also a few places where the model experiences momentary uncertainty: In the handful of seconds between the moment when a player is fouled and the free throws that follow, for example, we use the team’s average free-throw percentage to adjust its win probability. Still, these probabilities ought to do a reasonably good job of showing which games are competitive and which are essentially over.Also displayed in the box for each game is our “excitement index” (check out the lower-right corner) — that number also updates throughout a game and can give you a sense of when it’ll be most fun to tune in. Loosely based on Brian Burke’s NFL work, the index is a measure of how much each team’s chances of winning have changed over the course of the game.The calculation behind this feature is the average change in win probability per basket scored, weighted by the amount of time remaining in the game. This means that a basket made late in the game has more influence on a game’s excitement index than a basket made near the start of the game. We give additional weight to changes in win probability in overtime. Values range from 0 to 10, although they can exceed 10 in extreme cases.FiveThirtyEight’s Elo ratingsIf you’ve been a FiveThirtyEight reader for really any length of time, you probably know that we’re big fans of Elo ratings. We’ve introduced versions for the NBA and the NFL, among other sports. Using game data from ESPN, Sports-Reference.com and other sources, we’ve also calculated Elo ratings for men’s college basketball teams dating back to the 1950s. Our Elo ratings are one of the six computer rating systems used in each team’s pre-tournament rating.Our methodology for calculating these Elo ratings is very similar to the one we use for the NBA. Elo is a measure of a team’s strength that is based on game-by-game results. The information that Elo relies on to adjust a team’s rating after every game is relatively simple — including the final score and the location of the game. (As we noted earlier, college basketball teams perform significantly worse when they travel a long distance to play a game.)It also takes into account whether the game was played in the NCAA Tournament. We’ve found that historically, there are actually fewer upsets in the tournament than you’d expect from the difference in teams’ Elo ratings, perhaps because the games are played under better and fairer conditions in the tournament than in the regular season. Our Elo ratings account for this and weight tournament games slightly higher than regular-season ones.Because Elo is a running assessment of a team’s talent, at the beginning of each season, a team gets to keep its rating from the end of the previous one, except that we also revert it to the mean. The wrinkle here, compared with our NFL Elo ratings, is that we revert college basketball team ratings to the mean of the conference.And that’s about it! (Congratulations if you made it this far.) While we make no guarantee that you’ll win your pool if you use our system, we think it’s done a pretty good job over the years. Hopefully, you’ll have fun using it to make your picks, and it will add to your enjoyment of both NCAA tournaments. read more

Columbus Crews Robbie Rogers to join Leeds United

Former Columbus Crew midfielder and current United States national soccer team member Robbie Rogers is back to Europe. Rogers joined Leeds United Wednesday after playing the last five seasons with the Crew, and awaits the approval of a work permit to begin playing with the English Championship team. “(Leeds) were interested and they worked it out with my agent,” Rogers told leedsunited.com. “I had the opportunity to stay in Major League Soccer and it would have been very comfortable. My whole life I’ve grown up watching English soccer and European soccer and I really thought now was the time to take the chance and challenge myself. I think I’m ready for it.” The Crew did not respond to The Lantern’s request for comment regarding Rogers’ departure for Leeds. Rogers, who has 18 international appearances for his country and was an MLS Best XI selection in 2008, made his professional debut with Dutch side Heerenveen in 2006 before returning to America and signing with Columbus. Leeds, nicknamed the “Whites,” is currently in eighth place in the English Championship, which is one division below the English Premier League. read more

Mens Basketball Ohio State cant keep up with 3point shooting of No

Ohio State junior guard C.J. Jackson (3) drives to the paint in the first half in the game against Michigan on Dec. 4. Ohio State won 71-62. Credit: Jack Westerheide | Photo EditorIn its search for a signature win, Ohio State (10-4, 2-0 Big Ten) could not contain No. 5 North Carolina’s 3-point shooting, with the Buckeyes falling 86-72 Saturday. The Tar Heels (11-2) finished the game 13-for-25 from beyond the arc and outrebounded the Buckeyes 39-25. Ohio State shot just 44.1 percent (26-for-59) from the field and 31.2 percent from 3-point range (5-for-16). North Carolina’s bench, led by redshirt senior guard Cameron Johnson’s 14 points, outscored Ohio State’s bench 32-6.North Carolina’s 3-point success began early when forward Theo Pinson, guard Joel Berry II and Johnson hit three wide-open triples, the last of which put the Tar Heels ahead 11-8. Pinson and Berry each finished with 19 points. Ohio State junior guard C.J. Jackson tied the game up at 11 with a 3 of his own with 12:05 left. Jackson accounted for Ohio State’s first 11 points, and finished with 19 points. Redshirt junior forward Keita Bates-Diop and freshman center Kaleb Wesson were the only other Buckeyes to finish with double-digit points. Bates-Diop had 26 and Wesson had 12.The Buckeyes kept the game close early, but after the under-eight media timeout, North Carolina freshman guard Jalek Felton took over, knocking down three-straight 3-pointers and dropping in a lay-up. Junior guard Kenny Williams’ 3-pointer also contributed to the Tar Heels’ 14-3 run, which propelled them to a 31-23 lead.The half ended with Ohio State head coach Chris Holtmann picking up a technical foul for arguing with the referees after a blocking foul on Wesson. The Tar Heels made two of the four free throws, capping off a 10-0 run to end the half and go up 41-27. The 14-point halftime deficit was Ohio State’s largest this season.The two teams both exchanged momentum to start the second half, with Ohio State going on a 7-3 run before North Carolina responded with a 7-2 run to go up 51-36. That trend continued for the rest of the game, with North Carolina seemingly matching every Ohio State run with a run of its own. The Buckeyes never managed to trim the deficit within seven for the second half. read more

Mens Hockey No 6 Ohio State splits twogame series with No 13

Ohio State sophomore forward Tanner Laczynski controlls the puck during a 4-0 loss to Penn State on Dec. 2. Credit: Nick Hudak | For the LanternThe No. 6 Ohio State men’s hockey team (15-5-4, 8-5-1-0 Big Ten) split its weekend series against No. 13 Penn State (13-8-3, 6-5-3-2 Big Ten) in State College, Pennsylvania, dropping Friday’s game 5-2 , then rebounding with a 5-1 win the next day.Game OnePenn State sophomore goaltender Peyton Jones made 45 saves on 47 shots in a 5-2 win against Ohio State. The Buckeyes’ loss ended their season-high six-game win streak.Penn State struck early in the opening period when sophomore forward Denis Smirnov fired a shot past Ohio State redshirt junior goaltender Sean Romeo 5:18 in the first period to give the Nittany Lions a 1-0 lead.Later in the period, the Nittany Lions got loose on a two-on-one breakaway. Smirnov feathered a cross-crease pass to sophomore forward Nate Sucese, putting the Penn State up by two goals near the end of the first period. Ohio State mounted multiple fruitful offensive attacks in the second period.Early in the period, the Buckeyes capitalized on a power play. Buckeyes junior forward and captain Mason Jobst put in a rebound off a shot from sophomore forward Tanner Laczynski, making it a one-goal game.Penn State struck back with a power-play goal of its own, when freshman forward Evan Barratt found the back of the net at 7:46 of the second period.The back-and-forth play continued with another power-play goal for the Buckeyes. Jobst showed patience in the slot before sniping it into the top corner of the goal, over the glove of Jones. It was Jobst’s second goal on the power play.Ohio State had 22 shots in the second period, totaling 37 through the opening two periods. Penn State made a push in the third period that began began with the power play. Penn State junior forward Andrew Sturtz skated through the slot, dragged the puck through the Buckeye defense and beat Romeo with a quick shot through the five-hole to restore the two-goal lead.Barratt added an empty-net goal, his second goal and third point of the night, to ice the game for Penn State. Ohio State’s special teams were seemingly at the center of everything that happened Friday night. The Buckeyes went 2-for-4 on the power play, but went 1-for-3 on the penalty kill.Romeo made 31 saves in Ohio State’s loss. Game TwoThe Buckeyes enacted their revenge in the second game, snapping Penn State’s 11-game unbeaten streak in a 5-1 victory.Head coach Steve Rohlik made some drastic changes to the starting lineup before the game, starting freshman goalie Tommy Nappier and removing Jobst from the first line. It was Nappier’s third career start and Big Ten debut.Ohio State capitalized on a turnover early in the first period when junior forward Freddy Gerard found Laczynski on the backdoor for the sophomore’s 11th goal of the season on the backdoor to give the Buckeyes a one-goal lead. After a long shift in the Buckeye zone, Penn State sophomore forward Nikita Pavlychev found the puck through a crowd and beat Nappier between the legs to tie the game at one.Later in the period, a major penalty was called on Sturtz for kneeing Ohio State senior defenseman Janik Moser, giving the Buckeyes a five-minute power-play. Moser did not return to the game. Sophomore forward Ronnie Hein made a backhand pass from his knees to set up Gerard on the far post to score Ohio State’s second goal of the game.  Shots favored Ohio State 14-11, which helped the Buckeyes stake out to a  2-1 lead heading to the second period.The Buckeyes started the second period right where they left off the first, with a power-play goal. Junior forward Dakota Joshua tipped in a shot from sophomore defenseman Gordi Meyer to give Ohio State its second power-play goal and a 3-1 lead. Shortly after, Penn State senior forward James Robinson had a breakaway chance as he burst out behind the Ohio State defense, was hooked and awarded a penalty shot. Nappier made the save on the Penn State captain to keep the two-goal lead entering the third period.The third period was all Buckeyes, who added two goals late in the period to seal the victory.Gerard and Laczynski both finished with three points in the win. Nappier was solid, making 30 saves on 31 shots, while Jones made 33 saves on 37 shots in the losing effort.The Buckeyes will have next week off before hosting arch-rival Michigan for a two-game weekend series, which begins at 7 p.m. Jan. 26. Both games will be held at the Schottenstein Center. read more