By just about any measure, the last three seasons have been the best time to root for the Toronto Raptors in their 20-year history. The Vince Carter era was thrilling but brief, and Chris Bosh’s dinos never quite realized their potential. Since 2013-14, however, the Raptors’ winning percentage has hovered around 60 percent, and their efficiency differential has been roughly 3.5 points per 100 possessions — numbers that those previous runs only approached in spurts.For all that success, however, Toronto has had trouble making any kind of dent come playoff time. As my ESPN colleague Zach Lowe wrote about Tuesday, each of the team’s past two postseasons ended with a first-round exit, and although the Raptors were upset both times — implying they had the talent to potentially go further — 49-win teams don’t typically vie for NBA championships anyway.1There are rare exceptions, but even conditional on making it past the first round of the playoffs, only 13 percent of teams that won 48 to 50 games in a season went on to the NBA Finals. If this season’s version of the club is basically the same, expecting different results would be irrational.These Raptors, however, have a secret weapon that their predecessors lacked: skinny Kyle Lowry.Technically speaking, this is Lowry’s fourth season with Toronto; he even logged the second-most minutes of any Raptor during the failed playoff runs of 2014 and 2015. But that version of Lowry was — how can we say it? — less svelte, and far less productive. By Box Plus/Minus (BPM), Lowry’s 2014-15 season was the worst he’d had in four years. This season, though, Lowry profiles like a top-five player according to the advanced metrics. And his sudden improvement could finally give Toronto the star power necessary to truly compete for a championship.Lowry’s evolving gameBefore this season, Lowry appeared to be on an evolutionary arc many players go through, trading a higher usage rate for less efficient scoring. In his rise as one of the game’s best guards, he’d once ranked in at least the 70th percentile of NBA players in both true shooting percentage and usage. That isn’t an easy thing to do. But last season, Lowry seemed to have surpassed the workload at which he could maintain a reasonable level of efficiency — a situation exacerbated by the banged-up state he found himself in as the season progressed. As a result, his offensive numbers dipped: He settled for more midrange shots and drew fewer fouls; he ran the pick-and-roll less often (and less efficiently); and over the course of the season, he struggled with his jump shot in a way he hadn’t for years.Although Lowry was pretty clearly not being himself, the Raptors won the Atlantic Division and locked up the No. 4 seed in the East. But the team was also unceremoniously swept by Washington, a series in which Lowry kept a high usage but saw his efficiency completely collapse. This seemed like a bad sign.Perhaps even more troubling, it was getting harder to find evidence that Lowry — a player with a good two-way reputation — was still among the league’s best defensive guards. Going into last season, he’d ranked up around the 80th percentile of NBA guards in defensive BPM over his career — a ranking corroborated by play-by-play plus/minus metrics and tracking data from Synergy Sports Technology — numbers underpinned by smart, bruising pick-and-roll defense. But in 2014-15, Lowry’s defensive indicators offered mixed messages. Although he still gave the Raptors’ defense a boost while on the floor, the team was also significantly worse defensively than it had been the previous season, and Lowry often looked slow, clunky and, at times, indifferent when trying to fight through ball screens. So this season should be encouraging for Raptors fans, at least by this metric. But after years of watching Chris Paul-led teams underachieve in the playoffs, it’s fair to ask whether this algorithm oversells the title chances for a point guard-driven squad. And as it happens, controlling for the entire skill set of a team’s best player, we found a slight tendency for teams led by players with a lot of value tied up in passing to perform worse in the postseason than we’d expect from their BPM. This could be due to any number of causes — from defenses keying in on passing patterns in a long playoff series to the way a playmaker’s value is only maximized when complemented by other skills (or perhaps it’s just random noise) — but it’s one (albeit minor) reason to consider lowering expectations for Lowry.Except that this season, Lowry’s game has been extremely well-rounded — he ranks in at least the 78th percentile of all NBA players in scoring efficiency, possession usage, assist rate and defensive BPM. Historically, teams whose best players excel in the first and last of those categories tend to exceed expectations in the playoffs at a rate far greater than any penalty that’s levied against passers.Of course, all of this presumes that Lowry’s overhauled game is legit. He’s currently 29 years old, an age at which NBA players are typically already on the downside of their careers, not metamorphosing into championship-caliber stars. Also, there was little in Lowry’s preseason CARMELO projection (our statistical crystal ball for NBA careers) to suggest an imminent breakout, aside from the late-blooming presence of Steve Nash on the fringe of his comparables list. An optimistic look at his strongest CARMELO comps suggested that he might pull a Rod Strickland and stay productive into his mid-30s; a less rosy one saw the possibility of flaming out far sooner, like Michael Adams and Derek Harper. So it’s entirely possible that Lowry will regress toward his previous career norms in the season’s second half.But given the particulars of Lowry’s skill set, and the ways in which he’s corrected his deficiencies of a season ago, it’s also very possible that if his caloric intake doesn’t regress, neither will his output.The question of whether Lowry’s teammates are good enough to support a championship run is still very much open. And even if they are, Lowry may have timed his improvement poorly, elevating his play during a season with two abnormally dominant teams that are soaking up all the league’s title odds. But Lowry’s sudden upgrade to the NBA’s elite class of players gives the Raptors a superstar the likes of which they’ve never had before. At the very least, they now possess a crucial element that was missing from the team’s recent string of good-but-not-good-enough campaigns. The new, slimmed-down version of Lowry has been quicker afoot and more focused in his pursuit of ballhandlers around and through screens, forcing more turnovers and fouling less as a result.2015-16: It’s likely no coincidence that Toronto’s opponents are scoring at a rate of nearly 4 fewer points per 100 possessions with Lowry on the court than they did a season ago. In fact, Lowry’s rehabilitation has been so complete that the Raptors now rank among the league’s top 10 teams at both ends of the floor and he has risen to full-blown MVP candidate status.You’re only as good as your best playerIt’s no secret that there’s a distinct relationship between a team’s championship probability and the quality of its best player, but it takes a truly exceptional player to make a run at a title. In the past, Lowry hasn’t been good enough to move that needle, but this season’s version is inching into the territory where small individual improvements can drastically upgrade a team’s chances of winning a championship.We’d expect a team being led by Lowry at his previous career-high BPM of +5.9 to win the title about 5 percent of the time; at this season’s +7.2 mark, those odds are doubled, to 10 percent. (Not even Carter in his prime led Toronto with a BPM so high.) Add in a decent supporting cast — and it’s debatable as to whether Toronto has one of those, particularly with DeMarre Carroll on ice, but let’s entertain the notion anyway — and suddenly the idea of a championship parade down Bay Street doesn’t seem quite so pie-in-the-sky. This season, Lowry has made course corrections at both ends of the floor. Although his usage continues to grow, his scoring efficiency has bounced back, in part because of smarter shot selection. He’s once again devoting fewer shots to the midrange, allowing his rates of taking threes and drawing fouls to return to their historical norms, and he’s been faster and more aggressive in the transition game as well. On defense, you can really see the effects of Lowry’s offseason weight loss. Last season, Lowry frequently failed when trying to use his strength to fight through screens (both on the ball and off), ceded too many easy buckets on pick-and-rolls and was generally slow to recover when he guessed wrong or his gambles didn’t pay off.2014-15:
By Jody Avirgan As you’re watching the Super Bowl this weekend, keep in mind that behind the scenes, loads of data — and money — is shifting with each and every play. And as real-time data plays a bigger and bigger role in big-time sports, there are more opportunities for corruption.On this week’s episode of our podcast What’s The Point, James Glanz of The New York Times discusses his reporting on high-speed data in sports, as well as his investigations into daily fantasy sports. To listen, stream or download the full episode above, or subscribe using your favorite podcast app.Glanz also reveals that over the course of his reporting, he uncovered that the government routinely finds the names of active professional athletes when it takes down gambling rings. Video and a transcript of that part of the conversation are below.Are pro athletes gambling?Jody Avirgan: In the last couple years, you hear NFL players talk more explicitly about the fact that they know people have them in fantasy sports and their performance is linked to this proxy game or gambling that’s happening. Does it worry you that players are aware of all this other stuff that’s happening around them?James Glanz: Yeah. Yeah, it does. In reporting this story, integrity monitors are some of the people I spoke with — we didn’t do a lot about that — but what I hear from them is that unfortunately, even when [sports leagues] are working privately with integrity monitors, it’s not in any of the sports’ interest to really publicize the cases that they actually find. For example, here’s something I’ll give you that we didn’t put into the series.Avirgan: Are you about to out a player?Glanz: I’m not going to out a player, but in the United States betting organizations get taken down, prosecuted — sometimes severely if they’re convicted of money laundering and things like that, which is the usual charge — but prosecutors do not go after individual bettors, but they often know who they are. And in ring after ring, in this country, active players are constantly caught up in these dragnets that become criminal prosecutions, but because the players are generally just betting, they’re never named.What exactly is data?Avirgan: Over the course of all your reporting, did you land somewhere in terms of how our law should think of what the Internet is — or what data is?Glanz: I guess I’d turn it around. The Internet doesn’t rule the world. We’re in a nation of laws, and we have to actually change those laws if we want to operate under a different set of operating principles. The Internet calls some of that into question, but in some cases it just takes advantage of people’s ignorance about the way the whole system works — I’m talking about the digital system. So, if you’re running an illegal casino in Chelsea, you’re going to have to own up to it; that’s just the way it works.Avirgan: But you’re OK with the fact that it’s illegal in Chelsea, but it’s legal in Malta or some Caribbean island?Glanz: Well, I can’t really help what happens in Malta. I guess the way I’d put it is, that if you’re going to set up your casino in Chelsea, then put a sign out front. Because if what you’re doing is relying on law enforcement’s ignorance about the Internet, I can tell you, the house isn’t going to stand forever, because they’re going to figure that out — and they partly did from our series. That’s an inconvenient fact. Data is like all the rest of us, it exists in a physical place, and you have to take that into account. That’s just the way it is.Avirgan: What’s next in your reporting?Glanz: I’m not sure. I think that networking, and I’m talking about this in a very technical sense, is something that now weaves through all of our lives and affects almost every professional area in the United States as well as our personal lives and very few people understand. I’ve just started to get close to how complicated it is, but also how weirdly understandable it is. I’ll probably find another topic that kind of takes me through that world, and I’ll end up again in these places where you’re looking around and you think you’re in the belly of a submarine, but it’s really “the cloud.” I sort of like those places. More: Apple Podcasts | ESPN App | RSS | Embed “After a goal is scored, the result is transmitted to a server in Malta and shows up on a screen, before people in the stadium even jump up and scream.” Read more: “Inside the Shadowy World of High-Speed Tennis Betting” Embed Code If you’re a fan of What’s The Point, subscribe on Apple Podcasts, and please leave a rating/review — that helps spread the word to other listeners. And be sure to check out our sports show Hot Takedown as well. Have something to say about this episode, or have an idea for a future show? Get in touch by email, on Twitter, or in the comments.What’s The Point’s music was composed by Hrishikesh Hirway, host of the “Song Exploder” podcast. Download our theme music.
Villanova693110.04.5 Iowa State81196.83.1 Michigan State564211.24.8 Baylor70306.16.1 West Virginia59418.17.6 Wichita State54468.63.2 Maryland72287.63.0 SMU74267.55.4 Iowa70306.85.4 Embed Code Kentucky71297.85.7 Arizona64367.65.4 Oklahoma76249.21.1 Virginia68329.86.0 Louisville66348.76.5 Xavier65357.35.2 Duke79217.45.8 Vanderbilt67336.95.4 Sources: Sports Reference, Ian Levy More: Apple Podcasts | ESPN App | RSS | Embed UConn70306.04.9 Kansas70%30%8.78.2 Indiana63377.56.9 What distinguishes Xavier’s 1-3-1 from historical 1-3-1s like Baylor’s or Michigan’s (during John Beilein’s early years), though, is Mack’s use of two bigs — one in the middle and another on the baseline. Typically, a guard runs along the baseline of a 1-3-1, having the requisite speed to close out on short corner threes. But Xavier’s bigs — James Farr and Jalen Reynolds — are both quick for their position and also help XU rebound out of the zone defense (Xavier allowed opponents a 26.3 percent offensive rebounding rate), which is a traditional weakness of the formation. Some teams, like Seton Hall in the Big East tournament, have begun to figure out the scheme after playing Xavier a second time, but that’s not much comfort for teams getting their first taste this month.Hampton, Green Bay and Buffalo’s tempoBefore this season, the NCAA trimmed the Division I shot clock from 35 seconds to 30. Naturally, tempo has risen a bit — the average number of possessions in 2016 has been 69, per Ken Pomeroy, an uptick from 64.8 a season ago. The conventional wisdom is that this is bad news for underdogs — that weaker teams are best served by slowing down the game and pumping up the variance — but there are a few lower-seeded teams in this year’s field that push the ball anyway.The first is No. 16 Hampton (72.2 possessions per 40 minutes), which will face No. 1 Virginia (61.4 possessions) in the Midwest region. This is the largest difference between teams matched up in the first round. There is virtually no chance that the MEAC auto bid winners will be able to speed up and disrupt the methodical style of Tony Bennett’s squad enough to pull off a win (the FiveThirtyEight model gives Hampton a 2 percent chance of advancing).Another fast-moving team among the lower seeds is No. 14 Green Bay (76.6), which will play No. 3 Texas A&M (67.5). That matchup has the second-biggest difference in tempo, at 9.1 possessions per 40 minutes. Our model gives the Phoenix a 12 percent chance to pull the upset. Under new head coach Linc Darner, who came to the Horizon League school from a Division II program, the Phoenix went into overdrive and underwent a huge transformation, with 11.2 possessions more per 40 minutes than last season.Then there’s 14th-seeded Buffalo, which has a 14 percent chance of knocking off No. 3 Miami. Nate Oats became head coach at Buffalo when Bobby Hurley left for Arizona State, and Buffalo quickened its pace from 68.8 to 73.0. The margin between the Bulls’ pace and Miami’s 66.8 possessions per 40 minutes is 6.2.West Virginia’s benchFew teams in Division I rely on their bench as much as West Virginia. The No. 3 seed Mountaineers allot 41 percent2Data via Sports Reference with additional research by Ian Levy. of their overall minutes to reserves, which ranks 18th nationally and third among tournament teams. But WVU’s bench is unique because it isn’t just heavily utilized, it outperforms other units by a wide margin — even other teams’ starting lineups.Ian Levy of Nylon Calculus broke down the bench Box Plus/Minus of the top 30 squads in Pomeroy’s rankings, and the West Virginia bench’s BPM of +7.6 is better than that of every team’s except for Kansas’s (+8.2), but the Jayhawks don’t use their bench nearly as much as WVU (just 30 percent of their minutes). Among tournament teams that use their bench more often than WVU — Michigan State and Wichita State — the Mountaineers’ bench play is more valuable by a wide margin. (The bench BPMs for those two teams are +4.8 and +3.2, respectively.) Bob Huggins’s bench also outperforms 17 top-30 starting lineups, including No. 1 seed Oregon (+6.6) and No. 2 seed Xavier (+7.3). Texas62386.54.1 California69316.74.1 Utah71296.84.4 TEAMTOP 5 SHARE PLAYING TIMEBENCH SHARE PLAYING TIMETOP 5 BPMBENCH BPM Oregon74266.64.5 Texas A&M70306.85.4 Gonzaga76246.82.7 Our sports podcast Hot Takedown previews March Madness. North Carolina65359.15.3 By Matt Giles The catalyst is the play of both Jaysean Paige and Jonathan Holton, two Mountaineers who could start but thrive coming off the bench. Holton, a 6-foot-7 big, uses 51 percent of the team’s minutes and is nearly impossible to keep off the offensive glass, grabbing 17.1 percent of WVU’s misses — more than a quarter of his field goal attempts are putbacks, and he is second on the squad at field-goal percentage at the rim.Paige is West Virginia’s X-factor. Despite using only 56 percent of WVU’s minutes, Paige attempts 31.8 percent of the Mountaineers’ shots when he’s on the floor, and when he checks into the game, the Mountaineers often see an improvement, since he frequently subs for Daxter Miles, a 6-foot-3 guard with a BPM of +7 (Paige’s BPM is +10).North Carolina’s small ballRoy Williams loves his bigs. Throughout his career, the North Carolina coach has almost always played two traditional forwards at the same time. “I like to play two big guys, because I still think defending around the rim and grabbing rebounds are big parts of the game,” he told The New York Times earlier this season. But Williams’s thinking is beginning to align with the small ball revolution.It’s a good time for the change, since UNC’s roster is suited for small ball. Both Theo Pinson and Justin Jackson are mismatches at their respective positions of the 3 and the 4, and Pinson can help guard 4s while Jackson has the speed and the length (6-foot-8) to disrupt the offensive rhythm of 3s. During early ACC play, Williams began to dip his toe into the small ball waters, and the results were promising; per Adrian Atkinson, who specializes in crunching data for all things Tar Heel blue, UNC’s net efficiency was +43.1 in 39 minutes for the first five conference games.But then Kennedy Meeks returned from a knee injury, and Williams reverted back to his traditional lineups: UNC’s small ball lineups played only 50 minutes for the next 12 ACC games. In the final three games of ACC play, that net efficiency spiked to +55.1. Williams may only exploit this mismatch in small doses, but it is an interesting wrinkle for a coach with national title aspirations and a long-held two-post belief system.Kentucky’s adaptabilityKentucky is the field’s most dangerous seed that is not a No. 1 or 2. The No. 4 seed in the East region has potential matchups against Indiana, North Carolina and West Virginia, but outside of a handful of squads, there aren’t many teams in the tournament playing as well as the Wildcats. Kentucky has won 10 of their last 12 games, including the SEC tournament title.John Calipari has done his usual lineup juggling act this season, but it got particularly interesting after forward Alex Poythress injured his right knee and was sidelined for five games. In Poythress’s absence, Calipari slotted in Derek Willis, a stretch 4 whose skills combined well with the pick-and-pop game of Tyler Ulis, and UK’s offensive efficiency rate went from 1.11 points per possession pre-injury to 1.14 — unusual for a team that loses one of its best players. The team upped its rate of 3-point field goal attempts (from 30.2 percent to 37.4 percent) and began converting a whopping 49.1 percent of their threes. Poythress’s absence opened the half court for penetration and kick-outs, and while the squad didn’t defend at the level that we expect from Calipari-coached teams (UK began hacking opponents, notching a defensive free throw rate of 46 percent), its offense more than compensated.But then Poythress returned, and questions surfaced about how Kentucky would adjust with its sole traditional post player back in the lineup. The team adapted. Skal Labissiere began to play more on the elbow and above the free-throw line, which allowed for potential high-lows. The 1.05 PPP the Kentucky defense allowed in the seven games with a healthy Poythress is below the typical Calipari team’s standard, but we’ve learned that Kentucky’s offense is perhaps the best ever during the Calipari era: 1.25 PPP in 66 possessions.The team is hitting a similar percentage of threes (45 percent), and even Poythress is contributing to the 3-point-fueled offense; he’s taken seven of his 23 threes for the season since returning. Compared with the efficiency margins posted by other high major teams at the end of conference play, Kentucky’s +.20 efficiency margin would top every other squad. Purdue61397.96.8 A large part of enjoying the NCAA Tournament is about grinding your friends’ and family’s brackets into paste. For that, there are our March Madness predictions. Some other sizable portion of the tournament’s fun, though, is wrapped up in the diverse cast of teams assembled to play for the national title. The college game, much more so than the pros, is still home to quirks and oddities that can power a team to a few unexpected tournament wins. Here are five (or so) teams, and their statistical idiosyncrasies, to look out for this March.Xavier’s 1-3-1 zoneThe 1-3-1 is not a popular defense. Its spatial concepts are difficult to teach (players form an elongated plus sign in the defensive half court), and the formation is prone to imbalance if an opponent gets hot from the wing, which is easy to probe either for 3-point attempts, drives and backdoor lobs. But when a team is comfortable with the 1-3-1, the defense can be one of the most potent change-ups in the college game. Baylor used the 1-3-1 to advance to the Elite Eight in 2010, and Xavier is attempting a similar run this March.For the season, 33.6 percent of the Musketeers’ defensive possessions have featured the 1-3-1.1I went through each of the defensive possessions in which Xavier played zone using Synergy Sports Technology’s video tools and verified that all of the Musketeers’ zone plays came out of the 1-3-1. Last season, just 13 percent did. The only Division I team to rely on any zone more often this season has been Cincinnati (which uses the 2-3 variety); Xavier has used the 1-3-1 for 759 possessions, allowing just 0.797 points per defensive trip. Chris Mack doesn’t stray too far from his man-to-man roots with the base defense, but his personnel at XU is suited to making the 1-3-1 work. J.P. Macura, a wiry and lanky wing, has long arms atop the zone that can disrupt the vision of opposing guards, and Edmond Sumner and Trevon Bluiett — both long for their respective positions — are adroitly positioned at the wings to help trap and further obscure passing lanes and shot attempts. Miami69317.55.8 Seton Hall73276.61.3
The gap between the best home run hitters in the league and the average was never wider than in 1998, the midpoint of the PED era in terms of average hitter age, according to our definition above. Looking at the list of hitters that year, it’s not hard to tell why: Three of the top five hitters in home runs per plate appearance (minimum 300 PAs) were Mark McGwire, Sammy Sosa and Jose Canseco, all of whom later admitted or were alleged to have used PEDs. The second largest gap occurs in 2001, and features Bonds, McGwire and Sosa at the top of the list.Meanwhile, contemporary HR rates for the best hitters have increased in lockstep with the MLB average. The difference between the top five current hitters’ HR/PA and the average in the last two years has been about the same as the norm across MLB’s history.5Specifically, the top five from 2015 ranked in the 55th percentile of all years, and 2016 ranks in the 25th percentile. And while the rate of HR/PA across the league has never been higher than today, the rate of the top five lags far behind that of the steroid era. MLB’s recent offensive explosion has seen the average hitter perform significantly better without creating a new wave of outliers.That extraordinary evenness with which MLB’s latest HR surge has affected all players is maybe the best reason to discard the steroid explanation. The start of the steroid era was associated with a massive jump in home runs, but it affected some hitters more than others. Even most steroid users didn’t turn into musclebound hulks, but for those who did, the results were sometimes extraordinary. The recent offensive surge, on the other hand, has been both sudden and uniform across the league, resembling previous times in MLB’s history when the ball changed. Although historical comparisons like this cannot definitively prove that the ball is different now, they do suggest that whatever is causing the ball to fly farther is affecting all hitters equally.Check out our latest MLB predictions. Most historical instances of the ball changing were accompanied by rather dramatic shifts in HR/PA, which helps confirm that the makeup of the baseball can indeed influence power rates.1It’s worth noting that many of the largest jumps had dips immediately preceding them, suggesting either efforts by MLB to correct the ball’s performance or simple regression to the mean. And 2016 currently holds the second-largest two-year shift in HR/PA since 1901. Then again, the largest change came in 1994, at the very beginning of the steroid era. (It’s impossible to precisely date the onset of PEDs in the game, but the massive increase in home runs, coupled with changes in the productivity of older hitters and an increase in outlier seasons at the same time, suggests that 1994 is as reasonable a guess for its beginning as any.)2Also, both 1994 and 2016 may have slightly elevated HR rates due to our data not including September, when home runs tend to be slightly less frequent. Even so, the addition of September would be expected to change the home run frequency by less than 1 percent, so any adjustment wouldn’t meaningfully affect the results. But although that means PEDs could also explain the current offensive leap, the start of the steroid era came with a number of other statistical changes that aren’t being repeated in 2015 and 2016.In addition to the dramatic rise in home runs per plate appearance, one of the hallmarks of the PED era was a jump in the average age of hitters. Instead of withering away, many older hitters remained productive into their late 30s and early 40s, in some cases putting up their best seasons toward the end of their careers. (We’re looking at you, Barry.) MLB’s average plate appearance-weighted age in 2005 was 29.3, the second-highest history behind 1945, when many young would-be players were at war. Most of the top 10 years for weighted player age, whether you weight by wins above replacement or by plate appearances, are either within the steroid era or around World War II.By contrast, the average age of hitters hasn’t undergone much of an increase between 2014 and 2016. If anything, it’s gone down: last year featured the lowest WAR-weighted age since 1990, and while that number has ticked upward slightly in 2016, it’s still only level with 2013 and below 2014.3 Probably some of the blame for the year-over-year increase lies with the slowing pace of MLB games, a factor which disproportionately aids older hitters. The 1994 season, which saw the largest jump in HR/PA, also saw a 0.75-year increase in WAR-weighted age relative to 1992. At least so far, there has been no significant increase in older players’ value as there was in the steroid era.Finally, we can look at parity between players, since one of the PED era’s defining features was the profound imbalance between the chemically-altered juggernauts like Barry Bonds and the average player. Not only did the rate of home runs increase across the league, but the top players in particular saw their dingers increase by an astounding degree. Record-breaking outlier seasons, like the famous 1998 single-season home run chase between Sammy Sosa and Mark McGwire, became almost common. Roger Maris’s all-time record of 61 homers, which had stood for 37 years, was exceeded six times from 1998-2001.To measure this outlier effect in the steroid era, I calculated HR/PA for the top five home-run hitters in baseball each season.4There’s nothing special about the top five, but I got similar results when I used the top 10, 15, 20 and 25 hitters each year. I’m not necessarily assuming that all of the top five were PED-users, but if there were artificially-enhanced players in the top five, they acted to drive the highest HR/PA rates even higher. Ever since the steroid era, baseball fans have been cautious about reading too much into unexpected leaps in player performance. Today’s jaded rooters assume that performance-enhancing drugs are to blame, somehow, whenever a player experiences a breakout or the league undergoes a transformation. So it’s no surprise that, with home runs flying out of parks at nearly an all-time high in 2016, many have reacted by assigning the responsibility to some undetectable new PED.After exhaustive consideration, my former FiveThirtyEight colleague Ben Lindbergh and I concluded that the most likely culprit for 2016’s home run explosion is a change to the construction of the ball. Still, given MLB’s lengthy history with PEDs, I thought it was worth revisiting whether a chemical explanation could possibly shed light on the most recent offensive uptick. And there are some similarities between the steroid era and the present — but 2016’s home run explosion is also missing a few key characteristics that defined the steroid era.One of main reasons PEDs seem an unlikely explanation for baseball’s recent offensive surge is the suddenness with which home runs increased. The league’s rate of homers per game began climbing around the 2015 All-Star break, and this year it’s risen more than 30 percent compared with 2014. In theory, PEDs make their way into the game slowly, with knowledge being passed between players over the course of years, but changes to the game’s equipment could drive a more rapid increase. A new supply of slightly altered game balls would affect all players in the league at once, so even a small modification to the ball’s properties could produce a massive statistical change across MLB. Given the quick, drastic shift we’ve seen in home run rates, a change to the ball appears to require fewer leaps in logic: players take time to become juiced, but balls can become juiced immediately.To further investigate whether the ball — and not PEDs — explains MLB’s quick home run increase these past two seasons, I compared the steroid era with a handful of other times in history when the ball’s construction is known to have changed. Although the build of the modern ball has been nominally consistent since 1976, MLB has an extensive history of openly altering the ball in earlier epochs. The first alteration in baseball’s modern era (since 1901) was the introduction of the cork-core ball in 1910, after which the league’s batting average jumped 17 points. In 1943, wartime rubber shortages forced manufacturers to make baseballs with a substitute called balata, which had different elastic properties. Runs per game fell that season by 0.17, before rebounding by 0.26 runs per game in 1945, when the balls reverted to rubber cores. And in 1974, the surface of the ball changed from horsehide to cowhide, without much discernible impact on the league’s overall statistics.In addition to the times in MLB’s history in which the league has admitted to altering the ball, conspiracy theorists have posited numerous other instances in which the league may have modified the sphere in secret. Perhaps the most intriguing parallel to the current home-run increase came in the late 1980s, when Rawlings, MLB’s official baseball manufacturer, shifted production from Haiti to Costa Rica after the collapse of Haitian dictator Jean-Claude Duvalier’s regime. From 1988 to 1990, baseballs were produced in both countries before the Costa Rican facility took over completely. Over that period, slugging percentage immediately fell by nearly 40 points, taking seven years to creep back back toward its 1987 level. This production switch is especially intriguing because of shake-ups at Rawlings in the middle of 2015: although it didn’t change where the balls are manufactured, it did move part of its factory operations and laid off 200 employees.To get a better sense of whether MLB’s current offensive spike more closely resembles the steroid era or one of the times the ball changed, I charted home runs per plate appearance around a few of the historical instances of known ball-tinkering, as well as the midpoint of the steroid era.
Photo by USA Today.For all the disappointment in Miami and excitement in Cleveland that LeBron James changed teams last summer, it is the Heat that have the most to smile about at this early stage of the season.Luol Deng, who was ripped by Atlanta Hawks general manager as “having a little African in him” and being a locker room weak link, has stepped in nicely in James’ place. He’s been a steady influence in his demeanor and his play has been solid, culminating with his best performance in the team’s biggest win of the season in Dallas.Deng lit up the high-flying Mavericks for 30 points on 13 of 19 shooting with four assists Sunday in Miami’s impressive 105-96 victory. He also shut down Dallas’ key offseason acquisition, Chandler Parsons, holding him to just four points on 2-for-20 shooting.LeBron who?”We still have a lot to figure out,” Deng said. ”Their game plan today, they doubled Bosh and D-Wade, and we did a good job of moving the ball and had a lot of open jumpers.”Chris Bosh stayed with the Heat after James departed to Cleveland and is more of a featured player than in the four years with James at the helm. He had 20 points, 10 rebounds and 5 assists in his hometown. Dwyane Wade, James’ old sidekick, had 10 assists and seems to enjoy again being the team’s top player.The win in Dallas was “our best win of the year so far,” Wade said.They took down the Mavericks in Miami’s sixth game in nine nights, on the road. They are 5-2 and second in the Eastern Conference, while James’ Cavaliers are wallowing at 2-3, ninth place in the conference.It stands to reason that James, Kevin Love and Kyrie Irving will find a rhythm and end up being the stellar team that most pundits expected when the consensus best player left Miami to return to his home state.But for now, Miami seems as if it has the goods to be better than expected. Maybe the Heat will not fall apart without James. Maybe Eric Spolestra can coach. And maybe Cleveland and Miami will face each other in the playoffs. That would be worth watching.
YouTubeBrian Davis, a play-by-play announcer for the NBA’s Oklahoma City Thunder, has been suspended for saying Russell Westbrook was “out of his cotton pickin’ mind” during a game against the Memphis Grizzlies this week. He’ll be forced to miss the first game of the Thunder playoff series against the Utah Jazz, which starts on Sunday, April 15.Shortly after the remark was made, Twitter exploded and a Thunder spokesperson called the words “offensive and inappropriate.”Davis released a statement as well and said he understands the punishment but meant no harm.“It is with great remorse and humility that I accept this suspension for the insensitive words I used during Wednesday’s broadcast,” he wrote. “While unintentional, I understand and acknowledge the gravity of the situation. I offer my sincere apology and realize that, while I committed a lapse in judgement, such mistakes come with consequences. This is an appropriate consequence for my actions.”The announcer made the comment during the second quarter of the game, right before Westbrook became the first player to average a triple-double in multiple seasons. When all was said and done, he ended up with six points, 19 assists and 20 rebounds.Besides the statement, Davis also apologized on Twitter and most said they accepted his apology.During Wednesday’s Thunder broadcast, I used a phrase on the air that was ill-considered, insensitive and hurtful. I’m beyond sorry about it and apologize, without reservation, from the bottom of my heart.— Brian Davis (@TrueBDokc) April 13, 2018
Mookie Betts413995.1 For a righty power hitter on the Red Sox, it’s pretty unheard of for only 22 percent of his Fenway home runs to sail over the Green Monster. Going back to 2009,1The earliest season of statistics available in ESPN’s Stats & Information Group’s database. 385 of the 456 homers hit by right-handed Red Sox hitters were sent over the Monster, good for a rate of 84 percent. That number was slightly lower (81 percent) for visiting righty hitters at Fenway, which perhaps speaks to the aforementioned strategy of Boston seeking out pull-happy right-handed sluggers. But it’s also much higher than the 75 percent rate of righty homers to the same left and left-center area at every other park, which is further evidence that the Monster attracts long balls from pretty much all righty hitters — except, apparently, J.D. Martinez.And some of Boston’s most prolific home run hitters went to left even more than the overall Red Sox average. Adrian Beltre hit 11 of his 13 Fenway homers (85 percent) toward the Green Monster during his sole season in Boston. Dustin Pedroia, who’s hit more homers at Fenway than any other righty since 2009, launched 88 percent of his Fenway homers to left in that span. (Incidentally, Martinez already has as many non-Monster home runs at Fenway as Pedroia has tallied there since ’09.) Betts and fellow righty Xander Bogaerts have combined for 72 career home runs at Fenway, and only four of those blasts (two apiece) weren’t over the Monster.Even David Ortiz, a lefty with such a reputation for pulling the ball that he faced constant infield shifts, hit 21 percent of his Fenway homers from 2009 to 2016 over the Green Monster. In that context, Martinez’s 22 percent figure is downright stupefying. Adrian Beltre131184.6 Home runs Bill Hall8787.5 Jonny Gomes9888.9 Mike Lowell151493.3 Marco Scutaro99100.0 Kevin Youkilis322681.3 Xander Bogaerts312993.5 Mike Napoli261869.2 Hanley Ramirez392769.2 Martinez isn’t making much use of the Monster yetShare of right-handed Red Sox batters’ home runs that went over the Green Monster at Fenway Park, 2009-18 PlayerTotalOver Green MonsterShare of Total All Red Sox RHBs45638584.4 Dustin Pedroia605388.3% Obviously, it’s still quite early in Martinez’s Boston career; he’s only logged 22 games at Fenway Park as a member of the home team thus far. (And he didn’t hit any home runs at Fenway in the seven games he played as a member of the visiting Detroit Tigers.) It probably won’t be long before he finds himself crushing a ball or two out onto Lansdowne Street.But by the same token, Martinez will probably never rival Betts or Pedroia in terms of his tendency to go over the Green Monster. Even before this season, Martinez was the game’s pre-eminent opposite-field power hitter; from 2014 to 2017, he led all MLB batters (righty or lefty) in home runs hit the other way, with 37 opposite-field shots. (No. 2 was fellow righty Miguel Cabrera, at 30; no lefty had more than Chris Davis’s 20.) And that represents a pretty big change in the archetype for a right-handed Red Sox slugger — one who’ll make use of the entirety of Fenway’s peculiar dimensions, rather than always just taking aim at the enticingly close wall in left field.Going to right will, no doubt, ultimately cost him some home runs, as Boston features one of the majors’ deepest right-field power alleys. But it hasn’t seemed to matter yet, at least not the way Martinez is swinging the bat right now. More so than perhaps any other team, the Red Sox have always coveted righty power bats who pull the ball; it’s about time they had one who spreads his souvenirs around to the rest of the park. When the Boston Red Sox signed free agent slugger J.D. Martinez this past offseason, it looked like a match made in baseball heaven. As a right-handed power hitter who’d recently embraced MLB’s fly-ball revolution — to great effect — Martinez fit perfectly into one of the Sox’s longest-standing narratives for building around the quirks of Fenway Park: that the team needs righty mashers to take advantage of the short 310-foot distance to the Green Monster in left field. It’s a strategy that, at times, Boston has been guilty of obsessing over too much — but it still holds a certain logic, given that about half of all home runs at Fenway are hit to left field by right-handed batters.So with Martinez currently sitting one home run behind teammate (and fellow righty) Mookie Betts for the major league lead in dingers, you might think it’s just another case of marital bliss between a right-handed slugger and his favorite 37-foot-tall green fence. Except Martinez has barely taken advantage of Fenway’s looming left-field wall so far. He’s only hit three of his 15 total homers this season to left, period, and only two have been at home. Compare that with the seven dingers he’s hit to the other sectors of Fenway Park, including this one he tucked around the Pesky Pole in right field on Sunday: Mike Aviles9888.9 Jason Bay151173.3 Cody Ross131292.3 Batters listed by name had a minimum of eight home runs at Fenway. Totals for all right-handed Red Sox batters include players not listed here.Source: ESPN Stats & Information Group J.D. Martinez9222.2 Will Middlebrooks141285.7 Darnell McDonald8787.5 Jason Varitek9888.9
Seasons with Klopp 2015-16 only includes games when Klopp was manager.Source: Opta Sports In the round of 16, Liverpool got to face Porto and avoid a match against Real Madrid or Juventus. This increased the Reds’ chance of winning the Champions League from about three percent to about five percent. For the quarterfinals, Liverpool got a tough matchup in Manchester City, but most of the other remaining teams were also extremely strong, so the draw caused only marginal movement in Liverpool’s chances of winning the Champions League. Then the semifinal draw brought the greatest bounty, as the Reds avoided Bayern Munich and Real Madrid to face Roma instead. This increased Liverpool’s chance of winning the league from about 20 percent6The exact number was not available, so I extrapolated from the last number available before that draw. to 29 percent.The table to the left shows the net total improvement, in percentage points, of the chance SPI gave each team of winning the Champions League before and after the draw for each round. Among the teams that reached the quarterfinals, none benefited more than Liverpool. (And this calculation doesn’t even include Liverpool’s luck in the group draw, when the Reds were given the weakest of the eight groups.)Liverpool can winAs the table of team luck shows, Real Madrid has reached the Champions League final by facing a true gantlet. They got Paris Saint-Germain in the round of 16, Juventus in the quarters and Bayern Munich in the semifinals. However, the draw is not the only method by which good fortune may affect the outcome. Real would not have made the finals if Bayern Munich had not been extremely profligate with its chances. Bayern scored only three goals, but based on the chances the team got, we would expect them to have gotten 6.9 goals.But the way Bayern got all those chances bodes well for Liverpool. They pressed high and created turnovers. If Liverpool can execute its pressing game as effectively as Bayern did, the Reds should also be able to make trouble for Real Madrid. In this game, Liverpool’s defensive flexibility probably will be less help — sitting back and allowing Cristiano Ronaldo time to find space in the penalty area does not seem like the best option. With heavy metal soccer, Klopp may finally win a Champions League and bring a trophy back to Liverpool.CORRECTION (May 24, 2018, 6:15 p.m.): A previous version of this article incorrectly described Real Madrid’s path to the Champions League finals this year. They played Bayern Munich in the semifinals. Liverpool had the luck of the draw in this tournamentChange in each team’s chance of winning the Champions League before and after the draws, according the Soccer Power Index, 2018 Sevilla+3 Direct attacks to final third conceded per match25.021.218.7 The Egyptian-born Salah was coming off a 15-goal campaign with Roma in Serie A, but the signs of even bigger breakout were there. Liverpool inked him for around $47 million in June of last year, which was then a club record, and 42 goals later, that deal is looking like an incredible bargain. Firmino and Mane both similarly showed their potential before their Liverpool signings: Firmino’s production for Hoffenheim in 2014-15 and Mane’s for Southampton in 2015-16 were among the best player seasons in the sample I examined, which included non-striker attacking players in the five biggest leagues over the previous three seasons.3Minimum 2,500 minutes played combined between the player’s domestic league and the Champions League and European League. Liverpool used data to identify players who weren’t just on a hot streak but who demonstrated repeatable skills, and those purchases have paid off in goals.Liverpool adjusted to improve its defenseJurgen Klopp has called his style of play “heavy metal” soccer. His teams focus on creating and exploiting transition opportunities, the moments when neither team has established possession or set its defensive structure. His teams press high up the pitch, closing down opponents even when they have the ball well into their defensive half. In Klopp’s first season with Liverpool in 2015-16, his team led the league with a roughly 52 percent success rate in breaking up new opposition possessions. This metric calculates how often and how successfully a team closes down its opposition early in the opponent’s possession, which reflects the degree to which they implement a pressing defensive style.4Pressing rate is calculated by identifying when a new possession begins, and then tracking if the team in possession either completes three consecutive successful passes or completes an attack (by taking a shot, playing a pass into the penalty area, or winning a corner). If the possession is stopped, whether by a turnover, a foul or the ball going out of play for a throw-in, that counts as a “press.” The next season, with a year of training under their belt, Klopp’s players stepped up their pressure, breaking up nearly 54 percent of opposition possessions early. Once again, this rate led the league. However, there were some drawbacks to this style: In both those first two seasons, Liverpool was relatively vulnerable to direct attacks. If the first line of press failed, the Reds often found themselves chasing back to stop a counterattack headed for their goal. This is measured by direct attacks into the final third of the pitch, which shows when an opposition team can break forward into dangerous areas.5Direct attacks are calculated as attacking moves in which at least 50 percent of the movement is directly toward the goal, meaning that if you draw a straight line from where the attack started to where it ended and then measure the total distance the ball covered over all the passes and runs in the move, the ratio between those two distances must be at least 0.5.This season, Klopp has drilled his team to drop the pressing intensity in matches where it’s not needed. While they still can press high, Liverpool can also sit back and absorb pressure, as they did to great effect in the Champions League quarterfinal against Manchester City. This improved tactical flexibility has yielded results — reducing opponents’ goals, chances and successful fast attacking moves by a significant margin. The Champions League final seems immune to upsets. Real Madrid won three of the last five finals, with Bayern Munich and Barcelona taking the other two. And now Madrid is one win away from its fourth title in six years and third in a row. But this list of winners should not obscure that smaller clubs have come close. Atletico Madrid has taken Real Madrid to extra time twice in the last five finals, and Borussia Dortmund lost a nail-biter of a final 2-1 to Bayern. This year, it is Liverpool that has a real shot at upending a traditional power structure in the Champions League. And according to FiveThirtyEight’s Soccer Power Index, a Liverpool victory would not even be that much of an upset: SPI gives the team a 47 percent chance of lifting the trophy on Saturday.How did Liverpool become a true Champions League contender? To a certain degree, this is unsurprising. For starters, Liverpool is no upstart, at least historically. The club has five European Cups and its revenues are among the highest in European soccer.1Ninth highest last season, according to Deloitte. But the Reds have played in the Champions League only four times in the last decade, and this season is the first time they have even reached the knockout stages since 2009. It took an extensive and highly successful rebuilding effort to get Liverpool to the cusp of a European trophy. The three key components of this effort were smart analytics, innovative tactics and the usual helping of good luck.Liverpool struck gold in the transfer marketThe engine of this Liverpool team is its front line. Manager Jurgen Klopp prefers a 4-3-3 formation with four defenders, three central midfielders, and a forward line with a central striker flanked by two wide attackers. Center forward Roberto Firmino and left forward Sadio Mane combined for 44 goals and 22 assists between the Premier League and the Champions League, while Mohamed Salah matched that production almost by himself with 42 goals and 14 assists.Every one of these players was acquired in the transfer market: Firmino in 2015, Mane in 2016 and Salah last summer. Hitting on star attackers in three consecutive transfers is a major accomplishment no matter what your budget, but it’s especially impressive for Liverpool, which cannot afford to pay as much as the world’s richest clubs — as was made evident when Philippe Coutinho forced his way out of Liverpool for Barcelona in January. To build one of the world’s most dangerous front lines, Liverpool had to look for relative bargains, which more or less ruled out peak-age players at the height of their powers. Further, with Klopp’s pressing style, the team had to avoid the typical lumbering center forward and look for players versatile enough to press high and interchange in the attack. They needed attackers who could play anywhere in the front line. To find these key pieces, the team turned to analytics.One of the simplest ways to identify undervalued attackers is with expected goals (xG) and expected assists (xA) — two metrics that estimate the quality of scoring chances, built from information collected by sports-data company Opta.2The model for calculating expected goals seeks to give a single estimate for the likelihood of scoring a given shot, and the estimates for each shot are then added up over a season to give an expected goals total. You can find further methodological details in previous writeups. The ability to get on the end of good scoring chances, or to create them with a telling pass, is more stable across seasons than the ability to finish off such a chance. Over the last three years, very few young players have put up big numbers in xG and xA per 90 minutes while playing on smaller clubs and getting the majority of their minutes from outside the center forward role. Liverpool found three of them. Klopp has improved Liverpool’s defense this seasonHow Liverpool has fared in three defensive statistics during seasons under manager Jurgen Klopp Liverpool got lucky tooIt is practically impossible to win a cup final without some good fortune. Liverpool, by using its resources smartly and developing more flexible tactics, put itself in position to take advantage of good fortune when it arrived. And this year, every time the UEFA drew teams into competitive fixtures, Liverpool benefited. Expected goals conceded per match1.030.970.86 Roma-3 Pressing rate51.753.749.5 Juventus-2 Barcelona+6 Defensive stat2015-162016-172017-18 Bayern+9 Liverpool+11 Man City+2 Real Madrid-11 Source: FiveThirtyEight’s Soccer Power Index TeamChange in chance of winning
MIN56MIN64MIN 37, NYJ 17+4.5– IND9.24.7OAK1.00.75.41402 GB23.08.7LAR98.21.310.01558 PICKWIN PROB.PICKWIN PROB.ResultREADERS’ NET PTS Philly’s Super Bowl hangover is among the worst everWorst seven-game starts to a season (by Elo and win-loss record) for defending Super Bowl champions, 1967-2018 Home teams are in bold.The scoring system is nonlinear, so readers’ average points don’t necessarily match the number of points that would be given to the average reader prediction. BAL57NO53NO 24, BAL 23+8.4– 2013Ravens1591-372005Patriots4-3.571 Game quality is the harmonic mean of the Elo ratings for the two teams in a given matchup.*Average change is weighted by the likelihood of a win or loss. (Ties are excluded.)Source: ESPN.com 198549ers1620-73198549ers3-4.429 2005Patriots1641-712002Patriots3-4.429 1970Chiefs1624-612018Eagles3-4.429 Biggest Elo DeclinesWorst Starts CAR57.512.8BAL61.912.225.01581 Elo declines are relative to preseason Elo ratings for the season of the title defense.Sources: Pro-Football-Reference.com, ESPN.com JAX72JAX66HOU 20, JAX 7+6.6– MIA56MIA52DET 32, MIA 21+2.4– DEN10.75.2KC220.127.116.11551 PHI69PHI64CAR 21, PHI 17+5.3– Five of the teams on the lists above managed to recover enough to make the playoffs: the 1976 Steelers, 1985 49ers, 2001 Ravens, 2005 Patriots and 2010 Saints. (Pittsburgh even came within a game of returning to the Super Bowl.) But most of the defending champs who came out struggling could never quite recapture the magic of their championship runs — or, at least, they dug themselves too deep of a hole to climb out of. A 3-4 record might not sound too terrible, but since 1995 only 19 percent of teams that start 3-4 end up making the playoffs. (Yes, the Eagles are almost certainly more talented than a typical team that starts 3-4, but the odds aren’t great even after isolating teams that won at least 12 games the previous season.)So, this hasn’t exactly been the start coach Doug Pederson was looking for. But what’s to blame? And how can Philadelphia buck the odds and get back to its winning ways?It might be tempting to point the finger at a passing offense that went from fifth in adjusted net yards per attempt before Carson Wentz went down with a knee injury late last season to just 17th this year. And it’s true that backup Nick Foles was a shell of his Super Bowl self when starting the first two games of 2018, and that Wentz has had less time to throw deep and create big plays than he did while putting up MVP-caliber numbers a season ago. Certainly the Eagles’ offense has sputtered to a mere 22.0 points per game (22nd in the league) this year, after averaging 31.1 with Wentz in the 2017 regular season.2And 31.3 in the playoffs with Foles at the helm, for that matter.But by and large, Wentz has continued to be effective in orchestrating the Eagles’ passing attack, ranking eighth in the league in adjusted net yards per attempt — only two slots lower than last year — despite working his way back from a serious injury. Wentz’s average pass has traveled 2.3 fewer yards through the air according to ESPN’s Stats & Information Group, contributing to a decline in touchdowns per attempt (admittedly a problem for a red-zone offense that has dropped from first to 17th in efficiency). And yet Wentz is still moving the chains at the same rate,3His first downs per attempt are higher this year (37.9 percent) than last (36.4 percent). completing a sky-high 70.8 percent of his throws and tossing only one interception in 195 attempts.If Wentz’s performance has dropped off, it has only been a slight dip at most, perhaps one amplified by an abrupt change in clutch splits. In the final five minutes of one-score games in 2017, Wentz’s passer rating was 114.8 — 12.9 points higher than his rating for the season. This year, his passer rating in the same situations is 92.7 — down 15.4 points from his overall rating. But those plays make up only about 23 percent of Wentz’s passes, an unfair sample upon which to judge his entire body of work, even if it does have an outsize effect on the Eagles’ chances of winning from week to week.More significantly, the team around Wentz has been trending in the wrong direction. The QB is having to rely on tight end Zach Ertz more than ever, with wideouts Nelson Agholor and Alshon Jeffery struggling to get open downfield. (Mike Wallace was supposed to replace Torrey Smith as a complementary receiving threat, but he landed on injured reserve after just two weeks.) Meanwhile, Philly’s running game has declined from fourth in yards per carry (and third in yards per game) to 21st in each category, with Eagles ball-carriers slipping from third in yards after first contact per run to 19th.“I have no lack of confidence whatsoever in our run game,” Pederson insisted Monday. But after a contest in which Wendell Smallwood and Corey Clement combined for just 38 yards on 17 carries (a 2.2-yard average), perhaps his belief should be wavering. With Jay Ajayi on injured reserve, Philly is down to Smallwood (who ranks ninth in yards after contact per rush but hasn’t always been able to find a clear path to the second level4He ranks 28th of 47 qualified running backs in yards before first contact.) and Clement (who ranks 35th in yards after first contact per run). The result has been a less dynamic running game — Philadelphia’s longest rush is just 21 yards, tied for the least-impressive long run of any team — and an inability to slam the door when leading, such as in Sunday’s loss.Speaking of that defeat, it exposed another, even larger area of concern for the defending champs: defense. Last season, Philly ranked fourth in defensive expected points added (EPA) per game; this year, its ranking has slipped to 15th, with declines coming in near-equal measure against the pass and the run. Injuries have piled up, including ailments to 2017 starters Timmy Jernigan and Rodney McLeod. And while Fletcher Cox and the front seven have still managed to apply plenty of pressure,5According to Football Outsiders, Philly ranks eighth in pressures per dropback, and Cox ranks second in the league (behind the Los Angeles Rams’ Aaron Donald) with 25.5 pressures. the secondary has done a poor job in coverage — according to Football Outsiders’ charting data, Jalen Mills is allowing a staggering 11.7 yards per pass attempt (and is the fourth-most-targeted cornerback in the NFL) — plus the team ranks 21st in yards per rush allowed.Coordinator Jim Schwartz hasn’t altered his defense’s identity much: The Eagles don’t blitz often, relying on the line to generate pressure and counting on sound coverage and pursuit to limit opposing gains. But so far, that plan hasn’t worked as well as it did during the Eagles’ championship push.Philadelphia’s saving grace, though, might be its division. According to Elo, only the AFC East and AFC South are easier prey for their top-rated team than the NFC East, in terms of the quality of the next-best team in the division. (Philly remains the highest-rated team in the NFC East, by a whopping 91-point Elo margin over Washington.) Although our playoff odds give a slight edge in the division to the Redskins (41 percent to 39 percent, with Dallas checking in at 19 percent), things could be much worse for the Eagles if their competition were tougher.The banged-up Eagles have just one obstacle between them and a much-needed bye week: a showdown with the equally tailspinning Jacksonville Jaguars on Sunday in London. Despite the teams’ disappointing starts, this is one of the best games of Week 8, both in terms of matchup quality (i.e., the harmonic mean of the teams’ Elo ratings in each game) and how likely it is to swing either team’s odds of making the playoffs: 1981Raiders1555-91198249ers2-5.286 CHI27.99.3NYJ9.25.314.61457 2010Saints1581-541976Steelers3-4.429 LAR71LAR81LAR 39, SF 10+2.9– BUF52IND59IND 37, BUF 5+8.0– MIN67.7%±13.3NO78.0%±10.123.31609 Elo’s dumbest (and smartest) picks of Week 7Average difference between points won by readers and by Elo in Week 7 matchups in FiveThirtyEight’s NFL prediction game LAC62LAC69LAC 20, TEN 19+3.1– HOU51.313.9MIA29.013.627.51460 WSH53.013.9NYG0.70.814.61433 SEA37.916.0DET34.713.729.61543 Team ACurrentAvg. Chg*Team BCurrentAvg. Chg*Total ChangeGame Quality 1987Giants1534-1591987Giants1-6.143 Even for an NFL champion, life comes at you fast. Eight months ago, the Philadelphia Eagles were on top of the football world, having captured the franchise’s first Super Bowl title with a thrilling win over the New England Patriots. But after blowing a 17-point, fourth-quarter lead to the visiting Carolina Panthers on Sunday, the Eagles have started 2018 with a mediocre 3-4 record, sinking them to just a 45 percent chance of making it back to the playoffs (according to FiveThirtyEight’s Elo prediction model). Few defending champs have experienced a bigger drop-off to start the following year, and the early-season malaise has Philly’s faithful wondering whether this is just a standard Super Bowl hangover — or something worse.Going back to 1967 (the season after Super Bowl I), 52 teams have attempted to defend an NFL championship. Of those, just four — the 1987 New York Giants (1-6), 2006 Pittsburgh Steelers (2-5), 1999 Denver Broncos (2-5)1A team that was beginning life after John Elway. and 1982 San Francisco 49ers (2-5) — started the season with a record worse than the Eagles’ 3-4 mark over their first seven games. And in terms of Elo, only 11 Super Bowl winners lost more points of rating through seven games than the Eagles have, relative to preseason: CIN44.311.8TB18.104.22.168486 The best matchups of Week 8Week 8 games by the highest average Elo rating (using the harmonic mean) plus the total potential swing for the two teams’ playoff chances, according to FiveThirtyEight’s NFL predictions 198249ers1531-861981Raiders3-4.429 1999Broncos1593-961999Broncos2-5.286 2006Steelers1581-1012006Steelers2-5.286 OUR PREDICTION (ELO)READERS’ PREDICTION For Philadelphia, a win over Jacksonville could help stabilize its championship defense, boosting its playoff chances up to 53 percent. But a loss would knock those odds down to 30 percent, making a bad situation much worse.Defending champs rarely find their season hanging in the balance in Week 8. But if Philly doesn’t correct some of its problems against the Jaguars, the Eagles could quickly find themselves staring at one of the biggest post-Super Bowl letdowns in NFL history.FiveThirtyEight vs. the readersIn addition to our updating NFL prediction interactive (which uses FiveThirtyEight’s Elo ratings to forecast the rest of the season), you can pick against the algorithm in our prediction game. The prize? Bragging rights and a place on our giant leaderboard.Here are the games in which Elo made its best — and worst — predictions against the field of prognosticators last week: ARI61%DEN52%DEN 45, ARI 10+12.1– PIT61.76.1CLE0.70.66.71445 NE60NE64NE 38, CHI 31+0.7– PHI45.510.4JAX21.89.019.41537 Playoff %Playoff % WSH53WSH53WSH 20, DAL 17-1.6– 2002Patriots1549-602013Ravens3-4.429 Week 7 contained a special milestone for FiveThirtyEight prediction contestants: It was the first week of the season in which the average reader actually beat Elo’s picks! The readers picked up an average of 33.7 points against the model last week, with their only major slip-up being too little confidence in the Buccaneers against the Browns. (Elo looked particularly dumb when it picked Arizona to beat Denver, only to watch in horror as the visiting Broncos thrashed the Cards 45-10.) On the season, though, Elo still leads by an average of 199.6 points — so more weeks like this will be needed to chase down the computer.Particular congratulations are in order to Jesse Goddard, who led all (identified) users in Week 7 with 220.0 points, and to Scott Duhaime, who pulled into the season-long lead with 533.3 points. Thanks to everyone who has been playing — and if you haven’t, be sure to get in on the action! You can make picks now and still try your luck against Elo, even if you haven’t played yet.Check out our latest NFL predictions. 2001Ravens1601-511970Chiefs3-3-1.500 ATL80ATL77ATL 23, NYG 20-3.2– NE91.36.0BUF22.214.171.12426 2018Eagles1599-481968Packers3-3-1.500 SF0.70.7ARI0.20.10.81387 KC76KC74KC 45, CIN 10-2.8– TB77TB61TB 26, CLE 23-12.7– YearTeamElo RatingChangeYearTeamRecordWPct
Ohio State students and faculty may not want to head home too early for Memorial Day weekend. Today, OUAB’s Ramp Jam kicks off and brings BMX and skateboarding action to OSU. Ramp Jam will run 11 a.m.–5:30 p.m. in Buckeye Lot 3 behind the Schottenstein Center. There will be four showcases throughout the day featuring BMX rider Jamie Bestwick, skateboarder Pierre-Luc Gagnon, along with skateboarders Sandro Dias, Danny Mayer, Jimmy Walker, Elliot Sloan and BMX rider John Parker. “The main goal was to bring something to campus that has never been brought here before,” said Shari Lee, special events chairman of OUAB. “I think this is a pretty unique event that not many people get to experience, and it also has a really high appeal and excitement level.” The first shows will start at 12:30 p.m. and will last about 20 minutes. Ramp Jam costs about $65,000 and is funded by the student activity fee, Lee said. The funds go toward performance fees for the athletes and the band, the set-up fees required for the ramp and food vendors, promotional materials, safety and security needs and other miscellaneous costs, Lee said. OUAB receives 52 percent of the $25 Student Activity fee — $13. “With that $13, we have been able to plan 47 events this quarter, resulting in a cost of just under 28 cents per event,” Lee said. “For this specific event we will be utilizing around 1.6 percent of the allocated funds for the quarter.” The construction all over campus, particularly on the South Oval, prompted OUAB to combine Ramp Jam with the third annual CarnOval. “OUAB had been planning to do Ramp Jam for about six months,” Lee said. “CarnOval, because of all the construction on campus, was having a really hard time finding a location, and they were actually going to have to cancel it.” Lee said she believed the collaboration with CarnOval could help Ramp Jam. “I think (CarnOval) will bring a lot of people in because it’s become kind of a staple on campus over the last couple of years,” Lee said. Athletes will sign autographs during 50-minute breaks between performances. Donora, an indie-rock band, along with Cincinnati’s DJ Bandcamp also will perform music at the event. “I think it’s a really unique event, so it’s hard to capture the essence and enthusiasm of the event and that’s why we decided to do a video,” Lee said. “I think all in all the reaction has been good.” Ramp Jam is open to students with a valid Buck ID.