In July, I wrote a piece titled “The Rate of Domestic Violence Arrests Among NFL Players,” which has been getting a lot of attention recently — some of it missing the point.I based the analysis in my article on USA Today’s NFL Arrests Database, combined with data from the Bureau of Justice Statistics’ Arrest Data Analysis Tool and some historical data gleaned from the National Incident-Based Reporting System and a variety of BJS reports on domestic violence. The main points I made were:For most crimes, NFL players have extremely low arrest rates relative to national averages.Their relative arrest rate for domestic violence is much higher than for other crimes.Although the arrest rate for domestic violence may appear low relative to the national average for 25- to 29-year-old men, it is probably high relative to NFL players’ income level (more than $75,000 per year) and poverty rate (0 percent).But the article has been cited by a number of people to support the proposition that the NFL does not have an unusually high domestic violence rate. While I think this is a fair characterization of my intermediate results — the arrest rate I noted was 55.4 percent of the national average for 25- to 29-year-old men as suggested by the USA Today arrest data and rough number of players in the NFL — it’s misleading when taken out of context.Let’s be more explicit about the different assumptions that can affect that bottom-line comparison. For that analysis, I generally tried to lean toward assumptions favorable to the NFL, with the intention of showing that, even under those assumptions, the NFL appeared to have a “downright extraordinary” arrest rate for domestic violence.But there are still a lot of unknowns in the data and lot of choices to be made about what exactly we’re comparing to what.Reliability of arrest dataA lot of readers, commenters, emailers, tweeters, media, etc., have questioned the USA Today NFL arrest data. They’re right to be skeptical. There’s a good chance the arrest data is incomplete — particularly when it comes to marginal players who are only attached to the NFL briefly.When I wrote that piece, I was concerned about both over- and under-inclusion: The pool of NFL players who would pop up in the database might be even larger than the estimate based on roster limits (because some players come and go, and players are frequently dropped and replaced throughout the year), but it might also miss some players whose arrests flew under the radar.I hand-sampled a number of cases and found that they appeared to include many marginal players with minimal attachment to the league. With the NFL being so intensely followed, I thought the USA Today data set was probably pretty comprehensive.But some readers have made some good cases for why the arrest count the database produces could be low.On the pure data-collection level, I’ve corresponded with an enterprising reader who compared the frequency of arrests in the USA Today data for players with more games played vs. those with few games played. He found the first group had a much higher arrest rate. From this, he concluded that the database was probably missing arrests for lesser-known players, and he determined that basing the arrest rate on an assumption of 53 players per team (rather than the 80 players per team I used) was the most accurate approach (only coincidentally corresponding to the number of players on the roster during the year).His case seemed strong to me but not conclusive: It’s possible that marginally attached players are arrested at a lower rate. For example, marginally attached players may be younger (unsigned rookies) or older (borderline veterans) than typical players, and thus less likely to have families (younger) or be aged out of the most likely group to commit domestic violence (older). Additionally, we don’t know what’s driving the NFL’s overall domestic violence arrest rate, and I can imagine plausible scenarios in which regular players are more likely to commit and/or get arrested for the offense.Another potential problem, as several readers pointed out, is that virtually any NFL arrest data may understate the equivalent arrest rate in a less privileged population. In other words, NFL players who are involved in domestic violence incidents could be better at avoiding arrests than the general public. Relatedly, it’s possible there have been arrests that were either avoided or kept off the media’s radar because of team and/or league machinations.Whether any of those possibilities are likely or not, we should be explicit as to how our position on them affects our results.An appropriate pool for comparisonIf we want a bottom-line NFL vs. X number, the pool you use for X is obviously quite meaningful. But it’s difficult to figure out which pool we should be comparing to, and even if we do know what pool we want to use, figuring out their arrest rate (especially for domestic violence crimes) can be quite difficult.In my article, I primarily compare NFL arrest rates to arrest rates for 25- to 29-year-old men, and then I compared their arrest rate for domestic violence to their arrest rates for other crimes (it’s about four times higher). While we don’t have arrest data broken down by income, we do have such breakdowns for victimization rates (based on BJS survey data). I compared the relative domestic violence victimization rate for people from households making $75,000 or more to both the overall domestic violence victimization rate (it’s 39 percent as high) and rate for ages 20 to 34 (20 percent as high). It’s impossible to compare this directly to the relative NFL arrest rates with precision, but at least it gives us some benchmark for how income level may affect domestic violence incidents.In addition to inherent murkiness of trying to compare across different types of data, there are a few other possible problems with the $75,000 or more per year comparison.First, NFL players have a number of advantages that your typical member of a household making $75,000 and up each year may not. That’s the highest income group I had data for, but NFL players are typically wealthier than that. NFL players spend a good portion of the year in an extremely structured environment. They have extremely low rates of drug and alcohol abuse (especially relative to arrest rates for drug and alcohol-related crimes), and alcohol and drugs tend to be big risk factors for domestic violence.On the other hand, NFL players didn’t necessarily have the advantages that a lot of $75,000-and-up earners do. NFL players may be more likely than those earners to have come from difficult backgrounds, or to have experienced or observed abuse in their families, and in general to have missed out on the privileges associated with coming from a wealthier background.Finally, there are some differences in the data that we don’t know enough about to say what their effect might be, such as:Are victims from higher-income households more or less likely to make police reports that lead to arrests?How does the extreme wealth disparity between NFL players and their domestic partners affect the power dynamics that may lead to more or fewer arrests?Note: None of this has to be the case, and I haven’t studied these factors or their effects on criminality. But they are questions that affect our assumptions, and affect what type of comparison we should be making and how we should interpret it.Even if we could settle on a perfectly representative pool for comparison, getting even approximate figures for each group is extremely difficult. For example, as I noted in the original article, the BJS’s Intimate Partner Violence reports don’t include breakdowns by income anymore. So we have to make reasonable estimates based on several related numbers. This process has a lot of wiggle room in it as well, so we should be clear to look at what kinds of proxies lead to what kinds of results.Different combinations of assumptionsWith so much murkiness in both our data and our aims, the best thing to do is to look at a range of assumptions and see whether there are patterns that are apparent independent of such choices.Let’s first combine the possible issues with the USA Today data and represent them as a single number — which we’ll call “percentage of arrests captured by USA Today data” — representing its completeness with regards to actual arrests, as well as arrests that were otherwise avoided.Likewise, let’s combine the issues about comparison groups into a single percentage representing the bottom-line arrest rate of our comparable population (whatever it might be) relative to our 25- to 29-year-old average. In other words, we’re using one metric to represent each group by our best estimate for its relative arrest rate (which we can compare to benchmarks).Then we combine these two metrics with the information we have (NFL Arrest Rates in USA Today database, approximate number of NFL players and arrest rates for the general population), like so:We calculate the known NFL arrest rate and scale it to per 100,000 by taking the NFL arrests per year in the database, multiplied by 100,000, and divided by the number of NFL players per year (approximately 2,560).We divide this by the “percentage of arrests captured by USA Today data” (by assumption, per above).We gather data on the known national arrest rate for 25- to 29- year-olds, which is per 100,000.We divide this by our estimated relative arrest rate of a comparable population (by assumption, per above).Finally, we calculate the ratio between 2) and 4) and subtract 100 percent — this tells us how our estimated NFL arrest rate compares to the rate we estimate for a comparable population.Now we can chart the result of this calculation for given values of A and B as heat maps. Even if we assume extremely incomplete arrest data, the NFL’s overall arrest rate is still very low relative to the national average for its age range. But if we hold the NFL to an extremely high standard, we can still find its arrest rate to be subpar.I’ve used the same color scheme for both of these (100 percent = white). So it should be obvious that the NFL’s doing much worse with domestic violence arrests than with arrests overall.Note that the difference between assumptions can be an order of magnitude or more. Under a favorable set of assumptions, the NFL looks better than average; under an unfavorable set of assumptions, it’s doing terribly.For example, if you compare NFL players only to the national average for 25- to 29-year-old men, and you assume that the USA Today database is pretty much complete, you arrive at the 55.4 percent figure.On the other hand, if you assume that the NFL’s domestic violence arrest rate should be proportional to the overall arrest rate, you can see that the NFL has a “domestic violence problem,” whether the USA Today data is complete or not. This was essentially the scenario I was leading to in my initial article.
Going into Week 9, the No. 1 slot in our Elo ratings had been the exclusive province all season long of last year’s Super Bowl participants, the Seattle Seahawks and Denver Broncos. In fact, the last time a team other than Denver or Seattle ranked first in Elo was Week 19 of last season, when the San Francisco 49ers owned first place after beating the Carolina Panthers on the road in the NFC divisional playoffs. (They would cede that ranking to Seattle the very next week.)This week, though, the New England Patriots have finally broken the Denver-Seattle duopoly on No. 1 after the Patriots crushed the Broncos 43-21 Sunday afternoon. How unusual was the Seahawks’ and Broncos’ long stranglehold on the top slot? Going back to the advent of the 16-game schedule in 1978, it’s the eighth-longest span into a season it’s taken for a third No. 1-ranked team to emerge. Last season, it took seven weeks for Seattle to wrest No. 1 away from a Denver/New England duumvirate.For the Patriots, it’s a long-awaited return to a familiar spot. New England occupied No. 1 in 27 (!) consecutive editions of the Elo rankings between Week 19 of the 2011 season and Week 2 of the 2013 season. And since 2000, they’ve spent more weeks at No. 1 (102) than the next three most frequently top-ranked teams (the Indianapolis Colts, Green Bay Packers and St. Louis Rams) combined.But of all teams, the Patriots should know that a No. 1 Elo ranking midway through the season is no Super Bowl guarantee. They sat atop the league through the first nine weeks of both the 2012 and 2007 seasons but failed to hoist the Vince Lombardi Trophy either season. (Since 1978, the top-ranked team through Week 9 has gone on to win the Super Bowl at a 41.7 percent clip.)New England also faces a difficult schedule. It has a bye this week, but after the break it will have to travel to Indianapolis to face the fifth-ranked Colts. Then, following a home date against the 17th-ranked Detroit Lions, the Patriots must go on the road against the No. 12 Packers and the No. 14 San Diego Chargers in back-to-back weeks, with the surging No. 16 Miami Dolphins waiting in the wings after that. An average (1500 Elo rating) NFL team would be expected to win only 46.6 percent of the Patriots’ remaining games, which means they have the seventh-hardest remaining schedule of any team in the league.Our Elo-based simulations give the Patriots just a 16 percent probability of winning the Super Bowl, which is well below the aforementioned historical average for top-ranked teams through nine weeks. Part of that is simply an artifact of league and playoff expansion. Since the NFL adopted its current size and divisional format in 2002, the top-ranked team through Week 9 has won the Super Bowl 25 percent of the time, a rate more in line with New England’s simulated odds. But 2014 has also been a strange year in terms of the distribution of ratings across the league’s 32 teams. The Patriots’ 1677 Elo rating at No. 1 is 21 points below the average for that slot through Week 9 from 2002 to 2013, while 18 of the next 22 highest-rated teams have better Elo ratings than the average for their ranking from the previous 12 NFL seasons.In other words, New England isn’t as strong as the typical No. 1, and there is an unusual number of solid teams out there for the Pats to tangle with en route to the Super Bowl. That lends credence to the growing talk of 2014 being a banner season for parity in the NFL.Meanwhile, the league’s nine worst teams by Elo are far worse than usual, culminating with the Jacksonville Jaguars and Oakland Raiders each falling more than 50 points behind the typical ratings of the NFL’s two worst teams through nine weeks. It will be worth monitoring whether this year’s atypical dispersion of Elo ratings is a one-year quirk or part of a larger trend.Here are the current playoff and Super Bowl odds for all teams:I mentioned that San Francisco had defeated Carolina (who ranked fifth in Elo at the time) to briefly claim the No. 1 ranking during last season’s playoffs. This year, however, neither team has enjoyed the same kind of success, going a combined 7-9-1. And there’s a 55 percent chance that both will be shut out of a return trip to the postseason.After starting the season 1-2, the 49ers had regained some measure of playoff probability with three straight wins over the Philadelphia Eagles, Chiefs and Rams in Weeks 4 through 6. Going into Week 7, they even had an NFC West-leading 65 percent probability of making the playoffs, as well as the division’s best projected end-of-season win total in our Elo simulations. But a pair of losses sandwiched around a bye week have left San Francisco on the verge of missing the playoffs entirely. Its current playoff probability stands at 32 percent after taking into account their mediocre record (4-4), the difficulty of their remaining schedule (ninth-hardest), and the strength of the teams they’d have to beat out for a wild card (as their hopes of winning the NFC West have been all but extinguished).Carolina’s chances of returning to the playoffs look even worse. Despite failing to win five of its previous six games (it lost four and tied one), Carolina still had a 44 percent probability of qualifying for the postseason before its game against the New Orleans Saints — but our weekly playoff implications article also identified Panthers-Saints as one of the most crucial matchups of Week 9. Sure enough, New Orleans’ 28-10 victory dropped Carolina’s playoff probability by 25 percentage points, leaving it with less than a 1-in-5 chance of making the playoffs.In addition to the Panthers and 49ers, the other teams who lost the most from their playoff odds in Week 9 were the Baltimore Ravens and the Chargers in the AFC.The cause for Baltimore’s decline was all about the division odds — predictably, its head-to-head loss against the Pittsburgh Steelers on Monday night had huge ramifications for the AFC North race. Going into the game, the Ravens had a 33 percent chance of winning the division, with the Steelers sitting at 28 percent; after the game, Pittsburgh’s chances had increased to 45 percent and Baltimore’s had dropped to 13 percent. (Neither team’s wild card odds really budged at all.)San Diego’s dip, on the other hand, had little to do with a division race. The Broncos are rated so much higher than their AFC West competitors that our simulations see little chance they don’t win the division. That leaves the wild card as the only real viable path to the playoffs for the Chargers and Chiefs, both of whom are in a dogfight with each other — as well as the losers of the AFC East and North — for one of those two slots. (The AFC South loser is unlikely to make much of a wild card push.) Miami’s 37-0 pasting of San Diego on Sunday had direct consequences in that regard, boosting the Dolphins’ wild card probability by 17 percentage points as the Chargers’ chances dropped by 19 (with scarcely a change to either team’s division odds).Elo point spreadsRecord against point spread: 64-62-3 (7-5 in Week 9)Straight-up record: 94-39-1 (9-4 in Week 9)Although the Elo ratings are performing better against the spread in recent weeks, we still would strongly advise you not to take them to Vegas as a betting tool. Even so, it is always interesting to see how they differ from the spreads offered by the major sportsbooks.This week’s biggest disparity is in the Dallas Cowboys-Jaguars game, which is not only taking place in London, but adds the wrinkle of Dallas quarterback Tony Romo’s availability being in question. With the possibility that the Cowboys will once again have to start backup QB Brandon Weeden, who oversaw the team’s Week 9 defeat to the Cardinals, the oddsmakers have dropped Dallas to a mere 6-point favorite against the lowly Jaguars, rather than the 10.5-point favorite the Elo ratings would suggest.Aside from that change, the other big discrepancies against Vegas this week involve the Cardinals and Rams (the books have been comparatively down on Arizona all season, relative to Elo) and the Cincinnati Bengals and Cleveland Browns (Elo rates Cincinnati slightly higher — and Cleveland slightly lower — than Vegas’s power ratings would value the two teams). But in the Detroit-Miami tilt, which may go down as the biggest game of the week from a playoff-implications perspective, both Vegas and Elo agree: The hosting Lions should be favored by about a field goal.CORRECTION (Nov. 6, 11:56 a.m.): A previous version of this article incorrectly said that Elo is 62-44-3 against the point spread. It is 64-62-3.(Nov. 6, 2:04 p.m.): A previous version of this article said the Dallas Cowboys had a 75 percent chance of defeating the Jacksonville Jaguars on Sunday. Dallas should have an 82 percent win probability, because it has an Elo difference of +259 and there is no home-field effect in either direction.
More: Apple Podcasts | ESPN App | RSS Welcome to the latest episode of Hot Takedown, our podcast where the hot sports takes of the week meet the numbers that prove them right or tear them down. On this week’s show (Nov. 24, 2015), we bring you the latest edition of “Stat School,” just in time for you to enjoy alongside Thursday’s Thanksgiving football feast. Last time, Statman, aka Neil Paine, talked to us about NFL quarterback stats. This week, it’s the art of rushing. Neil takes us through three rushing-centric statistics: raw yardage, yards per carry and expected points added.Stat one: Raw yardageThe number of yards a player runs for in a game.Stat two: Yards per carryThe average number of yards a player gains per rushing attempt. Yards per carry is calculated by dividing the number of yards by the number of attempts.Stat three: Expected points addedAn estimate of the scoring margin generated by a player’s performance, based on a model predicting how many more points his team was expected to score after each play than before the play began.Stream the episode by clicking the play button, or subscribe using one of the podcast clients we’ve linked to above. Listen closely and you can school your football-obsessed uncles while chowing down on turkey and stuffing. If you’re a fan of our podcasts, be sure to subscribe on Apple Podcasts and leave a rating/review. That helps spread the word to other listeners. And get in touch by email, on Twitter or in the comments. Tell us what you think, send us hot takes to discuss and tell us why we’re wrong. Hot Takedown
Even before President Obama’s announcement Wednesday that the U.S. and Cuba were re-establishing diplomatic relations, the countries’ baseball relations were warming.Twenty-five players who were born in Cuba played for a Major League Baseball team in 2014, and together they accumulated 27.5 wins above replacement, according to Baseball Reference’s Play Index. Those are the highest totals for Cuban players in MLB since 1970 — back when players such as Tony Oliva, Tony Perez and Bert Campaneris, who’d signed with major-league teams before the U.S. trade embargo kicked in, were still stars.Raw numbers overstate the growing Cuban power in the majors. MLB has expanded from 24 teams in 1970 to 30 today. There are more players of all nationalities, and more wins above replacement to go around. (Roughly 1,000 per season these days.) But even as a percentage of MLB totals, Cuban batters and total Cuban WAR reached levels this past season not seen in at least 40 years.That level still isn’t all that high. Cuban players accounted for less than 3 percent of all wins above replacement last season. But even if Congress doesn’t lift the embargo, Cuban players already in the majors are likely to keep getting better and increase their share of MLB wins. Jose Abreu, Yasiel Puig, Leonys Martin and Jose Fernandez all are in their 20s. Each man has, in just the last two years, had seasons among the best ever for Cuban MLB players.It’s possible that a player who has debuted recently or who will join the league in the warmer diplomatic climate will become MLB’s best ever Cuban player. Only two Cubans have accumulated more than 54 wins above replacement in MLB history: Rafael Palmeiro and Luis Tiant. Neither was elected to the Hall of Fame.
This has been a pretty great year for Cleveland sports, particularly if you consider how miserable things had been over the previous five decades or so. In June, the Cavs staged an incredible comeback to win the NBA championship, and the Indians came within a game of winning the World Series in November. The only team that hasn’t joined the party by the Cuyahoga River is the Browns — because of course they haven’t. In fact, Cleveland’s football team might be headed for a very different kind of history if it can’t get its act together over the next month and a half.At 0-11, the Browns are the worst team in the NFL according to FiveThirtyEight’s Elo ratings, which estimate a team’s quality at any given moment. According to ESPN’s expected points metric, they have the league’s seventh-worst offense, the eighth-worst special teams, and the NFL’s worst defense by a mile. Even by the standards of a team that hasn’t made the playoffs since George W. Bush’s first term as president, this particular edition of the Browns has been notably terrible. The best they can hope for now is to avoid joining the small, ignominious club of teams who went an entire season without a win.Going back to the beginning of the NFL-AFL era in 1960, only three teams have played a full schedule1So, excluding the strike-shortened 1982 season, in which the Baltimore Colts went 0-8-1. without winning a single game: The 1960 Dallas Cowboys (who went 0-11-1, tying the Giants in the season’s penultimate game), the 1976 Tampa Bay Buccaneers (who went 0-14 in their debut season) and the 2008 Detroit Lions (who are currently the only team to ever go 0-16). Right now, our Elo model gives the 2016 Browns roughly a 32 percent probability of joining that group (31 percent for 0-16, plus a tiny chance of going winless with one or more ties).2Based on 100,000 simulations of the remainder of the schedule. 14Cincinnati27.2 And even if Cleveland does end up going 0-16, it should probably be spared the last-place ranking in the pecking order of winless squads. Among the set of simulations where they didn’t win a game, the Browns finished with a better end-of-season Elo rating than the 1976 Buccaneers every single time (those Bucs had the worst full-season Elo of any team in NFL history) and were rated better than the 1960 Cowboys 94 percent of the time. Then again, there’s less than a 1-in-15,000 chance that a winless Browns team finishes with a better Elo than the winless 2008 Lions, and that team is often considered the reigning worst team ever. There will be little to mitigate Cleveland’s disgrace if the team loses its next five games.But that’s still relatively unlikely. Since 1960, 13 other teams have lost all of their first 11 games, and all but three of them have found a way to avoid the humiliation of a winless campaign. Now comes Cleveland’s chance to do the same.Jay Boice contributed research.Check out our latest NFL predictions. 17Pittsburgh12.9 Upcoming Browns games To suffer a winless season, it takes a special combination of poor talent and horrible luck. In their 0-16 season, the Lions had the point differential of a roughly 3-win team, but they also had the misfortune of going 0-5 in games decided by 8 points or fewer, situations in which history tells us even bad teams can usually squeak out a few victories by chance alone. For their part, the Browns have the point differential of a 2-9 team and a better scoring margin through 11 games (-141) than the 2008 Lions (-153), 1960 Cowboys (-183) or 1976 Bucs (-195) did. 16San Diego32.9 12N.Y. Giants24.8% WEEKOPPONENTWIN PROBABILITY Average pregame win probability from Elo simulations.Source: Pro-Football-Reference.com 15Buffalo11.3
Cubs0.7C. GomezLF+1.6K. Schwarber+0.01.1 Dodgers1598101.898.5%26.5%2.2 Twins147574.5184.108.40.206 CAUTIOUS BUYERSELO RATINGEXP. WINS PER 162 GAMESDIV. SERIES ODDSWORLD SERIES ODDSDOYLE NUMBER Brewers1.3Z. CozartSS+3.1O. Arcia+1.02.7 Blue Jays1494220.127.116.11.1 Brewers151282.864.2%4.3%1.3 Yankees0.9T. Frazier1B+2.3J. Choi+0.12.1 Astros2.2Y. DarvishSP+3.1M. Fiers+1.14.3 Orioles147418.104.22.168.1 For most Major League Baseball teams, the trade deadline is a chance to step back and take stock of the franchise’s trajectory. Although only a small fraction of rumored deals actually end up happening, a team’s willingness to swap assets — as either a buyer or a seller — says a lot about where it is in the cycle between contending for a World Series and playing for the future.For a few teams, the choice has already been made. These are the clubs on the ends of the baseball spectrum: the bottom dwellers already committed to punting the present in order to stockpile young talent and the clear front-runners who can begin fine-tuning their playoff rosters in July.But the bulk of the league faces a fork in the road and doesn’t have the luxury of soul-searching with the trade deadline less than two weeks away. The decision to buy or sell is both critical — botched maneuvers can cripple a franchise for years — and further complicated by whether teams are getting a “rental” player (with an expiring contract) or someone who can help them for the next few years. But fear not, baseball general managers, we are here to help.A few years ago, my colleague Nate Silver and I developed a statistical framework for trade-deadline strategy: the Doyle Number (named for a certain pitcher the Detroit Tigers mortgaged their future to acquire at the 1987 deadline). Doyle represents the number of future wins a team should be willing to part with in exchange for adding an extra win of talent this season. So a Doyle of 1.00 means a team should be indifferent to buying or selling — a one-win improvement this year adds as much to its current World Series odds as a future win would add over the long term.1Specifically, its odds over the next six seasons. If its Doyle rises any higher, it should probably be buying (since wins this year are more valuable than future wins); any lower, and it should be selling.For example, the Cleveland Indians currently have a Doyle Number of 1.48. With a good (though not quite great) roster and decent (but not quite ironclad) division-series odds,2Doyle focuses on the division series rather than the wild-card playoff, because the latter’s single-elimination format truly is a crapshoot. they should probably be trying to add talent over the next few weeks to bolster their chances of returning to the World Series. Meanwhile, the New York Mets’ Doyle is 0.08; their injury-riddled talent base is mediocre, and they have very little shot at the division series, so they should be selling off anyone that isn’t nailed down.With those ground rules in place, here’s every team’s Doyle number as of July 16:3The only change I’ve made to the model for this season is that it now uses the future wins (per 162 games) implied by a team’s Elo rating to assess a team’s talent at the deadline, rather than its rest-of-season projected winning percentage from FanGraphs (which is slower to incorporate changes in a team’s play than Elo). Phillies143365.20.00.00.0 Giants147574.50.00.00.0 Rockies0.6J. BruceRF+2.0G. Parra+0.21.1 Red Sox1.6A. AvilaC+2.3C. Vazquez-0.24.0 Talent is an estimate of a player’s current projected wins above replacement (WAR) per 162 games.Sources: RosterResource, Baseball-Reference.com, FanGraphs, Tangotiger Expected wins are derived from the team’s current Elo rating.Source: FanGraphs Mets150322.214.171.124.1 The Doyle topples one of the most common perceptions of the deadline: The team most in need of a trade is the team that is one bat (or one arm) away from making a postseason run. By contrast, Doyle shows that the the teams who should be most willing to buy are the teams having the best seasons — not teams merely on the cusp of the playoffs. It’s a consequence of how random the MLB playoffs are: When even the best teams have long odds of winning, there’s practically no amount of talent a team can add that will cause its World Series probability to hit diminishing returns.This year, the top Doyle teams are the historically dominant Los Angeles Dodgers and Houston Astros — and, to a lesser extent, the Indians, Washington Nationals and Boston Red Sox. With the possible exception of Houston, each team has at least one position where it can substantially improve, and Doyle indicates they should focus on shoring up those weaknesses in preparation for a World Series run.More interesting, however, are the clubs near the threshold between buying and selling. These are teams for whom there is less of a clear-cut direction to take — but some decision must be made, since any direction would add more total future championships than merely standing pat. One archetype for that group is the unexpected contender: Think of the Milwaukee Brewers, who find themselves in first place in the National League Central division despite a relatively unimpressive collection of talent. Milwaukee’s 1.26 Doyle suggests it should lean toward buying, since an improved core will become much more valuable in the postseason.The opposite model might be that of Milwaukee’s division rival, the Chicago Cubs: an expected favorite to whom Doyle gives a disappointingly low World Series probability. The defending champs are having a well-documented down year, and although they’re talented enough to have decent title odds if they make the playoffs, that’s far from guaranteed no matter what deadline moves they make. As a result, their 0.66 Doyle suggests they should lean toward punting on this season.The Cubs, however, don’t seem willing to give up just yet, trading for starter Jose Quintana last week. They weren’t necessarily wrong to do it, either; it’s important to remember that the Doyle Numbers above mostly apply to rental players. After I tweaked the model to account for the remaining years on Quintana’s contract,4Specifically, I gave Chicago 3.2 wins above replacement of talent this season — Quintana’s current talent level, per Tom Tango’s WAR projection system — with an annual half-win decline over each of the next three seasons. Quintana’s total four-year contribution to Chicago’s talent level (9.8 WAR) was then subtracted, spread evenly over the three seasons after his contract expires. Chicago’s Doyle for this specific trade became 1.31 — meaning it was probably worth it to give up top prospects in exchange for improving its talent base over multiple seasons.Those are exactly the kinds of extenuating circumstances a team in Chicago’s current situation needs in order to justify buying instead of selling. Any team with a Doyle north of 0.60 or so could probably do a similar calculation, which means 11 clubs — the Dodgers, Astros, Nationals, Red Sox, Indians, Brewers, Diamondbacks, Yankees, Rays, Cubs and Rockies — could reasonably call themselves buyers this season under the right circumstances.So we know who’s at the restaurant, and we know who’s on the menu — but what is everyone ordering? We can also use Doyle to build a trade deadline plan for each team, pairing them with players who fit a need and make sense given how realistic a club’s World Series chances are. For each of the 11 teams above, I gathered their current starters5The cutoff for pitchers was either the No. 4 slot in the rotation (for starters) or the setup man role (for relievers). and tracked how good each is this season, according to Tom Tango’s WARcel projections. I also pulled a list of deadline rental targets6So, expiring contracts only. from the excellent RosterResource.com, calculating their WAR talent as well. Multiplying a team’s Doyle Number by the difference in WAR talent between a rental target and its current starter at the same position, we came up with a “deadline index” that indicates how good of a match the player is for the team. After assigning duplicated targets to the team whose index for the player was highest, here are the best pairings between team needs and available players, according to Doyle: Pirates1496126.96.36.199.1 Red Sox154489.8188.8.131.52 Marlins1494184.108.40.206.1 Diamondbacks152084.6220.127.116.11 Astros1591100.399.724.62.2 Doyle’s deadline shopping listThe top targets for each potential buyer based on deadline index, which is the difference in talent between an available ‘rental’ and the team’s current starter at his position, multiplied by the team’s Doyle Number Rays0.9C. MaybinLF+1.8S. Peterson+0.21.4 Tigers148918.104.22.168.1 Rangers152585.714.7%1.3%0.4 Where each team stands at the deadlineTeams ranked by Doyle Number — how many future wins of talent a team should trade away to acquire 1 win this season White Sox146772.71.10.00.0 TOP TARGETCURRENT STARTER FOR TARGET POSITION Padres144467.60.20.00.0 Braves147822.214.171.124.1 Cubs153587.822.02.30.7 Nationals155191.593.812.81.9 Indians1.5J.D. MartinezRF+2.4T. Naquin+0.33.1 Athletics147875.21.30.00.0 SELLERSELO RATINGEXP. WINS PER 162 GAMESDIV. SERIES ODDSWORLD SERIES ODDSDOYLE NUMBER Reds146371.80.70.00.0 TEAMDOYLEPLAYERPOSTALENTPLAYERTALENTDEADLINE INDEX Obviously, here are other layers of complexity involved in actually pulling off these deadline deals, including the quality of the trading team’s farm system, which of its existing players might return from injury before the playoffs, and the possibility of a contract extension with the player being acquired. But the general idea of Doyle is that it provides a flexible framework for trade-deadline decisions, based on how valuable it is to add or shed current talent with an eye on the future.Keep that in mind as we watch whatever deals unfold over the next couple of weeks. A team’s Doyle Number is a rough guideline, the starting point for thinking about trade possibilities. What happens after that is a combination of reading the market, picking the right moment to strike and then making endless phone calls until that forgettable middle reliever is finally yours.Check out our latest MLB predictions. Cardinals150781.610.20.60.3 Nationals1.9J. DysonLF+2.7C. Heisey-0.45.8 Rays151583.5126.96.36.199 Mariners1513188.8.131.52.3 Dodgers2.2A. ReedRP+1.9P. Baez+0.82.3 Indians154489.8184.108.40.206 D-backs1.0C. GrandersonLF+2.0D. Descalso+0.02.0 Angels1502220.127.116.11.1 SOLID BUYERSELO RATINGEXP. WINS PER 162 GAMESDIV. SERIES ODDSWORLD SERIES ODDSDOYLE NUMBER Rockies150480.918.104.22.168 Royals149578.922.214.171.124 Yankees153186.9126.96.36.199
The warm sunshine beams down upon the tropical waters off the coast of San Diego, as Ohio State softball shortstop Maddy McIntyre sits on a surf board, bobbing in the Pacific Ocean and waiting for the next wave to ride. The serenity the ocean offers is a far cry from the stress of finals week or the pressure of hundreds of screaming fans. “(Surfing) is just a good way to take a break from everything,” McIntyre said. “Sometimes you’re out on the softball field or sometimes it gets intense with school and everything, so it’s just the best way to fall back and just relax. The feeling I get when I drop in is priceless.” McIntyre, a sophomore from San Diego, has started every game but one in her two-year OSU career. She’s a career .265 hitter with a .944 fielding percentage from her middle infield position. But while softball might be her first love, surfing has morphed from a fun hobby into something much more important to McIntyre. “It’s definitely her passion,” said senior teammate and third baseman Megan Coletta. “She really misses it (when she’s in Ohio) and she has a lot of passion for it and knowledge about the ocean.” McIntyre’s passion started at age 12, off the coast of Maui, Hawaii. It was there she first received personalized instruction with surfing trainers who immediately recognized her talent and passion for the sport. They encouraged her to keep riding when she returned home to California. Her father made sure that became a reality. “For one of my birthdays, my dad got me a board, and it was the best thing. He couldn’t keep me out of the water after that,” McIntyre said. She and her father – an avid surfer himself – have used their passions for surfing to develop an even tighter bond. They usually go in the summers, fitting in a quick, two-hour session before Marc McIntyre drops his daughter off back home and heads to work. The father-daughter surfing time is something they both cherish. “It’s awesome,” Marc McIntyre said. “She’s a better surfer than I am, but it’s still fun just being out there in the water with her. It makes you think, ‘It doesn’t get much better than this.’” The landlocked qualities of Columbus make surfing during softball season impossible for Maddy McIntyre, so when she gets home to San Diego, she feels like she has to make up for lost time. “I get really excited to surf when I go home,” Maddy McIntyre said. “But at home, everyone gets so mad, like, ‘Oh, the waves suck today,’ so they won’t go out. But now, for me, it’s like even if the waves suck, I still want to go out because I’m not out there very often.” Her father said she will go out at every opportunity when she’s home. Whenever she can get someone to go with her, be it morning, noon or night, she’ll hit the waves. OSU softball coach Kelly Kovach Schoenly said she loves her shortstop’s passion for surfing, and encourages her to keep up with it as much as possible. When Schoenly takes recruiting trips to Calif., which is fairly frequently, Maddy McIntyre is often there, badgering her coach to catch some waves with her. “It’s really cool we have kids with such different passions,” Schoenly said. “I’ve never really known surfing, so when I hear about the waves, and just the love that she has for it, I’m really excited for her to have that.” For someone who is used to having all eyes on her whenever she competes, surfing offers Maddy McIntyre the chance to drop in and do what she loves, away from the fandom. “The thing I like most about (surfing) is it doesn’t have to be competitive,” Maddy McIntyre said. “I don’t have to go out and have to perform. I can go for something great and I don’t have to worry if I don’t land it, or if the wave eats me up, it doesn’t matter, I can just have fun with it.” Schoolwork and softball might be Maddy McIntyre’s primary focuses during the year, but once summer rolls around, her childhood passion takes center stage. Her bat and glove get swapped for a board, and her No. 30 jersey gets traded for a bathing suit. For Maddy McIntyre, summer is nearly here – the sun is out and the ocean beckons.
Junior center Trey McDonald (55) covers his face as he sits on the side of the court following the game. OSU lost to Dayton, 60-59, at First Niagara Center March 20. Credit: Ritika Shah / Asst. photo editorBUFFALO, N.Y. — The swan song has been sung for the Ohio State Buckeyes.As senior guard Aaron Craft’s desperation shot at the buzzer fell hopelessly to the floor, so did his career at OSU, as the No. 6-seed Buckeyes fell to No. 11-seed Dayton, 60-59, Thursday.Craft made a tough layup in the lane with less than 20 seconds to play to put his team ahead by one, but a running layup by Dayton redshirt-senior guard Vee Sanford proved to be the difference as the Flyers — and ex-Buckeye guard Jordan Sibert — pulled the upset.OSU started quickly, leading 7-3 after a layup by senior guard Lenzelle Smith Jr. at the 16:43 mark.But Dayton responded, scoring 10 of the game’s next 12 points after Flyer redshirt-senior center Matt Kavanaugh finished off a 3-point play.The Flyers held the lead until Craft made two free throws with 8:15 left in the first half to give the Buckeyes the lead, 22-21. Craft finished a perfect 3-3 from the field and 3-3 from the line in the first half, on his way to a team-high nine points in the game’s opening 20 minutes.The game remained close for the remainder of the first half, but Dayton took a 33-30 lead to the break behind nine points from Kavanaugh.OSU came out sluggish in the second half, allowing the Flyers to extend their lead to 41-34, with 15 minutes to play.But back-to-back dunks by junior forward Sam Thompson and a bucket by Ross tied the game at 41 with 10:58 remaining.Thompson tipped in a missed 3-pointer by Craft on the Buckeyes’ next possession for OSU’s first lead since the 8:15 mark of the first half.A rugged game ensued, and the Buckeyes led 50-49 before freshman forward Marc Loving picked up his fourth foul of the game. Sophomore forward Dyshawn Pierre then made two free throws to put the Flyers back in front by one.But after former Buckeye and now Flyer Sibert missed a 3-pointer, Craft drove the lane and scored to put OSU back up. He missed the free throw, but OSU still led, 52-51 with 3:32 left.Dayton senior forward Devin Oliver scored at the other end, and after a turnover by OSU, Craft committed a flagrant-1 foul on Sibert as he drove to the hoop. Sibert nailed both free throws, and Dayton led by three.But Craft responded with yet another and-one, this time making the free throw to tie the game at 55 and lead to the dramatic finish.Craft finished with 16 points, five rebounds and four assists in his final game as a Buckeye, and Thompson finished with a game-high 18. After his game-winning shot, Sanford tallied 10 points for the Flyers, who are set to face the winner of No. 3-seed Syracuse and No. 14-seed Western Michigan Saturday.
OSU redshirt junior quarterback Cardale Jones (12) runs with the ball during a game against Virginia Tech on September 7 in Blacksburg, Virginia. OSU won 42-24. Credit: Samantha Hollingshead / Photo EditorDespite a shaky start so far in 2015, redshirt junior quarterback Cardale Jones will remain Ohio State’s starter when the Buckeyes take the field Saturday to face off against Western Michigan, OSU coach Urban Meyer announced Wednesday after practice. Jones has started all three of OSU’s games so far, but he has yet to look like the same player that guided the Buckeyes to a national title last season after then-redshirt freshman J.T. Barrett got hurt against Michigan on Nov. 29. The Cleveland native has twice been benched in favor of Barrett, including last weekend against Northern Illinois after Jones led OSU to just three points in five possessions while throwing two first-quarter interceptions. Even though Barrett came in and helped lead the Buckeyes to a 20-13 victory, Meyer said he has yet to do enough to swipe the starting spot from Jones.“(Jones) was the quarterback of the team when we finished the season, he was the quarterback during spring practice and he finished training camp as the starting quarterback,” Meyer said. “To replace him, the other guy’s gotta pass him up. Either (on the practice field) or in the games. That hasn’t happened.” Meyer admitted that the battle between the two is close. However, the coach stressed that all the blame for the quarterbacks’ poor play can’t be placed on them. “Quarterbacks are a product of those around them. We all have to do a better job,” Meyer said. “It’s not (Jones). The offense right now is in a funk.” Redshirt junior wide receiver Michael Thomas said the offense will be fine moving forward, adding he has faith in whoever starts.“I trust J.T. out there or Cardale,” Thomas said.Jones and the Buckeyes are set to be back in action against Western Michigan on Saturday at Ohio Stadium. Kickoff is scheduled for 3:30 p.m.As for beyond the upcoming game, Meyer said Jones would be “the guy.”“Unless he doesn’t perform well,” he added.
Want the best of The Telegraph direct to your email and WhatsApp? Sign up to our free twice-daily Front Page newsletter and new audio briefings. Ross Poldark (played by Aidan Turner) and Demelza (played by Eleanor Tomlinson) Credit:Mike Alsford/BBC Poldark fans and critics were left delighted after Sunday night’s second series debut lived up to expectations.It picked up where it left off, with Ross arrested for “wrecking, inciting a riot, murder”, and Demelza bereft on a cliff-top with the threat of the death penalty hanging over her husband. Last month, Debbie Horsfield, who adapted the Poldark screenplay from the novels, admitted transforming Poldark’s Demelza from demure wife into combative proto-feminist. Heida Reed, the actress, has disclosed that she was involved in the decision to cut a controversial rape scene from Poldark.It was revealed last month that the BBC had dropped a storyline from the third novel in the series in which Aidan Turner’s character rapes his former lover.Now Ms Reed, who plays Poldark’s ex-fiancee Elizabeth, has revealed her role in the decision to replace the attack with an affair between the pair.The 28-year-old said she and Turner were consulted with production bosses about the scene and had “big conversations” as they “felt it wasn’t right”. The return of Poldark was watched by 5.1 million viewers, with a peak audience of 5.3 million and a share of 22.7 per cent.The BBC programme trailed slightly behind period drama rival Victoria on ITV, which scored an average of 5.2 million and peak of 5.9 million, with these numbers including those watching on ITV+1. The controversial scene did feature in the novels, by Winston Graham, and the 1975 BBC television adaptation of the classic historical adventure series.In Graham’s 1953 book Warleggan, Poldark breaks into Elizabeth’s house before grabbing her and treating her “like a slut”.The character tells her “it’s time you were so treated” before forcing her onto a bed. Elizabeth later becomes pregnant with his child.However, BBC insiders had said the scene was changed in the new TV series to an affair between the two characters because “times had changed” since the books were written. Viewers were also waiting with bated breath to see whether Ross would bare his chest again after the topless scything scene of series one.It did not take long for him to strip off to reveal his glistening physique and the TV audience was not disappointed. Icelandic actress Heida Reed said she and Aidan Turner felt the scene ‘wasn’t right’Credit:Chris Jackson/Getty Aidan Turner’s character Poldark stripped off to reveal his glistening physique on Sunday night’s show Speaking for the first time about the decision to drop the sexual attack from the Cornish drama, Reed said: “Actually, it did change, as we had conversations.””It was a collaborative decision,” she told the Daily Mail. “Initially, it was a bit more intense, but we felt it wasn’t right.”The Icelandic actress added: “Aidan and I were both consulted when they were discussing how to interpret that scene, because it’s a very delicate one.”We had big conversations about it and we rehearsed it a lot.” Aidan and I were both consulted when they were discussing how to interpret that scene… we had big conversations about itHeida Reed