The Philadelphia 76ers are going to make the playoffs — not that their best players know what that feels like. Teams with their level of inexperience don’t usually push past the first round. Can the Sixers break the mold?
Model CreatorsNate Silver, Jay Boice and Neil Paine ReferencesBasketball-Reference.com / Real Plus-MinusElo ratings / Monte Carlo simulations / Box Plus/Minus / Simple Projection System The DetailsFiveThirtyEight’s NBA predictions have gone through quite an evolution over the years.Our first iteration simply relied on Elo ratings, the same old standby rating system we’ve used for college and pro football, college basketball, baseball, soccer, Formula One racing and probably some other sports I’m forgetting. Basic Elo is generally useful — and we still track it for teams going back throughout history — but it only knows who won each game, the margin of victory and where the game was played. So if a player is injured or traded — or resting, as is increasingly the case in the NBA — Elo wouldn’t be able to pick up on that when predicting games or know how to account for that in a team’s ratings going forward. In fact, even if a team simply made a big offseason splash (such as signing LeBron James or Kevin Durant), Elo would take a long time to figure that out, since it must infer a change in team talent from an uptick in on-court performance.To try to address that shortcoming, in 2015 we introduced a system we called “CARM-Elo.” This still used the Elo framework to handle game results, but it also used our CARMELO player projections to incorporate offseason transactions into the initial ratings for a given season. In a league like the NBA, where championships now feel like they’re won as much over the summer as during the season itself, this was an improvement. But it still had some real problems knowing which teams were actually in trouble heading into the playoffs and which ones were simply conserving energy for the games that matter. Since a team’s underlying talent is sometimes belied by its regular-season record — particularly in the case of a superteam — an Elo-based approach to updating ratings on a game-to-game basis can introduce more problems than it actually solves.Moving beyond EloOne attempt to salvage CARM-Elo was to apply a playoff experience adjustment for each team, acknowledging the NBA’s tendency for veteran-laden squads to play better in the postseason than we’d expect from their regular-season stats alone. This also helped some, but CARM-Elo still had problems with mega-talented clubs (such as the 2017-18 Golden State Warriors) that take their foot off the gas pedal late in the NBA’s long regular season. It was clear our prediction system needed a major overhaul, one that involved moving away from Elo almost completely.As we hinted at in our preview post for the 2018-19 season, we made some big changes to the way we predict the league that year. Chief among them is that our team ratings are now entirely based on our CARMELO player projections. Specifically, each team is judged according to the current level of talent on its roster and how much that talent is expected to play going forward. Here’s how each of those components work:Talent ratingsAt their core, our CARMELO projections forecast a player’s future by looking to the past, finding the most similar historical comparables and using their careers as a template for how a current player might fare over the rest of his playing days. After running a player through the similarity algorithm, CARMELO spits out offensive and defensive ratings for his next handful of seasons, which represent his expected influence on team efficiency (per 100 possessions) while he’s on the court. You can think of these as being similar to ESPN’s Real Plus-Minus or other adjusted plus-minus-style ratings.The player ratings are currently based on a blend between Real Plus-Minus (RPM), Box Plus/Minus (BPM) and, on defense, our new DRAYMOND metric. In our mind, each of these metrics represents a different facet of measuring player performance: BPM to capture and weight the player’s contributions in the traditional box score; RPM to measure the effect he has on his team’s efficiency when he is on the court; DRAYMOND to capture a critical but underutilized aspect of defense, which is to reduce opponent shooting percentages by contesting and otherwise disrupting shots. A blend of all applicable metrics appears in the CARMELO individual pages under the player’s offensive rating (using BPM and RPM) and defensive rating (using BPM, RPM and DRAYMOND).These blended ratings provide a prior for each player as he heads into the current season. But they must also be updated in-season based on a player’s performance level as the year goes on. To do that, we have two methods (for both offense and defense) depending on the data available:Using Real Plus-Minus and Box Plus/Minus. Ideally, both metrics will be published during a season, allowing us to use a blend (⅔ weight for RPM; ⅓ for BPM) on each side of the ball to update our prior ratings. When that happens, we assign a weight to the prior that is relative to 1 minute of current-season performance. On offense, that weight is calculated with a constant term of 416 minutes, plus 0.3 times a player’s minutes from the season before, plus 0.15 times his minutes from two seasons before, plus 0.05 times his minutes from three seasons before. That number is multiplied by his CARMELO preseason offensive rating and added to the product of his current-season minutes and current-season offensive plus/minus blend, and divided by the sum of current-season minutes and the prior weight to get an updated offensive rating. (The rating for players with 0 current-season minutes played is, by definition, the prior.) On defense, the weight has a constant of 60 minutes, plus 0.3 times a player’s minutes from the season before, plus 0.15 times his minutes from two seasons before, plus 0.05 times his minutes from three seasons before. This weight is combined with current-season performance in the same manner as on offense.Using Box Plus/Minus only. At a certain stage of each season, ESPN will not have released RPM data for the current season yet. During that time, we must update the in-season ratings using only BPM, which is usually available since the very start of the season via Basketball-Reference.com. Just like with our blended number from above, we assign a weight to the prior that is relative to 1 minute of current-season performance — but we must use different weights because BPM is not quite as reliable an indicator of player performance as RPM (or our RPM-BPM blend). On offense, the weight is calculated with a constant term of 703 minutes, plus 0.27 times a player’s minutes from the season before, plus 0.13 times his minutes from two seasons before, plus 0.04 times his minutes from three seasons before. That number is multiplied by his CARMELO preseason offensive rating and added to the product of his current-season minutes and current-season offensive plus/minus blend, and divided by the sum of the current-season minutes and the prior weight to get an updated offensive rating.On defense, the weight has a constant of 242 minutes, plus 0.48 times a player’s minutes from the season before, plus 0.24 times his minutes from two seasons before, plus 0.08 times his minutes from three seasons before. This weight is combined with current-season performance in the same manner as on offense.Regardless of the version being used, these talent ratings will update every day throughout the regular season and playoffs, gradually changing based on how a player performs during the season.Overnight updatesBecause our data sources for player ratings (ESPN and Basketball-Reference.com) don’t update individual statistics immediately after the end of every game, we added a function to preliminarily estimate the changes to a team’s rating as soon as a game ends. For each player in our database, we adjust his offensive and defensive ratings up or down very slightly after each game based on his team’s margin of victory relative to CARMELO’s expectation going into the game. These numbers add up at the team level to reflect how we predict that a team’s ratings will change in the wake of a given result.The advantage of this is that we can provide an instant update to the model as soon as a game ends. However, since these estimates are stopgaps, they will be changed to the RPM/BPM-based ratings from above when the data from those sources updates. After any given game, these differences should be small and generally barely noticeable. But we think this change will be particularly worthwhile in the playoffs, when team odds can shift dramatically based on a single game’s result.Playing-time projectionsNow that we have constantly updating player ratings, we also need a way to combine them at the team level based on how much court time each player is getting in the team’s rotation.For CARM-Elo’s preseason ratings, we used to accomplish this by manually estimating how many minutes each player would get at each position. Needless to say, this is a lot more work to do in-season (and it requires a lot of arbitrary guesswork). So as part of our move toward algorithmizing our predictions in a more granular way, we developed a program that turns simple inputs into a matrix of team minutes-per-game estimates, broken down by position.This system requires only a rank-ordered list of players on a given team by playing-time preference (the default order is sorted by expected rest-of-season wins above replacement), a list of eligible positions a player is allowed to play (the system will assign minutes at every player’s “primary” position or positions first, before cycling back through and giving minutes at any “secondary” positions when necessary to fill out the roster) and some minutes constraints based largely on CARMELO’s updating minutes-per-game projections.For that last part, we have developed an in-season playing-time projection similar to the one we use to update our individual offensive and defensive ratings. For each player, CARMELO will project a preseason MPG estimate based on his own history and the record of his similar comparables. We then adjust that during the season by applying a weight of 12.6 games to the preseason MPG projection, added to his current-season minutes and divided by 12.6 plus his current-season games played. (Interestingly, this implies that the amount of weight the MPG prior receives is the same regardless of whether the player is a fresh-faced rookie or a grizzled veteran.)Those minutes are used as the default for our program, which then automatically creates a team’s depth chart and assigns minutes by position according to its sorting algorithm. The defaults, however, can and will be tweaked by our staffers to help the program generate more accurate rosters. For instance, we can mark certain games in which a player is injured, resting, suspended or otherwise unavailable, which will tell the program to ignore that player in the team’s initial rank-ordered list of players before allocating minutes to everyone else. (We also have a method of penalizing a player’s talent ratings if he is forced to play significantly more MPG than his updated CARMELO projection recommends.) New for 2020, there is even a “load management” setting that allows certain stars to be listed under a program of reduced minutes during the regular season.Through this system, we will be able to account for most injuries, trades and other player movement throughout the season on a game-by-game basis.Because of the differences between a team’s talent at full strength and after accounting for injuries, we now list two separate CARMELO ratings on our interactive page: “Current CARMELO” and “Full-Strength CARMELO.” Current is what we’re using for the team’s next game and includes all injuries or rest days in effect at the moment. Full-strength is the team’s rating when all of its key players are in the lineup, even including those who have been ruled out for the season. This will help us keep tabs on which teams are putting out their best group right now, and which ones have room to improve at a later date (i.e., the playoffs) or otherwise are more talented than their current lineup gives them credit for.Game predictionsAs a consequence of the way we can generate separate depth charts for every team on a per-game basis, we can calculate separate CARMELO ratings for the teams in a matchup depending on who is available to play.For a given lineup, we combine individual players’ talent ratings into a team rating on both sides of the ball by taking the team’s average offensive and defensive rating (weighted by each player’s expected minutes) multiplied by 5 to account for five players being on the court at all times. Those numbers are then combined into a generic expected “winning percentage” via the Pythagorean expectation:Winning Percentage=(108+Team Offensive Rating)14(108+Team Offensive Rating)14+(108−Team Defensive Rating)14Winning Percentage=(108+Team Offensive Rating)14(108+Team Offensive Rating)14+(108−Team Defensive Rating)14That number is then converted into its Elo rating equivalent via:CARMELO Rating=1504.6−450×log10((1/Winning Percentage)−1)CARMELO Rating=1504.6−450×log10((1/Winning Percentage)−1)From there, we predict a single game’s outcome the same way we did when CARM-Elo was in effect. That means we not only account for each team’s inherent talent level, but we also make adjustments for home-court advantage (the home team gets a boost of about 92 CARMELO rating points), fatigue (teams that played the previous day are given a penalty of 46 CARMELO points), travel (teams are penalized based on the distance they travel from their previous game) and altitude (teams that play at higher altitudes are given an extra bonus when they play at home, on top of the standard home-court advantage). A team’s odds of winning a given game, then, are calculated via:Win Probability=1/(10−(CARMELO Differential+Bonus Differential)/400+1)Win Probability=1/(10−(CARMELO Differential+Bonus Differential)/400+1)Where CARMELO Differential is the team’s talent rating minus the opponent’s, and the bonus differential is just the difference in the various extra adjustments detailed above.Season simulations and playoff adjustmentsArmed with a list of injuries and other transactions for the entire league, our program can spit out separate CARMELO ratings for every single game on a team’s schedule. For instance, if we know a player won’t be available until midseason, the depth-chart sorting algorithm won’t allow him to be included on a team’s roster — and therefore in the team’s CARMELO ratings — until his estimated return date.Those game-by-game CARMELO ratings are then used to simulate out the rest of the season 50,000 times, Monte Carlo-style. The results of those simulations — including how often a team makes the playoffs and wins the NBA title — are listed in our NBA Predictions interactive when it is set to “CARMELO” mode.It’s important to note that these simulations still run “hot,” like our other Elo-based simulations do. This means that after a simulated game, a team’s CARMELO rating is adjusted upward or downward based on the simulated result, which is then used to inform the next simulated game, and so forth until the end of the simulated season. This helps us account for the inherent uncertainty around a team’s CARMELO rating, though the future “hot” ratings are also adjusted up or down based on our knowledge of players returning from injury or being added to the list of unavailable players.For playoff games, we make a few special changes to the team CARMELO process explained above. For one thing, teams play their best players more often in the playoffs, so our depth-chart algorithm has leeway to bump up a player’s MPG in the postseason if he usually logs a lot of minutes and/or has a good talent rating. This year, CARMELO outputs a separate recommended-minutes-per-game projection for both the regular season and the playoffs.We also have added a feature whereby players with a demonstrated history of playing better (or worse) in the playoffs will get a boost (or penalty) to their offensive and defensive talent ratings in the postseason. For most players, these adjustments are minimal at most, but certain important players — such as LeBron James — will be projected to perform better on a per-possession rate in the playoffs than the regular season. (Truly, he will be in “playoff mode.”)And we continue to give a team an extra bonus for having a roster with a lot of playoff experience. We calculate a team’s playoff experience by averaging the number of prior career playoff minutes played for each player on its roster, weighted by the number of minutes the player played for the team in the regular season. For every playoff game, this boost is added to the list of bonuses teams get for home court, travel and so forth, and it is used in our simulations when playing out the postseason.The complete history of the NBAIf you preferred our old Elo system without any of the fancy bells and whistles detailed above, you can still access it using the NBA Predictions interactive by toggling its setting to the “pure Elo” forecast.This method still has the normal game-level adjustment for home-court advantage, but it doesn’t account for travel, rest or altitude; it doesn’t use a playoff-experience bonus; and it has no knowledge of a team’s roster — it only knows game results. It also doesn’t account for any offseason transactions; instead, it reverts every team ¼ of the way toward a mean Elo rating of 1505 at the start of every season. We use a K-factor of 20 for our NBA Elo ratings, which is fairly quick to pick up on small changes in team performance.You can also still track a team’s Elo rating in our Complete History of the NBA interactive, which shows the ebbs and flows of its performance over time. This number won’t be adjusted for roster changes, but it should remain a nice way to visualize a team’s trajectory throughout its history. Version History4.0 CARMELO updated with the DRAYMOND metric, a playoff adjustment to player ratings and the ability to account for load management. Pure Elo ratings now use a K-factor of 20 in both the regular season and the playoffs.3.1 Estimated overnight ratings added as a stopgap between game results and data updates.3.0 CARMELO is introduced to replace CARM-Elo. Pure Elo ratings are adjusted to have variable K-factors depending on the stage of the season being predicted.2.1 CARM-Elo is modified to include a playoff experience adjustment.2.0 CARM-Elo ratings are introduced. Seasonal mean-reversion for pure Elo is set to 1505, not 1500.1.0 Pure Elo ratings are introduced for teams going back to 1946-47. Related ArticlesThe Complete History Of The NBAHow We Calculate NBA Elo RatingsThe Best NBA Teams Of All Time, According To EloHow Our 2015-16 NBA Predictions WorkWhy The Warriors And Cavs Are Still Big FavoritesFrom The Warriors To The Knicks, How We’re Predicting The 2018-19 NBA
Torrance Gibson checking into the team hotel before 2016 fall camp. Credit: Sheridan Hendrix | Lantern PhotographerJust a week after OSU coach Urban Meyer announced redshirt freshman wide receiver Torrance Gibson had practiced for the first time in 10 days, Gibson has been suspended for the entire 2016 season for a violation of team rules.Gibson took a redshirt last season after injuring his ankle. It was rumored another key factor in the decision to redshirt the former No. 6 athlete in the class of 2015 was problems with Gibson in the classroom.Gibson played in the 2016 spring game for the Gray team scoring twice in his first action in Ohio Stadium.
The Buckeyes got a very important victory on Saturday: 31-13 over Wisconsin. The win was anything but conventional, but it did solidify the Buckeyes as the leaders of the Big Ten.“It was a little bit different ball game than I think any of us anticipated,” coach Jim Tressel said in his weekly press conference. “We knew Wisconsin was a heck of a football team, and we knew we were going to have our hands full.”Once again, the defense led OSU to a comfortable victory by several scores, but offensively the Buckeyes have more questions than answers.OSU (5-1, 3-0) now prepares for the Purdue Boilermakers (1-5, 0-2) on Saturday.Defense comes up big yet againAll season, the Buckeyes’ defense has made plays when necessary. Saturday wasn’t any different.Senior captain Kurt Coleman returned from a one-game suspension and wasted little time returning to form. His 89-yard interception return stopped a driving Badger team and shifted momentum into the Buckeyes’ favor for the remainder of the game. His 14 tackles were also a career high.“The funny thing about it, I was joking with my teammates and they were telling me that because I missed a game I needed to have double the production, and it just so happened that I happened to have double the production. It was a great feeling to come back and help this team, especially in that kind of fashion. I was just happy to be out there playing with my teammates again.”Tressel said the Badgers played up to his expectations, but the Buckeyes “came up with some plays that are game changers.”“Obviously, Kurt Coleman’s play and the pressure that was put on the quarterback, his being where he was supposed to be, and then I thought the execution on the interception return was outstanding,” Tressel said. “You always say when an interception is thrown, if you can block the intended receiver and you can block the quarterback and then get everyone else running down the sideline, you have a chance, and they did that just as you would hope they would do.”OSU got another interception for a touchdown in the second half. With the game still in doubt, junior safety Jermale Hines put the Buckeyes up two touchdowns with a 32-yard interception return.The defense will look to control Purdue’s high-powered offense on Saturday. The Buckeyes have held all but one opponent to under 20 points, including back-to-back shutouts of Toledo and Illinois.Pryor takes a step backAfter having nine touchdowns in the last three games, quarterback Terrelle Pryor saw his production drop significantly against the Badgers.The sophomore completed 5 of 13 passes for only 87 yards with one touchdown and an interception. His one bright spot for the afternoon came right before halftime, when he led the Buckeyes 88 yards for the go-ahead score. A run of 27 yards and a touchdown pass for 32 yards to DeVier Posey were the highlights of the drive.The offense struggled to find a rhythm because of three touchdown by the defensive and special teams. However, OSU would have liked to see more consistency from its quarterback.The problems on offense do not begin and end with one guy, Tressel stressed. The lack of production was an offensive problem, not just a problem with his quarterback.“I think the thing you do with any of us is understand that when things go just right, I probably didn’t do it by myself, and when things didn’t go the way you’d like, it probably didn’t have everything to do with me,” Tressel said.No Boom, only ZoomThe depth at running back is quickly depleting for OSU. Daniel “Boom” Herron did not play against Indiana on Oct. 3 but returned against Wisconsin. Unfortunately for the Buckeyes, he re-injured his ankle and most likely will not be available against the Boilermakers.Freshman Jamaal Berry, who was a prized recruit for the Buckeyes this season, has also been injured. Whether he will make an impact this season remains to be seen.“I’m the eternal optimist. I keep waiting for Jamaal Berry to be healthy because when he’s been healthy, he’s been very, very good,” Tressel said. “Right now, it’s Brandon and Jordan.”Small finally makes large impactSenior wide receiver and returner Ray Small has spent his fair share of time in Tressel’s doghouse. The Glenville product, who many thought would be the next Ted Ginn Jr., has not lived up to expectations, and it was unsure whether he would even play this season.However, when he took a Badger kickoff 96 yards for a touchdown on Saturday, he put defenders and past troubles behind him. He said there is no better feeling than making an impact again.“It means a lot. I play the game as if it’s my last play, no matter if it’s practice or if it’s the game,” Small said. “This year I came in and take it a lot more serious.”Small said he has no regrets and would love to have another big game this weekend to show how far he has come.
Sophomores ruled the day Monday for Ohio State men’s basketball as the Big Ten Conference announced its all-conference selections and awards. Buckeyes’ sophomore forward Jared Sullinger was a first-team Big Ten selection by the coaches and media while sophomore guard Aaron Craft was named Defensive Player of the Year by the conference’s coaches. Sophomore forward Deshaun Thomas was named a second-team All-Big Ten selection by the coaches, and the media and coaches named senior guard William Buford to the second team. Sullinger, who averaged 17 points and nine rebounds per game, was a unanimous selection to the first team for a second consecutive year. Craft’s selection as the defensive player of the year is the first for OSU since 2007 and the fourth in the history of the program. Craft, who was also given a Big Ten Sportsmanship award, told the Big Ten Network that his defensive game benefitted from playing against his older brother as a child. “I couldn’t score on those guys,” Craft said. “I could frustrate them a lot on defense. I got in a couple fights with my brother and some of his friends. So it kind of started back then. Just growing up, (defense) is just something that I’ve enjoyed and I really like doing and understood that that is what is going to help the team the most.” Thomas and Buford both averaged 15 points and five rebounds per game. The Buckeyes (25-6, 13-5 Big Ten) jumped three spots in the latest Associated Press Top 25 poll to the No. 7 spot. OSU defeated Michigan State, 72-70, Sunday on a last-second 2-point shot by Buford. With the win, OSU clinched a three-way tie for the conference’s regular season title with the Spartans and Michigan. Though it conceded an outright regular season conference title with the loss to the Buckeyes, the MSU program came away with some major Big Ten hardware Monday as possible consolation. Spartans senior forward Draymond Green claimed the Big Ten’s Player of the Year award, as well as a unanimous first-team honor from the coaches and media. MSU coach Tom Izzo was a unanimous Coach of the Year honoree. Other award winners include Michigan freshman guard Trey Burke who split Freshman of the Year honors with Indiana forward Cody Zeller. OSU will begin postseason play on Friday at Bankers Life Fieldhouse in Indianapolis, Ind., as the No. 3 seed in the Big Ten Tournament. The Buckeyes will play the winner of Thursday’s Purdue-Nebraska opening-round game. OSU’s postseason will tip at about 9 p.m.
Felix Brych was in the center of attention in Valencia, as he sent off Cristiano Ronaldo and showed three penalties. Miralem Pjanic converted two of them in Juventus’ 2-0 win. Valencia starting lineup: Neto, Ruben Vezo, Gabriel Paulista, Jeison Murillo, Jose Luis Gaya, Daniel Wass, Dani Parejo, Carlos Soler, Goncalo Guedes, Rodrigo, Mitchy Batshuayi Juventus starting lineup: Wojciech Szczesny, Alex Sandro, Giorgio Chiellini, Leonardo Bonucci, Joao Cancelo, Sami Khedira, Blaise Matuidi, Miralem Pjanic, Cristiano Ronaldo, Federico Bernardeschi, Mario MandzukicIn the 11th minute, Mario Mandzukic had a nice chance to score after being left alone at the far post during a cross, but sent the ball over the bar. In the 17th minute, Sami Khedira had an even easier chance to score. Ronaldo sent a great cross with his left foot. Bernardeschi got at the end of it at the far post and sent the ball back to a wide open Khedira in the middle. He could pick and choose where to shoot and somehow managed to miss the entire net. It was a huge opportunity for Juventus, their second in the opening 20 minutes.Gigantic chance number three came in the 21st minute. Neto made a mess of Alex Sandro’s cross. He made a great save on Bernardeschi’s attempt to fix his mistake initially, but then dropped the ball straight to Matuidi. The Frenchman fired a shot which was blocked by an alert Jeison Murillo. Valencia was very lucky to avoid being down. Seconds later, Khedira dropped to the ground complaining of a leg injury. Massimiliano Allegri was forced into making his first change – Emre Can for Sami Khedira.Rumour: Juve put a price on Pjanic George Patchias – August 28, 2019 Juventus have put an 80 million Euro price tag on Miralem Pjanic.According to Tuttosport, and Caliciomercato, the Italian giants are ready to sell there…Tears of anguish were dripping from Cristiano Ronaldo’s face in the 30th minute when he received a shocking red card for patting Murillo on the head. The Colombian was the one who provoked Ronaldo and the Portuguese reacted somewhat angrily, but he didn’t deserve a straight red. It was an incredibly frustrating decision by an experienced referee such as Felix Brych. Where is VAR when you need one?In the 39th minute, Batshuayi stole the ball from Chiellini inside Juve’s box, made a great turn and fired a shot directly at a ready Wojciech Szczesny. Just as Valencia were starting to gain confidence, Juventus took the lead. Another Alex Sandro cross came to a unmarked Joao Cancelo, who missed a volley at first, but then reset himself on the left foot and rocked the cross bar. The rebound was headed away by one of Valencia’s defenders and it came to Parejo, who raised his boot way too high and kicked Cancelo in the face, leaving no choice to Brych but to show on the penalty spot. A really clumsy challenge by The Bats’ captain. Miralem Pjanic took responsibility in the absence of Ronaldo. Neto got a hand on the ball, but it wasn’t enough. Pjanic’s effort was too precise. 1-0 Juventus.In the 50th minute, Brych awarded another penalty to Juventus. This time around, it was a rather generous one. Murillo got tangled with Bonucci during a corner kick, yet the referee saw enough to show on the spot for a second time. Pjanic stepped up and hit the exact same spot again, only this time with even more power. 2-0 Juventus. Ruben Vezo, who was cautioned moments earlier for a foul on Matuidi, was replaced by Denis Cheryshev in the 57th minute. In the 65th minute, Szczesny had to stretch to save Carlos Soler’s long-range effort headed towards the bottom right corner.Following the subsequent corner kick, Douglas Costa replaced Miralem Pjanic. In the 70th minute, Marcelino made two more substitutions, taking off Batshuayi and Guedes and sending Kevin Gameiro and Santi Mina onto the pitch. Juve were doing their best to strangle the life out of the game and they were succeeding. Rodrigo should’ve scored in the 80th minute. Dani Parejo found him from a corner kick, but the Spanish international hit the ball with his shoulder instead of his head. Seconds later, Soler had another attempt on goal go begging.Allegri’s team was defending with ten men behind the ball and blocking every shot Valencia’s players took. Douglas Costa dribbled past Gabriel and stung the hands of Neto in the 85th minute. The Brazilian stayed on the ground following Gabriel’s robust challenge and couldn’t continue. Center back Daniele Rugani was the one who came in his stead. Rodrigo missed another free header in the 93rd minute. Two minutes later, Brych gifted a penalty to Valencia, but Parejo failed to capitalize. The miss summed up a miserable night for the captain and his teammates. After six minutes of stoppage time, the game was over. Marcelino has a lot to think about, as his team was outplayed and beaten by an undermanned Juventus.
Michael Essien expects former Chelsea team-mate Frank Lampard to be in for a big and difficult night on his return to Stamford Bridge with Derby CountyThe former midfielder enjoyed a glorious trophy-laden 13 years with Chelsea over the course of his playing career.But now Lampard will return to Stamford Bridge in charge of his very own side in English Championship team Derby County for a fourth-round Carabao Cup tie.In his first ever campaign as a manager, Lampard has got off to a good start with nine wins in 18 games with Derby in sixth-place in the Championship table.He also notably knocked out his former Chelsea manager Jose Mourinho’s Manchester United team in the previous knockout round and will be hoping for more of the same on Wednesday.Premier League Betting: Match-day 5 Stuart Heath – September 14, 2019 Going into the Premier League’s match-day five with a gap already beginning to form at the top of the league. We will take a…Although while Essien expects a warm welcome for Lampard from the Chelsea fans, he doubts there will be any upsets.“We all know what he did for Chelsea, he is a legend,” Essien told SportsMax. “He’s coming home so it will be a big night.“I’m sure he’s looking to win but it’s not easy at Stamford Bridge.”Lampard is also Chelsea’s all-time record goalscorer with 209 goals in 640 games along with a further 150 assists.The game between Chelsea and Derby will begin on 20:45 (CEST) on Wednesday.
Wreckage believed to be from the ill-fated plane conveying new Cardiff City signing Emiliano Sala has been found on a beach near Surtainville on the Cotentin Peninsula.Investigators said earlier on Wednesday that two seat cushions that had washed up were likely to belong to the aircraft.The Air Accidents Investigation Branch (AAIB) was advised by its French counterparts on Monday that part of a cushion was found on a beach near Surtainville on the Cotentin Peninsula.The AAIB said in a statement obtained via The Mirror:AAIB responds to Sala’s family request to recover the plane’s wreckage Manuel R. Medina – August 14, 2019 The Air Accidents Investigation Branch says they already explained their decision not to recover the plane’s wreckage to Sala’s family and the pilot’s.“From a preliminary examination, we have concluded that it is likely that the cushions are from the missing aircraft.”It went on: “Since we opened our safety investigation on Tuesday 23 January, we have been gathering evidence such as flight, aircraft and personnel records, and have been analyzing radar data and air traffic tapes.“We have been working closely with other international authorities and have kept the families of those involved updated on our progress.”