Get live NHL Stanley Cup playoff updates, news and analysis during Game 4 of the Sharks’ Western Conference Finals series against the St. Louis Blues on Friday at Enterprise Center.Although the Sharks are coming off a thrilling 5-4 overtime victory in Game 3, they are at a loss to know why the Blues and others around the NHL have labeled them as a lucky team. Perhaps it’s because Timo Meier’s hand pass that wasn’t called led to Erik Karlsson’s game-winning goal? In San Jose’s …
Australia has taken out all three divisions, and all nine games, at the 2016 Trans Tasman Series. This is the first time Australia has completed a clean sweep of the whole series. Stay tuned to the website and our social media channels for plenty more highlights from the event. Congratulations to team Australia on this achievement. Mixed OpenGame One – Australia 10 defeated New Zealand 9 Game Two – Australia 4 defeated New Zealand 3Game Three – Australia 8 defeated New Zealand 7Congratulations to the Australian Mixed Open team, 2016 Trans Tasman Series champions. Women’s Open Game One – Australia 7 defeated New Zealand 6Game Two – Australia 6 defeated New Zealand 1Game Three – Australia 6 defeated New Zealand 5Congratulations to the Australian Women’s Open team, 2016 Trans Tasman Series champions. Men’s OpenGame One – Australia 13 defeated New Zealand 7Game Two – Australia 10 defeated New Zealand 6Game Three – Australia 9 defeated New Zealand 5Congratulations to the Australian Men’s Open team, 2016 Trans Tasman Series champions. Watch day one games here. Watch day two games here.Watch day three games here.Australia v JapanEarlier in the week, Australia and Japan met in the Menâ€™s and Womenâ€™s divisions to play two Test Matches in the lead up to the 2016 Trans Tasman Series. Australia vs Japan (Womenâ€™s Open)Game one â€“ Australia 17 defeated Japan 2Game two â€“ Australia 10 defeated Japan 2Australia vs Japan (Menâ€™s Open)Game one â€“ Australia 16 defeated Japan 2Game two â€“ Australia 11 defeated Japan 3Related LinksTrans Tasman results
Touch Football Australia would like to congratulate the following coaches who have been appointed to the Head Coach positions for the 2019 Australian Masters World Cup teams:Men’s 30s Coach: Nick PecchiarMen’s 35s Coach: Karley Banks (pictured)Men’s 40s Coach: Peter VincentMen’s 45s Coach: Chris LothMen’s 50s Coach: Mick McCallWomen’s 27s Coach: Danny GoodwinWomen’s 35s Coach: Mick GraySenior Mixed Coach: Mick McDonald
TagsTransfersAbout the authorPaul VegasShare the loveHave your say Barcelona join AC Milan interest for Man Utd striker Rashfordby Paul Vegas10 months agoSend to a friendShare the loveBarcelona have joined the interest for Manchester United striker Marcus Rashford.The Sunday Express says Barca bosses have compiled a dossier as they court wonderkid Rashford, whose long-term future at Old Trafford is in doubt.Rashford has seen his progress checked over the last season under Jose Mourinho and he has only scored five league goals for United this season.He could look to quit United if he doesn’t kick on under new caretaker boss Ole Gunnar Solskjaer.Barca have been keeping an eye on Rashford and are keen not to lose him to Real if he becomes available.AC Milan are also keen as they want to make a marquee signing this summer.Rashford scored in United’s 5-1 win over Cardiff on Saturday.
Wisconsin senior big man Frank Kaminsky was presented with the Oscar Robertson Trophy this morning as the United States Basketball Writers Association’s top college player. He received the honor during a press conference at the Final Four in Indianapolis. Seated among the small group of reporters covering the event were Kaminsky’s teammates, and two of them decided to get in the spirit of things and ask questions. When the floor was opened up, forward Nigel Hayes took the mic, identified himself as “Badger beat writer, inter-squad team relations,” and fired away, asking Kaminsky what it really means to win the award.The Wisconsin basketball program’s Instagram account has the footage.According to For The Win’s Tanya Sichynsky, forward Sam Dekker also got into the act after Hayes. Finally, an actual Wisconsin beat writer got a turn to speak, and here’s what happened. Nigel Hayes asks the first question, Sam Dekker asks the second question. I go third, and the team boos me.— Jim Polzin (@JimPolzinWSJ) April 3, 2015The Badgers certainly know how to keep seemingly mundane NCAA pressers entertaining, that’s for sure.
fournette congratulates chubbLSU sophomore running back Leonard Fournette dominated Eastern Michigan on Saturday, rushing for 233 yards and three touchdowns on just 23 carries. But afterwards, he actually wanted to talk about another tailback who plays in the SEC.Fournette, in both his post-game press conference and later a tweet, congratulated Georgia running back Nick Chubb for tying Herschel Walker’s record for consecutive 100-yard games in a Bulldogs uniform. Chubb’s 146 yards came in defeat to Alabama. It was the 13th straight time he’s crossed the mark.Via NOLA.com:Congrats to the homie @NickChubb21— 7⃣ (@_fournette) October 4, 2015In just four games, Fournette has 864 rushing yards and 11 touchdowns. If he keeps it up, he’ll be breaking records of his own.
zoomImage Courtesy: Pixabay under CC0 Creative Commons license Japanese shipping company NYK Line has launched preparations to integrate three of its research and technical subsidiaries.The company’s plans would see Japan Marine Science, Yusen Navtec, and NYK Engineering amalgamate on the back of a changing social structure and the business environment surrounding the NYK Group.NYK said it would integrate the management resources of each company to increase efficiencies and create value in accordance with the group’s medium-term management plan ‘Staying Ahead 2022 with Digitalization and Green’.The three research and technical subsidiaries will be amalgamated after approval is received at each company’s general meeting of shareholders in May 2019. The new company is scheduled to be formed on July 1, 2019.The three companies deal with various maritime segments, including maritime consultancy, ship technology, vessel survey and inspection, ships and marine structures, construction and modification, as well as research, development, planning and design of ships and marine structures.
TORONTO – When fans score tickets for events at the Burton Cummings Theatre in Winnipeg in the future, they might notice the absence of a familiar feature: that ubiquitous zebra-styled inventory tracker bar that adorns almost every retail product imaginable.The theatre’s operator, True North Sports and Entertainment, is testing a new Ticketmaster system that gives venues the option to omit barcodes that would usually be scanned to validate a ticket’s authenticity and grant entry to a concert or sporting event.It could be an early sign that the days of the barcode are numbered as technological improvements allow companies to replace them with more secure digital tickets with codes embedded in a fan’s phone or a Wi-Fi connected wristband that lets them track consumers for both security and data-collection purposes.Invented in the 1970s, the barcode was first used to purchase a 67-cent pack of Wrigley’s Juicy Fruit gum, but was quickly adopted in many industries after companies realized it could expedite purchases and assist in tracking inventory.Businesses that are already moving on from the barcode range from Montreal’s Osheaga music festival, which prefers scannable wristbands, to Amazon’s new, cashierless store in Seattle that uses various sensors to detect products customers have in their carts and automatically charge their accounts.One U.K. retail expert recently gave the technology a shelf life of only another five to 10 years.“The barcode’s going to go away,” Ticketmaster’s CEO Michael Rapino reportedly told an audience at a Goldman Sachs investor conference last fall, though he didn’t offer a timeline for the barcode’s demise.His company has stayed fairly quiet about its experiments with ditching the barcode through Ticketmaster Presence — a program that allows venues to let fans scan e-tickets embedded with a digital token instead of a barcode and stored on their phone or smartwatch at self-service terminals to gain entry to events.The entertainment giant wouldn’t name what Canadian venues or artists are looking to experiment with cutting the barcode beyond the Burton Cummings Theatre, which True North Sports and Entertainment’s vice-president of communications, Rob Wozny said has yet to offer a barcodeless show.So far Ticketmaster said 70 venues, including the 25,500-person capacity Orlando City Stadium, have used Presence in North America and more are likely to toy with the program this year as it rolls out further.Ticketmaster started pushing Presence amid its ongoing crusade against bots that buy up large portions of tickets within seconds after they go on sale online and fraudsters that dupe ticket buyers in the resale market by photocopying a ticket numerous times and reselling it to unsuspecting fans who are then denied entry at the door.“That’s bad for everyone involved — venues, clubs, artists, and especially the fans,” Justin Burleigh, Ticketmaster’s executive vice president of product, said in an email.A digital smartphone ticket is supposed to be more difficult to resell on sites and especially outside of concert venues.“(With Presence) there has been zero instances of fraud so far and the tech is succeeding in getting fans into venues to see their favourite live events faster and more efficiently than ever.”Presence not only directs fans to the shortest lines or parking lots with the most empty spaces, but offers a sales and marketing edge because it gives Ticketmaster access to reams of data on eventgoers and their habits.Barcodeless systems also offer the opportunity to lower staffing costs by eliminating the need to scan individual items or tickets, said Norman Shaw, an associate professor at Ryerson University, who studies the cashless society.Shaw said companies are gravitating towards two barcode alternatives: near-field communication (NFC), which is most often seen in tap-and-go credit cards and proximity-based garage entry systems, and radio frequency identification (RFID), which companies can set up to detect which items are leaving their store.“If I have RFID, I have more flexibility, because as soon as it comes in, I know what I have,” said Shaw. “On a store level, it is really important for a retailer to know what they have, rather than having to look at every single item.”For instance, cruiselines use the technology to monitor who gets on and off at ports of call.Companies are using such technologies to track internal movements as well.Retailers with large warehouses have been among the quickest to adopt RFID for use with incoming shipments that are often bundled on large pallets that can be difficult and tedious to comb through, Shaw said.Miners and energy companies, such as Suncor Energy, are using RFID fobs to locate workers without forcing them to scan a barcoded pass as they enter rooms. And manufacturers such as Ford Motor Co. and DeWalt use RFID to help construction and factory workers keep track of tools and equipment.While Shaw believes the proliferation of RFID and NFC will continue, he doesn’t expect retailers to abandon the barcode en masse because most of the alternatives require customers to have a smartphone or rely on the internet, which can have outages.“It doesn’t cover every situation, but it will cover many, many situations,” he said.But as for any notion that the barcode is on its deathbed, he added, “It will take us a long time to get there.”
New Delhi: Delhi Police on Wednesday arrested a member of Khalistan Commando Force from ISBT Delhi on March 12. The accused, identified as 53-year-old Gursewak Singh, was a known associate of infamous militant Jarnail Singh and was wanted in connection with non-bailable warrants issued by the Patiala House Court in two cases when he was arrested.ACP RK Ojha led the team which was formed under the supervision of DCP Bhisham Singh. After the police started technical and manual surveillance, it was revealed that the accused was in contact with some militants currently serving time in Tihar jail. Police said that the team received a secret tip-off from a confidential source about Gursewak’s meeting with one of his associates at ISBT Delhi, when they arrested him. The accused has been known to be involved in over 50 criminal cases including terrorist activities, murder of police officials and informers, bank and police station dacoities, and several robberies in at least four states. Police said that Gursewak joined the Jarnail Singh’s militant organisation in 1982 but when their leader was killed during “Operation Blue Star” in 1984, he joined the newly formed Khalistan Commando Force under the leadership of Manveer Singh Chehdu. In 1985, the accused murdered eight police personnel of Punjab Police while freeing KCF chief Jarnal Labh Singh and his associates from police custody in a court house. The accused spent 18 years in Tihar Jail after being arrested in a case of murdering 9 members of a family in Punjab, from where he planned to smuggle arms and ammunition in large numbers including automatic assault rifles (AK-47) and explosives. This plan, however, was foiled in 1998 by Delhi Police when they apprehended two terrorists from Punjabi Bagh with 18kgs of RDX, eight hand grenades with 10 fuses, an AK-47 with 100 cartridges, and a pistol with five magazines and up to 130 cartridges. Police said that the most recent case against the accused is one registered by the Crime Branch of Delhi Police under the Arms Act in 2017. Additional Commissioner of Police Ajit Kumar added that relevant authorities have been informed regarding the arrest of the accused.
Related ArticlesThe Complete History Of The NFLMay 1, 2018Introducing NFL Elo RatingsSept. 4, 2014The Best NFL Teams Of All Time, According To EloSept. 18, 2015Did The Packers Squander Aaron Rodgers?Dec. 5, 2018The Browns Are A Hot Super Bowl Pick For 2019. (Wait, What?)July 15, 2019 Multiply all of those factors together, and you have the total number of Elo points that should shift from the loser to the winner in a given game. (Elo is a closed system where every point gained by one team is a point lost by another.) Put another way: A team’s postgame Elo is simply its pregame Elo plus or minus the Elo shift implied by the game’s result — and in turn, that postgame Elo becomes the pregame Elo for a team’s next matchup. Circle of life.We also adjust each starting quarterback’s rating based on his performance in the game, adjusting for the quality of the opposing defense. (Read on for more details about how that process works.)Elo does have its limitations. Aside from changes at quarterback, it doesn’t know about trades or injuries that happen midseason, so it can’t adjust its ratings in real time for the absence of an important non-QB player. Over time, it will theoretically detect such a change when a team’s performance drops because of the injury, but Elo is always playing catch-up in that department. Normally, any time you see a major disparity between Elo’s predicted spread and the Vegas line for a game, it will be because Elo has no means of adjusting for key changes to a roster and the bookmakers do. (But this should be much less frequent after the addition of our QB adjustments, since oddsmakers don’t tend to shift lines much — or at all — in response to changes at non-QB positions.)The quarterback adjustmentNew for 2019, we added a way to account for changes in performance — and personnel — at quarterback, the game’s most important position. Here’s how it works:Both teams and individual quarterbacks have rolling ratings based on their recent performance.Performance is measured according to “VALUE,” a regression between ESPN’s Total QBR yards above replacement and basic box score numbers (including rushing stats) from a given game, adjusted for the quality of opposing defenses.The formula for VALUE is: -2.2 * Pass Attempts + 3.7 * Completions + (Passing Yards / 5) + 11.3 * Passing TDs – 14.1 * Interceptions – 8 * Times Sacked – 1.1 * Rush Attempts + 0.6 * Rushing Yards + 15.9 * Rushing TDs.3For seasons before game-level sack logs are complete (pre-1981), the sack term is zeroed out.This metric is also adjusted for opposing defensive quality by computing a rolling rating for team QB VALUE allowed, subtracting league average from the VALUE an opponent usually gives up per game, and using that to adjust a QB’s performance for the game in question. So for example, if a team usually gives up a VALUE 5 points higher than the average team, we would adjust an individual QB’s performance downward by 5 points of VALUE to account for the easier opposing defense. The DetailsFiveThirtyEight has an admitted fondness for the Elo rating — a simple system that judges teams or players based on head-to-head results — and we’ve used it to rate competitors in basketball, baseball, tennis and various other sports over the years. The sport we cut our teeth on, though, was professional football. Way back in 2014, we developed our NFL Elo ratings to forecast the outcome of every game. The nuts and bolts of that system are described below.Game predictionsIn essence, Elo assigns every team a power rating (the NFL average is around 1500). Those ratings are then used to generate win probabilities for games, based on the difference in quality between the two teams involved, plus adjustments for changes at starting quarterback, the location of the matchup (including travel distance) and any extra rest days either team had coming into the contest. After the game, each team’s rating changes based on the result, in relation to how unexpected the outcome was and the winning margin. This process is repeated for every game, from kickoff in September until the Super Bowl.For any game between two teams (A and B) with certain pregame Elo ratings, the odds of Team A winning are:Pr(A)=110−EloDiff400+1Pr(A)=110−EloDiff400+1ELODIFF is Team A’s rating minus Team B’s rating, plus or minus the difference in several adjustments:A home-field adjustment of 55 points at base, depending on who was at home, plus 4 points of Elo for every 1,000 miles traveled. This means the Giants get a 55-point Elo bonus when “hosting” the Jets (despite both teams calling MetLife Stadium home), while the Patriots would get a 65-point Elo bonus when, say, the Chargers come to visit. There is no base home-field adjustment for neutral-site games such as the Super Bowl1Unless a team somehow makes the Super Bowl in its host year. or international games, although the travel-distance adjustment is included for the Super Bowl.A rest adjustment of 25 Elo points whenever a team is coming off of a bye week (including when top-seeded teams don’t play during the opening week of the playoffs). Our research shows that teams in these situations play better than would be expected from their standard Elo alone, even after controlling for home-field effects.A playoff adjustment that multiplies ELODIFF by 1.2 before computing the expected win probabilities and point spreads for playoff games. We found that, in the NFL playoffs, favorites tend to outplay underdogs by a wider margin than we’d expect from their regular-season ratings alone.A quarterback adjustment that assigns every team and each individual QB a rolling performance rating, which can be used to adjust a team’s “effective” Elo upward or downward in the event of a major injury or other QB change. (See below for more details about how this adjustment works.)We also tested effects for weather and coaches (including both head coaches and coordinators) but found that neither improved the predictive value of our model in backtesting by enough to warrant inclusion.Fun fact: If you want to compare Elo’s predictions with point spreads like the Vegas line, you can also divide ELODIFF by 25 to get the spread for the game. Just be sure to include all of the many adjustments above to get the most accurate predicted line.Once the game is over, the pregame ratings are adjusted up (for the winning team) and down (for the loser). We do this using a combination of factors:The K-factor. All Elo systems come with a special multiplier called K that regulates how quickly the ratings change in response to new information. A high K-factor tells Elo to be very sensitive to recent results, causing the ratings to jump around a lot based on each game’s outcome; a low K-factor makes Elo slow to change its opinion about teams, since every game carries comparatively little weight. In our NFL research, we found that the ideal K-factor for predicting future games is 20 — large enough that new results carry weight, but not so large that the ratings bounce around each week.The forecast delta. This is the difference between the binary result of the game (1 for a win, 0 for a loss, 0.5 for a tie) and the pregame win probability as predicted by Elo. Since Elo is fundamentally a system that adjusts its prior assumptions based on new information, the larger the gap between what actually happened and what it had predicted going into a game, the more it shifts each team’s pregame rating in response. Truly shocking outcomes are like a wake-up call for Elo: They indicate that its pregame expectations were probably quite wrong and thus in need of serious updating.The margin-of-victory multiplier. The two factors above would be sufficient if we were judging teams based only on wins and losses (and, yes, Donovan McNabb, sometimes ties). But we also want to be able to take into account how a team won — whether they dominated their opponents or simply squeaked past them. To that end, we created a multiplier that gives teams (ever-diminishing) credit for blowout wins by taking the natural logarithm of their point differential plus 1 point.MovMultiplier=ln(WinnerPointDiff+1)×2.2WinnerEloDiff×0.001+2.2MovMultiplier=ln(WinnerPointDiff+1)×2.2WinnerEloDiff×0.001+2.2This factor also carries an additional adjustment for autocorrelation, which is the bane of all Elo systems that try to adjust for scoring margin. Technically speaking, autocorrelation is the tendency of a time series to be correlated with its past and future values. In football terms, that means the Elo ratings of good teams run the risk of being inflated because favorites not only win more often, but they also tend to put up larger margins in their wins than underdogs do in theirs. Since Elo gives more credit for larger wins, this means that top-rated teams could see their ratings swell disproportionately over time without an adjustment. To combat this, we scale down the margin-of-victory multiplier for teams that were bigger favorites going into the game.2Special note: In the case of a tie, the multiplier becomes 1.525, or 2.2 times the natural log of 2 (which, based on the formula above, effectively assumes the absolute margin of victory in any game must be at least 1). The rolling rating represents the VALUE we’d expect a quarterback (whether at the individual or team level) to produce against a passing defense of average quality in the next start. To convert between VALUE and Elo, the rolling rating can be multiplied by 3.3 to get the number of Elo points a QB is expected to be worth compared with an undrafted rookie replacement. Preseason QB ratings are also assigned at the team level. These consist of one-third weight given to the team’s previous end-of-season rolling QB rating and two-thirds weight given to the preseason rolling rating of the team’s projected top starter.Pregame and preseason ratingsSo all of that is how Elo works at the game-by-game level and what goes into our quarterback adjustments. But where do teams’ preseason ratings come from, anyway?We use two sources to set teams’ initial ratings going into a season:At the start of each season, every existing team carries its Elo rating over from the end of the previous season, except that it is reverted one-third of the way toward a mean of 1505. That is our way of hedging for the offseason’s carousel of draft picks, free agency, trades and coaching changes. We don’t currently have any way to adjust for a team’s actual offseason moves, aside from changes at quarterback, but a heavy dose of regression to the mean is the next-best thing, since the NFL has built-in mechanisms (like the salary cap) that promote parity, dragging bad teams upward and knocking good ones down a peg or two.For seasons since 1990, we also use Vegas win totals to help set preseason Elo ratings, converting over-under expected wins to an Elo scale. (This addition to the model helped significantly improve predictive accuracy in backtesting, by a little more than half the improvement that adding the QB adjustment did.) As a side note, this is partly why we mix the projected startIng QB’s rolling rating into the preseason team QB rating — we assume that changes at quarterback are “baked into” Vegas over/unders and must be adjusted for to avoid double-counting the improvement added by an upgrade at QB.These two factors are combined, with one-third weight given to regressed Elo and two-thirds weight given to Vegas-wins Elo. This blend is what forms a team’s preseason Elo rating.Note that I mentioned “existing” teams when mentioning end-of-season ratings from the previous year. Expansion teams have their own set of rules. For newly founded clubs in the modern era, we assign them a rating of 1300 — which is effectively the Elo level at which NFL expansion teams have played since the 1970 AFL merger. We also assigned that number to new AFL teams in 1960, letting the ratings play out from scratch as the AFL operated in parallel with the NFL. When the AFL’s teams merged into the NFL, they retained the ratings they’d built up while playing separately.For new teams in the early days of the NFL, things are a little more complicated. When the NFL began in 1920 as the “American Professional Football Association” (they renamed it “National Football League” in 1922), it was a hodgepodge of independent pro teams from existing leagues and opponents that in some cases were not even APFA members. For teams that had not previously played in a pro league, we assigned them a 1300 rating; for existing teams, we mixed that 1300 mark with a rating that gave them credit for the number of years they’d logged since first being founded as a pro team.InitRating=1300×23YrsSince1stSeason+1505×(1−23)YrsSince1stSeasonInitRating=1300×23YrsSince1stSeason+1505×(1−23)YrsSince1stSeasonThis adjustment applied to 28 franchises during the 1920s, plus the Detroit Lions (who joined the NFL in 1930 after being founded as a pro team in 1929) and the Cleveland Rams (who joined in 1937 after playing a season in the second AFL). No team has required this exact adjustment since, although we also use a version of it for historical teams that discontinued operations for a period of time.Not that there haven’t been plenty of other odd situations to account for. During World War II, the Chicago Cardinals and Pittsburgh Steelers briefly merged into a common team that was known as “Card-Pitt,” and before that, the Steelers had merged with the Philadelphia Eagles to create the delightfully monikered “Steagles.” In those cases, we took the average of the two teams’ ratings from the end of the previous season and performed our year-to-year mean reversion on that number to generate a preseason Elo rating. After the mash-up ended and the teams were re-divided, the Steelers and Cardinals (or Eagles) received the same mean-reverted preseason rating implied by their combined performance the season before.And I would be remiss if I didn’t mention the Cleveland Browns and Baltimore Ravens. Technically, the NFL considers the current Browns to be a continuation of the franchise that began under Paul Brown in the mid-1940s. But that team’s roster was essentially transferred to the Ravens for their inaugural season in 1996, while the “New Browns” were stocked through an expansion draft in 1999. Because of this, we decided the 1996 Ravens’ preseason Elo should be the 1995 Browns’ end-of-year Elo, with the cross-season mean-reversion technique applied, and that the 1999 Browns’ initial Elo should be 1300, the same as any other expansion team.Season simulationsNow that we know where a team and quarterback’s initial ratings for a season come from and how those ratings update as the schedule plays out, the final piece of our Elo puzzle is how all of that fits in with our NFL interactive graphic, which predicts the entire season.At any point in the season, the interactive lists each team’s up-to-date Elo rating (as well as how that rating has changed over the past week and how any changes at QB alter the team’s effective Elo), plus the team’s expected full-season record and its odds of winning its division, making the playoffs and even winning the Super Bowl. This is all based on a set of simulations that play out the rest of the schedule using Elo to predict each game.Specifically, we simulate the remainder of the season 100,000 times using the Monte Carlo method, tracking how often each simulated universe yields a given outcome for each team. It’s important to note that we run these simulations “hot” — that is, a team’s Elo rating is not set in stone throughout the simulation but changes after each simulated game based on its result, which is then used to simulate the next game, and so forth. This allows us to better capture the possible variation in how a team’s season can play out, realistically modeling the hot and cold streaks that a team can go on over the course of a season.Our simulations also project which quarterback will start each game by incorporating injuries, suspensions and starters being rested. For example, we might know that a quarterback is out for Weeks 1 and 2 but back for certain in Week 3. Or our forecast might have some uncertainty around a quarterback’s injury and project that he has only a 10 percent chance of playing next week but a 50 percent chance of playing the following week, and so on. In cases where we don’t know for sure which quarterback will start a game, the team’s quarterback adjustment is a weighted average of the possible starting quarterback adjustments.Late in the season, you will find that the interactive allows you to experiment with different postseason contingencies based on who you have selected to win a given game. This is done by drilling down to just the simulated universes in which the outcomes you chose happened and seeing how those universes ultimately played out. It’s a handy way of seeing exactly what your favorite team needs to get a favorable playoff scenario or just to study the ripple effects each game may have on the rest of the league.The complete history of the NFLIn conjunction with our Elo interactive, we also have a separate dashboard showing how every team’s Elo rating has risen or fallen throughout history. These charts will help you track when your team was at its best — or worst — along with its ebbs and flows in performance over time. The data in the charts goes back to 1920 (when applicable) and is updated with every game of the current season.An important disclaimer: The historical interactive ratings will differ from the ratings found in our current-season prediction interactive because the historical ratings do not contain our quarterback adjustments. (If you’re interested in looking at the historical QB adjustment data, it’s available on our data homepage.) The quarterback Elo adjustment is applied before each game by comparing the starting QB’s rolling VALUE rating with the team’s rolling rating and multiplying by 3.3.For example: when Aaron Rodgers was injured midway through the 2017 season, he had a rolling VALUE rating of 66. The Green Bay Packers’ team rolling VALUE rating was 68, and backup Brett Hundley had a personal rating of 14. So when adjusting the Packers’ Elo for their next game with Hundley starting instead of Rodgers, we would have applied an adjustment of 3.3 * (14 – 68) = -1764After rounding. to Green Bay’s base Elo rating of 1586 heading into its Week 7 game against the Saints. This effectively would have left the Packers as a 1409 Elo team with Hundley under center (before applying adjustments for home field, travel and rest), dropping Green Bay’s win probability from 63 percent to 39 percent for the game despite playing at home. In cases like these, the QB adjustment can have a massive effect! Version History2.0Quarterback adjustments are added, along with special adjustments for travel distance, bye weeks and playoff rating spreads.Sept. 4, 20191.1Ratings are extended back to 1920, with a new rating procedure for expansion teams and other special cases. Seasonal mean-reversion is set to 1505, not 1500.Sept. 10, 20151.0Elo ratings are introduced for the current season; underlying historical numbers go back to 1970.Sept. 4, 2014 ReferencesPro-Football-Reference.comAutocorrelation / Elo rating / Monte Carlo simulations / Regression to the mean / ESPN’s Total Quarterback Rating You can track these quarterback ratings on a team-by-team and division-by-division basis using this interactive page, which shows the relative quality of every QB in the league. The average team QB VALUE rating going into the 2019 season was about 49.5 (or about 163 Elo points), a leaguewide number that has increased substantially over the history of the NFL as passing has become more prevalent and efficient. So a rolling rating that would have made a QB one of the best in football in the 1990s would rank as only average now, even though the zero-point in our ratings remains the replacement-level performance of an undrafted rookie starter.One last note on these ratings involves how they are set initially. We’ll explain preseason team Elo ratings below, but here is how preseason ratings are set for the quarterback adjustment:Before a season, each starting quarterback is assigned a preseason rating based on either his previous performance or his draft position (in the case of rookies making their debut start).For veterans with between 10 and 100 career starts, we take their final rating from the end of the previous season and revert it toward the rating of the average NFL QB start by one-fourth before the following season.For players with fewer than 10 or more than 100 starts, we don’t revert their ratings at all.For rookies making their starting debuts, we assign them initial ratings based on draft position. An undrafted rookie is always assigned a rating of zero for his first start. The first overall pick, by comparison, gets a rating of +113 Elo points before his first start. Model CreatorsNate Silver The founder and editor in chief of FiveThirtyEight. | @natesilver538Jay Boice A computational journalist for FiveThirtyEight. | @jayboiceNeil Paine A senior sportswriter for FiveThirtyEight. | @Neil_Paine For individual QBs, the rolling rating is updated every 10 games. (i.e., Rating_new = 0.9 * Rating_old + 0.1 * Game_VALUE ).For teams, the rolling rating is updated every 20 games.This implies that short-term “hot” and “cold” streaks by individual QBs have predictive value, which can trigger a nonzero pregame QB adjustment even when a team has had the same starter for each of its previous 20 games.