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  • Birthday April 18

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    Leningrad -> Tel-Aviv -> San Jose
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    Sharks
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  1. Ever since I started collecting the NHL data it was very important to me to validate the collected information. So I created a set of checks that finally formed a whole library to test both the NHL boxscore feeds and the HTML reports. I managed to fish out quite a few errors and inconsistencies. Some where systemic, and could be fixed in software, some required a manual intervention, sometimes by editing the source file, sometimes by providing the correct value overriding what the parser would read. These interventions, classified into a variety of types, formed another library. But I also wanted to share the errors that I found and the fixes I figured out with the analytics community. So I decided to create a website dedicated to it. It took a while, but finally a couple of days ago I was able to open NHLErrata.com. There you can find: An overview of data sources. Information on missing players and events Information of broken reports, players and events Systemic problems encountered with the reports Both mentioned libraries, Test.pm and Errors.pm are part of my scrape-to-database package on CPAN.
  2. After a period of deep dormancy we welcome the 2018/19 on our website with three major changes: 1. MoreHockeyStats is now a network of sites: MoreHockeyStats.com - the unusual statistics from the NHL for the league, the teams, the players, the coaches and the draft. HockeyEloRatings.com - the Elo ratings for teams, coaches and players, in general and for particular stats and situations. NHLErrata.com - the errors we discovered while crawling and testing the NHL data. 2. All our data is now available through a sort of API. When a table is displayed, there is a set of links on how you can access the data: JSON - receive the data displayed in the table as a JSON via direct link. CSV - receive the data in a CSV table. Table - display the data as a pure HTML table with a direct link. Link - direct link to the results displayed. These links have a systemic structure and thus can be crawled by a bot. 3. Most of our tables now feature links to personal cards for teams, players, coaches and even the rinks. These cards display the visual changes to the stat displayed in the table for the particular team, player etc. We welcome ideas for the cards in the pages that do not have these cards yet. Here's a sample playercard: Welcome, and have a great 2018/19 hockey season.
  3. First of all, I think everyone is watching whether the Flames will be able to secure the deal for the new stadium. If not, then to Houston, or KC, or elsewhere in the Central they will go. Second, the league may just swap Arizona out into Central. Third, the league may relocate Arizona somewhere, too. I can't believe Bettman will run a 9+7+8+8 league, even the MLB gave up on such a disbalance. In a very long shot, however, I can see an NFL-like setup with 8 divisions: * VAN, EDM, CGY, SEA * SJS, ANA, LAK, VGK * WPG, MIN, CHI, STL * ARI, COL, DAL, NSH (crazy travel) ----------------------------------- * BOS, MTL, OTT, TOR * BUF, NJD, NYR, NYI * PIT, PHI, DET, CBJ * WSH, CAR, TBL, FLA 8 division winners and 2x4 best teams in each conference qualify. Schedule: In your own division: 4x3 = 12 games Outside your division, select division, rotates: 4x4 = 16 games Outside your division: 3x8 = 24 games Outside conference: 2x16 = 32 games Total: 84 games, too.
  4. It would rather be Interconference: 2x16 = 32 Intraconference, Interdivision: 3x8 = 24 Intraconference, Intradivision: 4x7 = 28 For the total of 84, where they already had been some time ago.
  5. Website A Page - A Day, Part VI - Warm Welcome Original post Prologue Part I Part II Part III Part IV Part V With nothing else to do for about half an hour, why not to resume the series? Have you wondered if it is your team, or your goalie, who always has the first career goal scored against them? Now you can check if your feeling is right. On the page 'Warm Welcome' of the League section on the website we present a look at the first goals scored against different teams and goalies. With the two left items in the top menu you can select the span over which you want to see the statistics. Want one season only? Select the same season for the start and for the end. Then you can toggle the view by the team or the goalie the first goal is scored against. For example, for the 2016/17 season, team view: # Team Goals Allowed 1 Dallas Stars 7 2 Carolina Hurricanes 7 3 New Jersey Devils 7 4 Tampa Bay Lightning 6 5 Ottawa Senators 6 6 Detroit Red Wings 5 7 Pittsburgh Penguins 5 8 New York Rangers 5 9 San Jose Sharks 5 10 Vancouver Canucks 5 11 Colorado Avalanche 5 12 Nashville Predators 4 13 Boston Bruins 4 14 Buffalo Sabres 4 15 Winnipeg Jets 4 16 Arizona Coyotes 3 17 Columbus Blue Jackets 3 18 Edmonton Oilers 3 19 Montreal Canadiens 3 20 Anaheim Ducks 3 21 St. Louis Blues 3 22 Los Angeles Kings 2 23 Washington Capitals 2 24 Calgary Flames 2 25 Minnesota Wild 2 26 New York Islanders 2 27 Toronto Maple Leafs 2 28 Chicago Blackhawks 2 29 Florida Panthers 2 30 Philadelphia Flyers 0 Take a look. You might be surprised. Or not.
  6. Original post. Part I After completing the first part of the lemma research - penalty box - the second part was shorter, easier, but just as useful. I decided to find out the share of time teams spend on average while at even strength, on power play/shorthanded and with empty net. Then given this number, and the number of goals scored in each such situation, I was able to calculate the frequency of EVG/PPG/SHG/ENG or the reverse of it which I called the difficult of such goal. I scanned the database of all games between the 1999/00 season and today, and all the goals extracted from these games. Penalty shot goals were ignored, regardless if during the game itself, or in post-game shootout. The EN time was calculated as total game time minus goaltender TOI. PP/SH time was deducted from the recorded PP TOI of the players. The EV time would naturally become the total game time minus EN minus PP of both teams. Then I calculated the difficulty of scoring a goal in each of these situations through the following formula: DiffTYPE = ( GOALSEV / GOALSTYPE ) x ( TOITYPE / TOIEV ) where the difficulty of the EV goal is considered "1". Here are the combined results of the difficulties in a table: Season EV PP SH EN 1999 1.000 0.502 3.506 0.162 2000 1.000 0.473 3.387 0.146 2001 1.000 0.492 3.635 0.153 2002 1.000 0.468 3.585 0.167 2003 1.000 0.445 3.127 0.221 2005 1.000 0.535 4.247 0.272 2006 1.000 0.506 4.000 0.228 2007 1.000 0.458 3.597 0.187 2008 1.000 0.438 3.745 0.183 2009 1.000 0.456 4.044 0.192 2010 1.000 0.450 3.517 0.177 2011 1.000 0.460 3.568 0.169 2012 1.000 0.430 3.890 0.169 2013 1.000 0.453 3.209 0.198 2014 1.000 0.427 3.564 0.171 2015 1.000 0.415 3.284 0.158 2016 1.000 0.419 3.252 0.178 2017 1.000 0.427 3.052 0.168 If you divide 1 by these values you can get the relative frequency of goals scored in each situation. The dataset containing this data is available on the website, on the Request Analysis page. So why did I need these two lemmas? That blog post won't be ready any time soon, and I better resume the "Page A Day series'.
  7. Original post Nothing derails from the regular blogging like a research that you've been so eager to start, but were putting off to finish simpler and more materialistic stuff, but then you couldn't hold it off any longer.But then, I realized that in order to do that research I need to perform a lemma research. Just like its mathematical namesake, a lemma research is one that is done for the sake of a bigger one, yet producing a useful result by itself.So I noticed that I needed the penalty box data. Who was in the penalty box during a power play goal? More specifically, who was responsible for that goal, i.e. who left the penalty box as the result (or had a non-matched 5-minute major penalty during it). Once there was a feed that had penalty box data, but it was only since 2010 or so, and it seems to have become discontinued. Therefore I gathered the game data I already had and just went through the power play goals from 1987/88 through now, and tried to match them with penalties, while weeding out all the cancelling and all the irrelevant (e.g. misconduct) ones.I am glad to tell that I was able to create a consistent, at least at first look, dataset. But before that I had to go in and correct penalty box entries for about 160 goals manually. About 35 of them were just forced to enter the penalty data manually, because any algorithm assigning the player in the box to the goal would be ambiguous. However I also discovered about 125 goals (120 pre 1999/00, when extra reports were introduced, and only five since) that should not even be marked as power play goals. There was no matching penalty. Of course, the mistake can be on the penalty data in the NHL report: the time of the penalty may be reported wrongly. But until further notice, these goals should not be considered PPG: GameID P Time Scorer Team 198720125 3 9:19 BOB SWEENEY Boston Bruins 198720134 3 18:58 RICK TOCCHET Philadelphia Flyers 198720239 1 1:23 STEPHANE RICHER Montreal Canadiens 198720367 1 4:51 DALE HAWERCHUK Winnipeg Jets 198720388 1 17:46 TROY MURRAY Chicago Blackhawks 198720389 3 3:55 PAUL MACLEAN Winnipeg Jets 198720431 2 6:56 PETER TAGLIANETTI Winnipeg Jets 198720449 2 12:34 MIKKO MAKELA New York Islanders 198720471 3 10:51 ANTON STASTNY Quebec Nordiques 198720484 2 13:38 MARIO LEMIEUX Pittsburgh Penguins 198720528 1 6:32 CHARLIE SIMMER Pittsburgh Penguins 198720610 3 3:08 LAURIE BOSCHMAN Winnipeg Jets 198720735 3 8:10 MIKE FOLIGNO Buffalo Sabres 198720755 1 3:06 GARRY GALLEY Washington Capitals 198720755 2 0:29 GERALD DIDUCK New York Islanders 198720787 1 17:02 AARON BROTEN New Jersey Devils 198720799 2 0:49 JIMMY CARSON Los Angeles Kings 198720802 2 3:24 MIKE FOLIGNO Buffalo Sabres 198720804 1 18:03 PAT VERBEEK New Jersey Devils 198730134 1 7:52 BRUCE DRIVER New Jersey Devils 198730223 3 9:47 MARK JOHNSON New Jersey Devils 198730314 2 12:31 CAM NEELY Boston Bruins 198820088 2 6:17 RANDY MOLLER Quebec Nordiques 198820088 2 7:11 ANTON STASTNY Quebec Nordiques 198820147 1 15:58 JOHN CULLEN Pittsburgh Penguins 198820150 2 2:29 KEVIN DINEEN Hartford Whalers 198820203 3 12:45 JOE MULLEN Calgary Flames 198820241 2 18:53 DAN QUINN Pittsburgh Penguins 198820307 3 10:12 MARIO LEMIEUX Pittsburgh Penguins 198820318 2 5:24 GAETAN DUCHESNE Quebec Nordiques 198820331 3 7:36 PAUL GAGNE Toronto Maple Leafs 198820489 1 16:20 DALE HUNTER Washington Capitals 198820542 1 18:13 DOUG EVANS St. Louis Blues 198820727 3 7:49 PAUL MACLEAN Detroit Red Wings 198820803 2 6:58 DOUG SMITH Vancouver Canucks 198820821 3 17:43 BRENT FEDYK Detroit Red Wings 198920146 1 5:14 KEVIN DINEEN Hartford Whalers 198920158 1 5:26 TROY MURRAY Chicago Blackhawks 198920220 2 15:53 NEAL BROTEN Minnesota North Stars 198920238 1 2:39 GREG PASLAWSKI Winnipeg Jets 198920303 2 4:55 PAT ELYNUIK Winnipeg Jets 198920475 3 8:25 BRIAN MULLEN New York Rangers 198920543 3 18:46 AL MACINNIS Calgary Flames 198920667 1 3:04 JEREMY ROENICK Chicago Blackhawks 198920749 1 8:18 CRAIG JANNEY Boston Bruins 198920818 2 1:25 JOHN OGRODNICK New York Rangers 198930231 2 13:43 TRENT YAWNEY Chicago Blackhawks 198930322 2 18:01 JARI KURRI Edmonton Oilers 199020005 3 19:54 RAY SHEPPARD New York Rangers 199020056 1 15:44 DAVE TAYLOR Los Angeles Kings 199020262 2 11:20 BOBBY HOLIK Hartford Whalers 199020612 3 7:18 JOHN CHABOT Detroit Red Wings 199020636 1 15:02 BRIAN LEETCH New York Rangers 199020647 2 9:16 KENNETH JR HODGE Boston Bruins 199020704 2 12:47 KELLY KISIO New York Rangers 199020716 3 0:34 JOE SAKIC Quebec Nordiques 199020762 2 5:16 MARK RECCHI Pittsburgh Penguins 199020815 2 19:28 KEVIN STEVENS Pittsburgh Penguins 199030222 3 2:17 DINO CICCARELLI Washington Capitals 199030235 3 14:04 BRIAN PROPP Minnesota North Stars 199120059 3 2:20 DOUG GILMOUR Calgary Flames 199120070 2 10:26 DAVE GAGNER Minnesota North Stars 199120093 3 18:48 DARREN TURCOTTE New York Rangers 199120238 3 0:18 PAUL RANHEIM Calgary Flames 199120313 3 11:52 JEREMY ROENICK Chicago Blackhawks 199120407 1 10:39 BOBBY CARPENTER Boston Bruins 199120504 2 18:42 JIMMY CARSON Detroit Red Wings 199120617 2 16:43 MARTY MCSORLEY Los Angeles Kings 199120625 3 18:17 TODD ELIK Minnesota North Stars 199120638 1 13:15 GREG ADAMS Vancouver Canucks 199120755 3 10:48 DOUG GILMOUR Toronto Maple Leafs 199130143 3 13:57 AL IAFRATE Washington Capitals 199220002 2 5:17 SCOTT STEVENS New Jersey Devils 199220013 1 12:08 RICK TOCCHET Pittsburgh Penguins 199220023 2 17:32 MARIO LEMIEUX Pittsburgh Penguins 199220068 2 17:22 MIKE GARTNER New York Rangers 199220091 3 19:34 JOE JUNEAU Boston Bruins 199220121 1 6:14 MIKE GARTNER New York Rangers 199220149 2 18:44 CHRIS KONTOS Tampa Bay Lightning 199220181 3 6:21 ULF DAHLEN Minnesota North Stars 199220287 1 16:56 CHRIS KONTOS Tampa Bay Lightning 199220337 2 5:42 ALEXANDER MOGILNY Buffalo Sabres 199220388 1 15:45 GREG HAWGOOD Edmonton Oilers 199220401 2 12:48 JEFF NORTON New York Islanders 199220562 3 9:19 CHRIS KONTOS Tampa Bay Lightning 199220563 1 9:25 TEPPO NUMMINEN Winnipeg Jets 199220589 3 9:18 ROD BRIND'AMOUR Philadelphia Flyers 199220595 1 7:20 CRAIG JANNEY St. Louis Blues 199220908 2 16:28 VALERI KAMENSKY Quebec Nordiques 199220986 1 15:44 JIRI SLEGR Vancouver Canucks 199320065 1 15:37 DENIS SAVARD Tampa Bay Lightning 199320092 3 11:22 SERGEI FEDOROV Detroit Red Wings 199320636 1 16:40 TIM SWEENEY Mighty Ducks Of Anaheim 199320643 3 16:50 MARTIN LAPOINTE Detroit Red Wings 199320740 2 7:53 KEITH TKACHUK Winnipeg Jets 199320840 1 17:17 SERGEI ZUBOV New York Rangers 199320905 3 18:16 KEVIN STEVENS Pittsburgh Penguins 199420025 2 1:32 KELLY BUCHBERGER Edmonton Oilers 199420072 2 7:27 STEVE THOMAS New York Islanders 199420087 1 9:52 KEITH TKACHUK Winnipeg Jets 199420332 2 2:35 GRANT LEDYARD Dallas Stars 199420332 2 7:11 RAY SHEPPARD Detroit Red Wings 199520189 2 15:41 LUC ROBITAILLE New York Rangers 199520226 3 17:34 CHRIS GRATTON Tampa Bay Lightning 199520490 2 9:41 TODD BERTUZZI New York Islanders 199520539 3 13:25 MARK MESSIER New York Rangers 199520560 1 9:03 VYACHESLAV KOZLOV Detroit Red Wings 199520694 3 15:43 RON FRANCIS Pittsburgh Penguins 199520744 2 6:41 SCOTT MELLANBY Florida Panthers 199520750 2 9:05 NICKLAS LIDSTROM Detroit Red Wings 199520766 1 16:00 BENOIT HOGUE Dallas Stars 199520776 2 5:53 MARIO LEMIEUX Pittsburgh Penguins 199520809 1 12:47 ADAM GRAVES New York Rangers 199520847 2 16:40 KEITH PRIMEAU Detroit Red Wings 199620127 3 12:03 ALEXEI ZHAMNOV Chicago Blackhawks 199620211 2 13:08 GREG ADAMS Dallas Stars 199620466 3 14:50 JOZEF STUMPEL Boston Bruins 199620792 1 11:50 BRENDAN SHANAHAN Detroit Red Wings 199621058 2 1:41 MARTIN GELINAS Vancouver Canucks 199720028 2 18:01 TREVOR LINDEN Vancouver Canucks 199720067 3 16:29 TERRY YAKE St. Louis Blues 199920756 1 6:46 JAMIE LANGENBRUNNER Dallas Stars 200520486 1 17:28 ROB COLLINS New York Islanders 200620150 1 7:59 NATHAN HORTON Florida Panthers 200620627 1 5:00 RYANE CLOWE San Jose Sharks 200821010 1 16:44 MIKAEL SAMUELSSON Detroit Red Wings 201620276 2 12:03 JOHAN LARSSON Buffalo Sabres The resulting penalty box data is available on our website, in the Request Analysis section.Hopefully, tomorrow, I'll blog about another useful dataset the lemma research has produced.
  8. ProloguePart IPart IIPart IIIPart IVOriginal Post Well, the pace didn't last long, but we're back with Part V - Rink Repair StatisticsProbably, this is the least hockey related page of the website, but hey, we can do it, and it's actually pretty easy, so why not?The STOP events as listed in the Play-By-Play HTML summaries since the 2002/03 season on the NHL.com website contain the reason(s) for the stop. While most of them are game-based, such as ICING or OFFSIDE, one of the more rare ones caught our eye: RINK REPAIR. We decided to collect these stops and rank NHL home teams as well as NHL arenas by the amount of rink repairs that happened. We filter out the occasional venues, such as outdoor stadiums for NHL special events or the foreign arenas for the European showdown games.Since we already parse practically all events from the Play-By-Play summaries (or PL), and classify them by types, we already have a collection of STOP events. And we also detect and catalog the reasons for the stoppages, so it is an easy Mongo query to extract all rink repairs incurred. We then aggregate them by locations and teams, and create SQL tables for easy quick display of the data.And so we were able to assemble a nice set of tables displaying the level of maintenance in the rinks around the league. Here's a look at the 2016/17 season: Arena Repairs BARCLAYS CENTER 8 XCEL ENERGY CENTER 3 CANADIAN TIRE CENTRE 2 VERIZON CENTER 2 PEPSI CENTER 2 FIRST NIAGARA CENTER 2 NATIONWIDE ARENA 2 CENTRE BELL 2 WELLS FARGO CENTER 1 SCOTTRADE CENTER 1 ROGERS ARENA 1 REXALL PLACE 1 PRUDENTIAL CENTER 1 CONSOL ENERGY CENTER 1 BB&T CENTER 1 JOE LOUIS ARENA 1 HONDA CENTER 1 So the claims that the Islanders' current home has the worst ice has been substantial. For the last three years, actually, Barclays Center ranks among highest. Naturally, the old arenas like Canadian Tire Centre or Rexall Palace also seemed to get a lot of rink repairs during the games. You can switch the year of the display or the mode between 'By Team' and 'By Arena'. As with all the displayed tables on our site, there are links below it to see it in a pristine form, the direct link to the page for the selected season, and buttons to share it on Twitter and Facebook. Once again, it doesn't seem like a highly meaningful piece of work, but we consider it fun, and it took about quarter an hour to implement altogether. TODO: Aggregate show by a period rather than a single season Include arena ages (requires manual input of construction years)
  9. Well, there are two graph/graph-like pages. One is the one referred in this post, another one is West vs. East (see next blog post ) I can't pay for the services, sorry. Thanks for the offer, though. Credit or data is the only compensation I can suggest.
  10. ProloguePart IPart IIPart IIIAnd now we're putting two in a row with West vs. East.PART IVThis page shows the results of games between Eastern and Western Conference teams. The data is available from the year 1993, when Western and Eastern Conference were formed, from the Boxscore files.Shown from left to right: Regular West wins OT/SO West wins Ties(up to year 2005) OT/SO East wins Regular East wins Stanley Cup Winning Conference A total tally is available as well. As of the date of this post the standings are:WEST 2802 Reg. W - 595 OTW - 444 T - 541 Reg. W - 2570 Reg. W EASTWest holds a formidable lead which eroded a bit in the 2015/16 and 2016/17 seasons. Before that the last time East won the count was back in 1998/99! The 2009/10 was the most lopsided season with the final score of 155-115 in West's favor.West won 14 times, East - 6. Once, in 2011/12 there was a tie with 134 wins apiece.The Stanley Cup winners are divided more evenly, however, with West holding the edge 13-10.There is no data for seasons 1994/95, 2004/05 and 2012/13 because of full or or partial season lockout. Also, the win-loss count from the Finals are not included.WE NEED YOUR HELP!If you are an experienced Webmaster, especially with Javascript and CSS we would greatly appreciate the potential tidy-up and enrichment you could provide to these graphs. Your work will be credited for future reference! Write to us, or get in touch with us on Twitter. Thanks!Possible future additions: Season aggregation More compact design Your ideas are welcome!
  11. Hey, and thanks for the interest. I'd like to have the graph more responsive, like showing the actual number on the bar when the mouse goes over. Also in the screens with composite stacked bars, I'd love to have the ability to have the components as checkboxes, and toggle them on/off on the graphs when necessary. And, of course, any advice, and for overall design as well, is welcome.
  12. Despite all the delays we move on to League's Yearly Tendencies.PART IIIThis view shows stacked bars of various event counts per season in the NHL.All the stats are presented per game, since the amount of games played varied every season. For the first time we encounter the stat selection menu, on top of the graphs. On this page it features the following options: Category of the stats Stage of the games (Regular or Playoff) Available stats are: Shots Goals (available since 1987, from Boxscore reports) Shots on Goal (available since 1987, from Boxscore reports) Misses (available since 2005, from PBP reports) Blocks (avaliable since 2005, from PBP reports) Icings (available since 2002, from PBP reports) Margin of victory (available since 1987, from Boxscore reports) Penalties Minor Major Fighting Misconduct Match Penalty Goals per Game The stats are available for regular season, playoffs and both stages combined.The PBP reports from the NHL dating before 2005 are wildly inconsistent, thus we didn't use them for MISSES and BLOCKS.We are using the wonderful d3js library for producing these graphs.WE NEED YOUR HELP!If you are an experienced Webmaster, especially with Javascript and CSS we would greatly appreciate the potential tidy-up and enrichment you could provide to these graphs. Your work will be credited for future reference! Write to us, or get in touch with us on Twitter. Thanks!Possible future additions: PowerPlay success Minor penalty breakdown Aggregations and overlays Mouse graph manipulations Your ideas are welcome!
  13. Original post. While the series "Website - A Page A Day" is being delayed by all kinds of things, here comes a short post on a different topic. Last year, in my opinion, the accuracy shooting competition which included shooting the pack from the goal line into a small hole was, in my opinion a total failure. Mike Smith's spectacular score across the rink did the injustice and provided a false impression this skill contest was any good. Otherwise, the competition was not exciting to say the least. Therefore, here's a suggestion to replace it: reverse shootouts. Let the goaltenders shed their equipment for once, and let the skaters don it instead. Let's have a competition where the goaltenders skate and attempt to score in shootout, while the skaters try to stop them. I am sure that somewhere in the back of their minds that would fulfill a little dream both parties would have!
  14. Original post The main page of the website shows the summary of all its features.The site menu features the main statistical sections: League - league-wide statistics Teams - team-based statistics Players - personal statistics Coaches - statistics for the NHL coaches Drafts - statistics for currently drafted players and the historical performance by draft Fantasy - tools to help the fantasy player On the top we have a ticker of the scores, as predicted by the model. The ticker is always scrolled to the current date, however you can navigate it back and forth using the two arrows at the edges. The away team is on the top, and the home team is on the bottom. The predicted score is in the Prdct column. The actual score is in the Act column. The projected winner is displayed in bold. If the prediction failed, the displayed teams will be painted red. We never adjust our predictions backwards. Only the scores for the current season are featured.Then, on the top right we have three very important links that would help you with understanding the pages: Learn More - about the methodology of the Website Glossary - about the terms used in the pages Blog - link to this blog which, as you see, also takes time to elaborate on the site. We also display our latest addition to the website and the latest blog entry. Then we have three random snippets in the columns. The snippets represent excerpts from the tables published elsewhere on the site and may change after each publication, which happens overnight. The snippets currently (hopefully they would become more diverse) are: Team data snippets: Buchholz/Berger-Sonneborn coefficients Empty Net Statistics (probably our most popular page) Teams Elo Ratings and predicted standings, per division Strikebacks Player data snippets: Goaltender elo ratings Deadly pairs of the NHL (goals+primary assist tandems) Clutch players excelling scoring lead-changing goals Reverse stats (players being hit, drawing penalty, etc.) Coach data snippets: Face to face coaching records Coach challenge statistics Only current season data is displayed in the snippets. Below the random snippets we feature a permanent snippet that shows the best projected picks for the daily fantasy competitions. We provide a model-based evaluation of the expected score for players in the three most popular Daily Fantasy websites - Yahoo, FanDuel and DraftKings. Below each snippet there is a link to the page with the full data. At the bottom we have a collection of information links. Make sure you visit the Glossary and the About pages. The Links page has an ever-growing collection of hockey-related links. The Forum link leads to hockeyforums.net, the site we're partnering with - this blog is broadcast there as well. The Data section shows the software and the data sources this website is built with.
  15. Original Post Hello, hockeyforums.net, from Mr. Van Winkle...This prolonged silence was caused by a lot of factors, led, naturally, by REAL LIFE™. But I also made a fundamental mistake in the infrastructure setup, and so I had to roll out a hastily patched setup when the season was starting; I then went back and worked on this infrastructure fix, the work which continued over three months and is now complete! Unfortunately, all this work will not be visible to the visitor, with possible exception of a slightly faster page loading - all the changes belong to the back end.But now, once again, with REAL LIFE™ limitations I am able to work on improving the website look, speed and features. I am being somewhat torn apart since I also need to hone the models I'm using, but I decided the models can wait with half of the hockey season gone by now. In addition I'll try to put an extra effort to promote the site and made it more visible on the Web.One of the things I was not able to complete is to release my code as the open source. This has also been put into a bottom drawer. However, I still welcome cooperation very much and will gladly share the code with people who would want to contribute to the project. The areas I could really use some help are: JavaScript/HTML/CSS MongoDB query and database optimization SEO optimization So if you feel like helping - drop me a mail.Also I will begin a series "Website - A Page A Day", where I plan to describe each and every statistical page on the site because I have a feeling I haven't been clear enough with the explanations until now; moreover it will help me discover errors and inconsistencies that probably crawled through.
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