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USA TODAY Sports / NFCA High School Super 25 Softball Rankings: สัปดาห์ที่ 11
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หลุยส์วิลล์กี. - ถ้าคุณเคยได้ยินหยุดเรา: Neshoba Central มาถึงสถานะสุดท้ายของคลาส 5A แล้ว ตำแหน่งแชมป์รัฐมิสซิสซิปปีเจ็ดสมัยและทีมอันดับ 1 ของสหรัฐอเมริกาจะเผชิญหน้ากับ East Central ในวันนี้ในการเปิดการแข่งขันชิงแชมป์สามอันดับแรกที่ Southern Mississippi University Sports / NFCA High School Super 25 ในวันนี้ เกมที่สองจะจัดขึ้นในวันศุกร์และเกมที่สามกำหนดไว้สำหรับวันเสาร์หากจำเป็น (30-0) The Rockets ชนะ 37 เกม ในขณะเดียวกัน№ 2 Lake Creek (36-0), Hewitt-Trussville อันดับสาม (43-2-1), อันดับ 4 Lakewood Ranch (27-2) และ Park Vista อันดับที่ 5 (27-0) ทุกคนยังคงอยู่ต่อ อาชีพที่เกี่ยวข้องลุยทัวร์นาเมนต์ของรัฐและเล่นให้มากขึ้นในอีกไม่กี่วันข้างหน้า ซานอันโตนิโอวอร์เรน (25-2) รู้สึกไม่พอใจในสองเกมสุดท้ายของซีรีส์เพลย์ออฟกับลอสเฟรสนอสทำให้แต่ละทีมจากแปดทีมต่อไปนี้เลื่อนขึ้นหนึ่งรุ่งโดยลดลงจากอันดับหกเป็น 23 ที่อื่น Masuk of Connecticut (14-0) และ Winnakunnett จาก New Hampshire (4-0) เป็นอันดับใหม่ในการจัดอันดับของสัปดาห์นี้ US TODAY Sports / NFCA High School Super 25 ใช้การจัดอันดับของรัฐที่กำหนดโดยโค้ชสมาชิก NFCA ทีมจะถูกเลือกตามคุณภาพคุณภาพของรายการและความแข็งแกร่งของกำหนดการ ในปี 2564 โรงเรียนที่ไม่มีการแข่งขันจะไม่สามารถเข้าร่วมการสำรวจได้ USA TODAY Sports / NFCA High School Super 25 Survey - 13 พ.ค. 2021 อันดับ | ทีม | บันทึก 2021 | เรตติ้งก่อนหน้า 1. Neshoba Central (Miss.): 30-0 - PR: 1 2. Lake Creek (Texas): 36-0 - PR: 2 3. Hewitt-Trussville (Ala.): 43-2-1 - PR : 3 4. Lakewood Ranch (Fl.): 27-2 - PR: 4 5. Park Vista (Fla.): 27-0 - PR: 5 6. Leander (Texas): 32-0 - PR: 7 7. เคลียร์สปริงส์ (เท็กซัส): 26-0 - PR: 8 8. Barbe (La.): 31-2 - PR: 9 9. Norko (California): 17-1 - PR: 10 10. St. Amant (La) .): 25-3 - PR: 11 11. Marist (Ill.): 21-0 - PR: 12 12. New Palestine (Ind.): 23-0 - PR: 13 13. Keystone (Ohio): 26- 1 - PR: 14 14. Burns (SC): 25-1 - PR: 16 15. Rocky Mountain (Idaho): 21-1 - PR: 18 16. Lakota West (Ohio): 25-1 - PR: 19 17 Roncalli (Ind.): 19-2 - PR: 15 18. South Warren (Ki.): 20-1 - PR: 17 19. Bob Jones (Ala.): 33-4 - PR: 20 20. Barber Hill ( Texas): 33-2 - PR: 21 21. Crown Point (Ind.): 21-2 - PR: 22 22. Masuk (Conn.): 14-0 - PR: NR 23. San Antonio Warren (Texas): 25-2 - ประชาสัมพันธ์: 6 24. วินนากุลเนตร (NH): 4-0 - ประชาสัมพันธ์: NR 25. เทรนตัน (ชั้น): 18-1 - ประชาสัมพันธ์: 25 ซ้าย: อัลวิน (เท็กซัส) สเปนปาร์ก (Ala.) NFCA เพื่อทราบข้อมูลเพิ่มเติม USA TODAY Sports / NFCA High School Super 25 Softball Rating: 10th Week USA TODAY Sports / NFCA High School Super 25 Softball Rating: 9th Week USA TODAY Sports / NFCA High School Super 25 Softball Rating: 8th Week USA TODAY Sports / NFCA High School Super 25 อันดับซอฟท์บอล: สัปดาห์ที่ 7
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EPL: ท็อตแนมชนะ Europe’s Wolves: Photos
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ท็อตแนมปลดเปลื้องความหวังของพวกเขาในการผ่านเข้ารอบสำหรับยูโรป้าลีกด้วยการเอาชนะหมาป่า สเปอร์สซึ่งอยู่ห้าคะแนนจากสี่อันดับแรกเพิ่มขึ้นเป็นหกในประตูที่แตกต่างกับเวสต์แฮมสามคะแนนตามหลังเอฟเวอร์ตันซึ่งเล่นต่อมาในวันอาทิตย์ มันเป็นชัยชนะที่สมควรได้รับสำหรับเจ้าของบ้านที่ตีไม้สามครั้งหลังจากสร้างโอกาสที่ยอดเยี่ยมมากมาย แฮร์รี่เคนซึ่งพยายามตีด้วยมือซ้ายอย่างสมบูรณ์แบบเดินไปยังสเปอร์สอย่างใจเย็นจากการส่งบอลครึ่งลูกที่สวยงามของปิแอร์ - เอมิลไฮแบร์ก หมาป่าขู่และบางครั้งก็ถูกบังคับให้ต้องเสี่ยงโชคในช่วงพักและทั้ง Kane และ Dele Alli ชกกันที่มือขวาเป็นเวลาสองสามวินาที Hodzberg ขึ้นนำเป็นสองเท่าของสเปอร์สอย่างน่าประหลาดใจก่อนอื่นต้องขอบคุณการย้ายของผู้รักษาประตู Wolf Rui Patricio Gareth Bale เพื่อย้ายบอลไปที่มุมล่างขวา Romain Saiss, Adam Traore และ Fabio Silva มีโอกาสที่ดีในการตอบสนองต่อผู้มาเยือน แต่นี่ไม่ใช่ครั้งแรกในฤดูกาลนี้ที่ Wolves ซึ่งจบอันดับที่ 12 ของตารางมีวันที่น่าผิดหวัง เครดิต: BBC Similar to: Download Download ... Related
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Tokyo Olympics panel starts search for new boss after sexism row
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FILE PHOTO: Tokyo 2020 Olympics organizing committee president Yoshiro Mori announces his resignation as he takes responsibility for his sexist comments at a meeting with council and executive board members at the committee headquarters, in Tokyo, Japan February 12, 2021. Yoshikazu Tsuno/Pool via REUTERS/File Photo The panel charged with finding a new Tokyo Olympics chief after a sexism row began talks on Tuesday as campaigners called for more transparency in the selection process. The eight-person committee convened for the first time to discuss choosing a successor to Yoshiro Mori, 83, who stepped down Friday after his claims that women talk too much in meetings sparked widespread outrage. The panel “discussed the qualities required of a new president,” according to Tokyo 2020 organizers, and agreed on five selection criteria. But campaigners said the process should be made more transparent, with Games chiefs declining to identify the members of the panel, which was expected to have a 50-50 gender split. The postponed 2020 Games are set to begin in July, with officials and organizers insisting they will go ahead despite doubts over the event’s viability given the ongoing coronavirus pandemic. The formation of the new panel, headed by 85-year-old Canon CEO Fujio Mitarai, was announced Friday after Mori’s reported attempts to hand-pick 84-year-old Saburo Kawabuchi as his successor was met with opposition. “Now they say they won’t reveal who the members are of the committee to choose the next chief,” Kazuko Fukuda, a campaigner for women’s sexual and reproductive rights, told AFP. “So it’s really like the whole process will take place in secret again.” ‘DEEP UNDERSTANDING’ Equality campaigners handed a petition with more than 150,000 signatures to Tokyo 2020 organizers on Tuesday morning, urging them to put concrete measures in place to prevent further discrimination. The selection committee laid out five criteria for choosing a new president — sporting knowledge, international experience, management skills, familiarity with the Tokyo Games organization and “deep understanding” of Olympic principles, including “gender equality, diversity and inclusion.” The committee pledged to select candidates “as swiftly as possible”, with local media suggesting a new president could be named before the end of the week. Reports said Olympic Minister Seiko Hashimoto, Japanese Olympic Committee president Yasuhiro Yamashita and former hammer-thrower Koji Murofushi are among those in contention. Hashimoto — one of just two women in Japan’s cabinet — was reported as saying Tuesday that she had not been approached about taking over. “It should be done with transparency,” she said. “I hope we can get the new structure in place quickly.” Reports said the selection panel is expected to meet again on Wednesday to draw up a list of nominees. The final choice must be endorsed by Tokyo 2020’s executive board. Read Next Don't miss out on the latest news and information. Subscribe to INQUIRER PLUS to get access to The Philippine Daily Inquirer & other 70+ titles, share up to 5 gadgets, listen to the news, download as early as 4am & share articles on social media. Call 896 6000. For feedback, complaints, or inquiries, contact us.
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Know the Top 5 Wicket-takers in ICC Champions Trophy 2017
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Today we bring you the Cricketers who picked the most wickets in Champions Trophy 2017. The 2017 Champions Trophy was played during June 1-18 in England, with eight teams participating divided in two groups and round robin matches among group teams would give the top 2 on points table, the 4 semifinalists who would then fight to enter the tournament final. India & Pakistan played the tournament final with Pakistan winning their first Champions Trophy title. Indian Batsman Shikhar Dhawan led the batting cards of the tournament edition. Here we detail the bowlers who grabbed the most wickets in Champions Trophy 2017. 5. Adil Rashid (England) The England Leg-spin bowler Adil Usman Rashid would go on to take 7 wickets from the three matches he played at an average of 20.28 & strike rate of 25.7. With these wickets, Adil Rashid featured in the top 5 list of the most wickets in Champions Trophy 2017. His best was 4/41 against Australia on June 10 at Edgbaston, Birmingham. Australia had made 277/9 from their overs with Aaron Finch’s 68, Steven Smith’s 56 & Travis Head’s 71 not out. Rashid & Mark Wood both took 4 wickets each. England won the rain curtailed match by 40 runs. Eoin Morgan scored 87 while Ben Stokes scored 102 not out to take the team through. 4. Liam Plunkett (England) The England Fast Bowler Liam Edward Plunkett would pick 8 wickets from the four matches he played in the ICC Champions Trophy 2017 at an average of 24.50 & strike rate of 25.1. With these wickets, Plunkett featured in the top 5 list of the most wickets in Champions Trophy 2017. His best was 4/55 at Sophia Gardens, Cardiff against New Zealand on June 6. England had batted first and were bowled out for 310 from their overs with Alex Hales’ 56, Joe Root’s 64 & Jos Buttler’s 61 not out. New Zealand, in reply, were bowled out for 223 with Plunkett’s 4, Jake Ball’s 2 & Adil Rashid’s 2. 3. Junaid Khan (Pakistan) The Pakistan Medium pace bowler would pick 8 wickets from the four matches he played in the ICC Champions Trophy 2017 at an average of 19.37 & strike rate of 25.3. With these wickets, Junaid Khan featured in the top 5 list of the most wickets in Champions Trophy 2017. His best was 3/40 against Sri Lanka on June 12. Batting First, the Sri Lankan team was restricted for 236 with Junaid’s 3 & Hasan Ali’s 3. Pakistan chased down the target & won by 3 wickets; Fakhar Zaman scored 50 while Sarfaraz Ahmed scored 71 not out. 2. Josh Hazlewood (Australia) The Australia Medium Pacer Josh Reginald Hazlewood would pick 9 wickets from the three matches he played in the ICC Champions Trophy 2017 at an average of 15.77 & strike rate of 18.6. With these wickets, Hazlewood featured in the top 5 list of the most wickets in Champions Trophy 2017. His best was 6/52 against New Zealand on June 2. Batting first, New Zealand were bowled out for 291 despite Kane Williamson’s 100 & Luke Ronchi’s 65. Hazlewood picked 6 while John Hastings took 2. The match couldn’t be completed as rains would play spoilsport. HUGE WICKET!Virat Kohli is dismissed for 89 – Josh Hazlewood is at it again 🙌#AUSvIND pic.twitter.com/LHYqltc09q— ICC (@ICC) November 29, 2020 1. Hasan Ali (Pakistan) The Pakistan medium pacer would go on to take 13 wickets from the five matches he played in 2017 edition of the ICC Champions Trophy at an average of 14.69 & strike rate of 20.5. With these wickets, Hasan Ali led the top 5 list of the most wickets in Champions Trophy 2017. His best was 3/19 against arch rivals India on June 18 at Kennington Oval, London. Pakistan had batted first and scored 338/4 with Fakhar Zaman’s 114, Azhar Ali’s 59 & Mohammad Hafeez’s 57 not out. India, in reply, were bowled out for 158; Hasan Ali & Mohammad Amir took 3 wickets each while Shadab Khan took 2. Only one bowler took 6 wickets haul, while six bowlers took 4-wickets hauls in the tournament. These were the top wicket-takers, the ones who made the top 5 list of the most wickets in ICC Champions Trophy 2017. The eight teams’ tournament ICC Champions Trophy 2017 was won by Pakistan. Hope you liked the content, don’t shy away from asking your questions, commenting about the content.
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Build a Beautiful Site in the WordPress Mobile Apps with Predesigned Page Layouts
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Build a Beautiful Site in the WordPress Mobile Apps with Predesigned Page Layouts We think you’ll love the new Starter Page Layouts feature. Thomas Bishop Your WordPress mobile app is a convenient way to create and manage your WordPress site. Now, you can design a new page right from your phone or tablet — and build the site of your dreams — with predesigned page layouts. Introducing starter page layouts Not all of us are designers, and building a page on your site with the layout in your mind can be intimidating and time-consuming — but it doesn’t have to be that way! Now when you create a new page on WordPress for iOS or Android, you can choose from premade layouts. You can also customize them to fit your needs, right from the block editor. Choosing a layout When you create a new page in the app, you’ll see a list of premade page layouts, including about pages, contact pages, team pages, services pages, and more. Whether you’re the owner of an online shop of sustainably made clothing, the founder of a newly formed digital magazine, or a financial strategist who’s just launched a consulting business, you can use these premade layouts to build the most essential pages on your website. Once you find a layout that you’d like to try, tap it to select it. After you’ve selected a layout, you can either preview it or create a new page with the chosen layout. Ready to try these new Starter Page Layouts? Be sure to update your WordPress app to the latest version. If you don’t have the app yet, download it for free, on both Android and iOS. We’d love to hear your feedback on these new layouts. Reach out to us from within the app by going to My Site, tapping your photo on the top right, tapping Help & Support,  and then selecting Contact Support. Like this:Like Loading... Related Previous PostShowcase Your Figma Designs on WordPress P2
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My Confession: Male, Age 21 (AUSTRALIA)
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Let me give you some valuable background info first: I live at home with my Dad & my girlfriend (she’s between houses). They’re both my best friends. I am currently going through a chronic pain type disorder that appeared in both wrists & forearms since July 2020. In & out of appointments/checks every fortnight. I am unable to do much in my day, it hurts to do normal things in my day - so I am unable to work or study anymore. Painkillers are not helping. Thursday was the day, the day I basically lost my entire life savings. Since then, I’ve been using every single dollar I can get my hands on to recover this loss & I’m sure you know where I’m at now. $8 in debt & unemployed with no income. But how did I get here? I got caught gambling when I was 17/18, lost all my money then too but it was less than $1000 (my Dad was the only one who knew). Since then, I vowed to never gamble again & I didn’t until 2 weeks ago. My Dad & I were watching the cricket & he placed a $100 multi (he rarely gambles) & won $450. We both thought this was great so I put in $50 myself for the next game. I ended up losing $25 & won it back in the darts later on. I then decided to move on & not do any more as my girlfriend of 2 years (the one I’ll marry) did not approve of me gambling again. So I stopped - until my Dad persuaded me to lie & just gamble anyway behind her back. It was innocent losses, $5-$10 here & there for the next 2 weeks. It wasn’t until last week, the day after my girlfriend’s birthday, that everything went downhill. She had to work Wed & Thu which left me to be alone for 2 days. I was very down in the dumps & just felt like I had all this money & didn’t use it (which is the stupidest thing ever, I know). So I started gambling on the races. With high $1000 bets & spent hours & hours, got up $10k then back down to $5k before I bet my whole bank to get back where I started at $15k. I stopped, went in my room & realised what I did, I almost lost my ENTIRE bank. Did I stop there? Nope, you guessed it. Eventually, one thing led to another & now I’m $15k down & $9 in debt. I confessed everything to my girlfriend & Dad on Thursday. Which they were both very supportive. I had $2000 in my bank then & said I’d stop. But I didn’t, Iost $1500 yesterday & $500 today. So yes in $9 debt. Although I do not have an addiction (oddly enough I studied psychology for 2 years before this chronic pain stopped me), I have definitely fallen into the trap of gambling once again & I only risked losing my last $2000 to not win the money back, but rather I looked at it as an outlet to make money so I can provide my girlfriend & I with a future. But this was such a bad mindset to approach everything. $9 in debt. I am stopping here. I vow to, right here, right now. I have not told my girlfriend or Dad about the last $2000, but I think I will hang onto this one for now as I can make that back in selling some of my collectables that have been collecting profit over the years. So thank god for that at least. Additionally, I may receive a pension for my condition so if that’s approved, must lock my money away. I had to get all this out & it has put me in an awful lot of PHYSICAL pain to even write this due to my chronic pain condition. I don’t expect anyone to read this all as this is rather for me. Thank you. C. submitted by /u/codesfrost [comments]
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Serena’s husband rips tennis administrator after win
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Serena Williams' husband Alexis Ohanian has fired another shot at Madrid Open owner Ion Tiriac after Williams booked yet another Australian Open semi-final appearance.Williams was in imperious form in her quarter-final clash against Simona Halep, thoroughly dismantling the No.2 seed en-route to a 6-3 6-3 win at Rod Laver Arena.Watch the Australian Open with live streams of every court at 9Now. Click here to start watching!The 39-year-old has looked extremely sprightly after being forced to pull out of the French Open early last year through injury, chasing down balls defensively with the same ferocity she did earlier in her career. Williams' vintage showing so far in the Australian Open has silenced many of her critics who believed her chances of winning another Grand Slam title were slim, with Tiriac one of the more vocal critics.Williams was in untouchable form against Simona Halep in her Australian Open quarter-final clash (Getty)Following Williams' dominant display against Halep and advanced to her 40th Grand Slam semi-final, Ohanian made sure to stick the boot into Tiriac on social media."Good thing no one listens to that racist sexist (clown) Tiriac," he tweeted.The tweet wasn't the first time Ohanian had taken aim at Tiriac and called him racist and sexist, after also doing so late last year when Tiriac called out Williams' physique."At this age and the weight she is now, she does not move as easily as she did 15 years ago," Tiriac said on Romanian TV."Serena was a sensational player. If she had a little decency, she would retire." Williams' improved lateral movement has stood out so far in her Australian Open campaign, with her agility a far cry from the version of her fans saw in Melbourne Park last year when she was hampered by ankle and Achilles issues.Williams' coach Patrick Mouratoglou admitted this week that her withdrawal from the French Open last year had allowed the 23-time Grand Slam winner to get out of a "vicious circle".Williams' lateral movement has been noticeably improved after she had been hampered by injuries (Getty)"We've been struggling those last years because she had a lot of injuries, so she was not able to practice the way we wanted," he said."It's a bit of a vicious circle because when you can't practice well, you don't get fit. When you're not fit, you get more injured. We had to get out of this vicious circle."In Roland Garros she had an injury that could get really worse, and that would have been extremely bad. That was definitely the right decision to stop, to heal, and to start working hard because she was able after that to do the necessary work in order to get fit."Now we're more in a virtuous circle than a vicious one. You have to start that virtuous circle by being fit, then everything goes better."For a daily dose of the best of the breaking news and exclusive content from Wide World of Sports, subscribe to our newsletter by clicking here!
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What is Matka? How to play Satta Matka
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Visit Betway's live casino page. What is Matka? Matka is a simple lottery-style betting game which involves guessing two random numbers between 1-9. Among several types of markets, you can win up to 999x your stake by correctly guessing the right sequence of numbers. Card versions of Matka, which are enjoyed by Indian Casino users, have also been developed over the years. How to play Matka The game starts with the player picking their first set of three numbers between 0 and 9, for example: 1, 4, 7. These three numbers are then added up – 1+4+7= 12. The first digit of that total number is dropped, leaving ‘2’. The final selection then looks like 1, 4, 7*2. The player then picks their second set of numbers in exactly the same way, for example: 2, 6, 8. 2+6+8=16, leaving you with 6 as the selection. The second set of numbers is therefore 2, 6, 8*6. Once your full selection is confirmed – in this case, 1, 4, 7*2 X 2, 6, 8*6 – you choose your bet. There are a number of different bets you can place based on the numbers you have chosen, including a bet that would return 9x your stake on whether your first selection (in this case, 2) is correct. After you have placed your bets, the winning numbers will be drawn randomly and all winning bets will be immediately paid out. History of Matka The game originated when bets used to be placed on the opening and closing numbers of the cotton rates that were sent to the Bombay Cotton Exchange from the New York Cotton Exchange. That practise was outlawed in 1961, but the style of game continued when it was proposed that people could simply punt on randomly-generated numbers instead. Pakistani Ratan Khatri proposed that the numbers be written on pieces of paper and drawn from a ‘matka’, a type of pot. Although the way in which the numbers are drawn has changed over the years, the term ‘matka’ has survived.
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Criticisms of Michael Slepian’s Stanford study on poker tells and hand movements (published 2015)
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Some places the study was featured. The following is reposted from a 2015 piece I wrote for Bluff magazine. It was originally located at this URL but has become unavailable due to Bluff going out of business. I saw this study mentioned recently in Maria Konnikova’s book ‘The Biggest Bluff’ and was reminded about this piece and noticed it was offline, so I wanted to share it again. A few notes on this piece: The original title below and was more negative-sounding than I liked; Bluff chose it. Also, if I could rewrite this piece now, I’d probably choose less negative-sounding phrasing in some places.  Regardless of the exact factors that might be at work in the found correlation, I realize it’s scientifically interesting that a significant correlation was found. But I also think it’s possible to draw simplistic and wrong conclusions from the study, and my piece hopefully gives more context about the factors that might be at work. Image on left taken from Michael Slepian’s media page. The Slepian Study on Betting Motions Doesn’t Pass Muster A 2013 study¹ conducted at Stanford University by graduate student Michael Slepian and associates found a correlation between the “smoothness” of a betting motion and the strength of the bettor’s hand. In a nutshell, there was a positive correlation found between betting motions perceived as “smooth” and “confident” and strong hands. The quality of the betting motions was judged by having experiment participants watch short clips of players making bets (taken from the 2009 WSOP Main Event) and estimate the hand strength of those bets. This experiment has gotten a lot of press over the last couple years. I first heard about it on NPR. Since, I’ve seen it referenced in poker blogs and articles and in a few mainstream news articles. I still occasionally hear people talk about it at the table when I play. I’ve had friends and family members reference it and send me links to it. It’s kind of weird how much attention it received, considering the tons of interesting studies that are constantly being done, but I guess it can be chalked up to the mystique and “sexiness” of poker tells. The article had more than casual interest for me. I’m a former professional poker player and the author of two books on poker behavior: Reading Poker Tells and Verbal Poker Tells. I’ve been asked quite a few times about my opinion on this study, and I’ve been meaning to look at the study more closely and write up my thoughts for a while. In this article, I’ll give some criticisms of the study and some suggestions for how this study (and similar studies) could be done better. This isn’t to denigrate the work of the experiment’s designers. I think this is an interesting study, and I hope it will encourage similar studies using poker as a means to study human behavior. But I do think it was flawed in a few ways, and it could be improved in many ways. That’s not to say that I think their conclusion is wrong; in fact, in my own experience, I think their conclusion is correct. I do, however, think it’s a very weak general correlation and will only be practically useful if you have a player-specific behavioral baseline. My main point is that this study is not enough, on its own, to cause us to be confident about the conclusion. I’ll give a few reasons for why I think the study is flawed, but the primary underlying reason is a common one for studies involving poker: the study’s organizers just don’t know enough about how poker works. I’ve read about several experiments involving poker where the organizers were very ignorant about some basic aspects of poker, and this affected the way the tests were set up and the conclusions that were reached (and this probably applies not just to poker-related studies but to many studies that involve an activity that requires a lot of experience to understand well). Poker can seem deceptively simple to people first learning it, and even to people who have played it for decades. Many bad players lose money at poker while believing that they’re good, or even great players. In the same way, experiment designers may falsely believe they understand the factors involved in a poker hand, while being far off the mark. Here are the flaws, as I see them, in this study: 1. The experimenters refer to all WSOP entrants as ‘professional poker players.’ This first mistake wouldn’t directly affect the experiment, but it does point to a basic misunderstanding of poker and the World Series of Poker, which might indirectly affect other aspects of the experiment and its conclusions. Here are a couple examples of this from the study: The World Series of Poker (WSOP), originating in 1970, brings together professional poker players every year (from the study’s supplemental materials) These findings are notable because the players in the stimulus clips were highly expert professionals competing in the high-stakes WSOP tournament. The WSOP Main Event is open to anyone and most entrants are far from being professional poker players. Categorizing someone’s poker skill can be difficult and subjective, but Kevin Mathers, a long-time poker industry worker, estimates that only 20% of WSOP Main Event entrants are professional (or professional-level) players. This also weakens the conclusion that the results are impressive due to the players analyzed being professional-level. While the correlation found in this experiment is still interesting, it is somewhat expected that amateur players would have behavioral inconsistencies. I’d be confident in predicting that a similar study done on only video clips of bets made by professional poker players would not find such a clear correlation. 2. Hand strength is based on comparing players’ hands This is a line from the study that explains their methodology for categorizing a player’s hand as ‘weak’ or ‘strong’: Each player’s objective likelihood of winning during the bet was known (WSOP displays these statistics on-screen; however, we kept this information from participants by obscuring part of the screen). They relied on the on-screen percentage graphics, which are displayed beside a player’s hand graphics in the broadcast. These graphics show the likelihood of a player’s hand winning; it does this by comparing it to the other players’ known hands. This makes it an illogical way to categorize whether a player believes he is betting a weak or strong hand. If this isn’t clear, here’s a quick example to make my point: A player has QQ and makes an all-in bet on a turn board of Q-10-10-8. Most people would say that this player has a strong hand and has every reason to believe he has a strong hand. But, if his opponent had 10-10, the player with Q-Q would have a 2.27% chance of winning with one card to come. According to this methodology, the player with the Q-Q would be judged as having a weak hand; if the test participants categorized that bet as representing a strong hand, they would be wrong. It’s not stated in the study or the supplemental materials if the experimenters accounted for such obvious cases of how using the percentage graphics might skew the results. It’s also not stated how the experimenters would handle river (last-round) bets, when one hand has a 100 percent winning percentage and the losing hand has 0 percent (the only exception would be a tie). It’s admittedly difficult to come up with hard-and-fast rules for categorizing hand strength for the purposes of such an experiment. As someone who has thought more than most about this problem, for the purpose of analyzing and categorizing poker tells, I know it’s a difficult task. But using the known percentages of one hand beating another known hand is clearly a flawed approach. The optimal approach would probably be to come up with a system that pits a poker hand against a logical hand range, considering the situation, or even a random hand range, and uses that percentage-of-winning to rank the player’s hand strength. If this resulted in too much hand-strength ambiguity, the experiment designers could throw out all hands where the hand strength fell within a certain medium-strength range. Such an approach would make it more likely that only strong hand bets and weak hand bets were being used and, equally important for an experiment like this, that the player believed he or she was betting either a strong or weak hand. 3. Situational factors were not used to categorize betting motions When considering poker-related behavior, situations are very important. A small continuation-bet on the flop is different in many ways from an all-in bet on the river. One way they are different: a small bet is unlikely to cause stress in the bettor, even if the bettor has a weak hand. Also, a player making a bet on an early round has a chance for improving his hand; whereas a player betting on the river has no chance to improve his hand. When a player bets on the river, he will almost always know whether he is bluffing or value-betting; this is often not the case on earlier rounds, when hand strength is more ambiguous and undefined. This experiment had no system for selecting the bets they chose for inclusion in the study. The usability of the clips was apparently based only on whether the clip meant certain visual needs of the experiment: i.e., did the footage show the entirety of the betting action and did it show the required amount of the bettor’s body? From the study: Research assistants, blind to experimental hypotheses, extracted each usable video in each installment, and in total extracted 22 videos (a standard number of stimuli for such studies; Ambady & Rosenthal, 1993) for Study 2 in the main text. Study 1 videos required a single player be in the frame from the chest-up, allowing for whole-body, face-only, and arms-only videos to be created by cropping the videos. These videos were therefore more rare, and the research assistants only acquired 20 such videos. The fact that clips were chosen only based on what they showed is not necessarily a problem. If a hand can be accurately categorized as strong or weak, then it doesn’t necessarily matter when during a hand it occurred. If there is a correlation between perceived betting motion quality and hand strength, then it will probably make itself known no matter the context of the bet. Choosing bets only from specific situations would have made the experiment stronger and probably would have led to more definite conclusions. It could also help address the problem of categorizing hand strength. For example, if the experiment designers had only considered bets above a certain size that had occurred on the river (when all cards are out and there are no draws or semi-bluffs to be made), then that would result in polarized hand strengths (i.e., these bets would be very likely to be made with either strong or weak hands). Also, the experiment’s method for picking clips sounds like it could theoretically result in all strong-hand bets being picked, or all weak-hand bets being picked. There is nothing in the experiment description that requires a certain amount of weak hands or strong hands. This is not in itself bad, but could affect the experiment in unforeseen ways. For example, if most of the betting motion clips chosen were taken from players betting strong hands (which would not be surprising, as most significant bets, especially post-flop, are for value), then this could introduce some unforeseen bias into the experiment. One way this might happen: when a video clip shows only the betting motion (and not, for example, the bettor’s entire torso or just the face, as were shown to some study groups), this focus might emphasize the bet in the viewer’s mind and make the bet seem stronger. And if most of the hands-only betting clips were of strong-hand bets (and I have no idea how many were), the study participants watching only the hand-motion betting clips would falsely appear to be making good guesses. My main point here is that thinking about the situational factors of a betting motion, and incorporating that into the experiment in some way, would have resulted in less ambiguity about the results. (It appears that it was difficult to find usable clips from a single WSOP event; in that case, the experimenters could just add footage from another WSOP Main Event to the study.) 4. The number of chips bet was not taken into account The experiment designers did not take into account the chips that were bet. In their words: During betting, each player pushes poker chips into the center of the table. Each chip has a specific color, which indicates a specific value. These values range from $25 to $100,000. This range of chip values has a crucial consequence for the current work. The number of chips does not correlate with the quality of the hand (see Table 1A in the main text). Players could move a stack of 20 chips into the center of the table, and this could be worth $500 or $2,000,000 (the winner of the 2009 WSOP won $8,547,042, thus the latter bet magnitude is a bet that can be made in the WSOP). Because no participants were professional poker players, nor considered themselves poker experts, they were not aware of chip values. They could not, then, use the number of chips as a valid cue to judge poker hand quality. It’s true that your average person would not know what the chip colors at the WSOP Main Event mean. But it seems naïve to think that seeing the chips being bet couldn’t possibly have an effect on the experiment. For one thing, the number of chips being bet could bias a participant to think a bet was stronger or weaker, whether correctly or incorrectly. What if all the strong-hand bets in the study were also bets that involved a lot of chips? (This is not implausible because smaller bets with weak hands are common early in a hand, when bets are small, whereas larger bets later in the hand are more likely to represent strong hands.) And what if some of the study participants were able to deduce (consciously or unconsciously) the strength of the bet from the number of chips? Also, it’s possible that some of the test participants were knowledgeable (consciously or not) about some WSOP chip colors and what their denominations were. Or they were able to deduce (consciously or not), from the arrangement and number of chips, what the chip values were. (For example, large denomination chips are generally required to be kept at the front of a player’s stack.) Again, this could have been addressed by selecting bets taken only from specific situations and only of certain bet sizes. If all bets chosen were above a certain bet size, and this was communicated to the study participants, then this would have lessened the impact of the chips being able to be seen. 5. Quality of “smoothness” was subjective The experiment was based on the perceptions of study participants watching the assembled video clips. It was not based on objective measurements of what constitutes “smoothness” of a betting motion. This was a known issue in the experiment: Thus, both player confidence and smoothness judgments significantly predicted likelihoods of winning, which suggests that movement smoothness might be a valid cue for assessing poker hand quality. It is unknown, however, how participants interpreted “smoothness” or whether the players’ movements that participants rated as smooth were truly smoother than other players’ movements. Other physical factors, such as speed, likely played a role. This is not a major criticism; I think using perception is a fine way to find a correlation, especially for a preliminary study. But I think it does mean that we have no reason to be confident in the idea that smoothness of betting motion is correlated with hand strength. If there is are correlations between betting motion and hand strength (which I believe there are), these could be due to other aspects of arm motion or hand motion, such as: the betting speed, the position of the hands, the height of the hand, or other, more obscure, factors. In summary Again, I don’t mean to denigrate the experiment designers and the work they’ve done. I think this was an interesting experiment, and I think it’s probable the correlation they noticed exists (however weak the correlation may be). Also, as someone who is very interested in poker behavior, I’d love to see similar studies be done. My main goal in writing these criticisms and suggestions was to emphasize that poker is complex, as is poker behavior. There are many behavioral factors in a seemingly simple hand of poker and taking these factors into account can make an experiment stronger and the results more conclusive. Patricia Cardner, PhD, EdD, is a poker player and the author of Positive Poker, a book about the psychological characteristics of professional poker players. She had this to say about poker’s use in scientific studies: “While researchers often have the best of intentions, it is difficult for them to fully understand the nuances of poker. Researchers who reach out to poker players for help can make more informed decisions about the research areas they choose to pursue, increase reliability and validity, and improve the overall quality of their results and conclusions.” ¹: Slepian, M.L., Young, S.G., Rutchick, A.M. & Ambady, N. Quality of Professional Players’ Poker Hands Is Perceived Accurately From Arm Motions. Psychological Science (2013) 24(11) 2335–2338. Related
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2021 Australian Open: What to Watch on Thursday Night
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How to watch: 6 p.m. to 9 p.m. Eastern on the Tennis Channel and 9 p.m. to 7 a.m. on ESPN2 in the United States; streaming on the ESPN+ and ESPN3 apps.As each singles draw dwindled to 32 players, some former major champions lost their hopes of snagging one more Grand Slam title. The 17th-seeded Stan Wawrinka lost his second-round match to Marton Fucsovics, and the eighth-seeded Bianca Andreescu fell to Hsieh Su-Wei.Although the field has shrunk, plenty of promising youngsters and past major champions remain.Here are some matches to keep an eye on.Because of the number of matches cycling through courts, the times for individual matchups are best estimates and certain to fluctuate based on when earlier play is completed. All times are Eastern.Rod Laver Arena | 7 p.m. ThursdayAryna Sabalenka vs. Ann LiAryna Sabalenka, the seventh seed, has equaled her best result at the Australian Open by reaching the third round. She has yet to make it to a Grand Slam quarterfinal, despite how consistently well she plays on tour. Sabalenka won three hardcourt singles titles in 2020, and started 2021 by winning the Abu Dhabi Open. Her aggressive style can help her on faster-paced courts, although on her poorer days it can create plenty of unforced errors.Ann Li, the world No. 69, has had a fantastic run of results in the past few weeks. Last week, she won the Grampians Trophy in Melbourne with a walkover in the final. Then, in the first round of the Australian Open, she upset the 31st seed, Zhang Shuai, while dropping only two games. Although her second-round match against Alizé Cornet required a bit more from her, Li played well, pushing through a tough second set tiebreaker in which she faced two set points. One more upset would put her in her first round of 16 at a Grand Slam event.John Cain Arena | 10 p.m. ThursdayNaomi Osaka vs. Ons JabeurNaomi Osaka, the third seed, has won a Grand Slam event in each of the past three years, all on hardcourts. The fast pace of play suits her, as she pins opponents into the back corners of the court with her flat shots. Osaka did not play in the French Open in October, citing concerns related to the pandemic. She is back into a groove at the Australian Open, dropping just eight games across her first two matches.Ons Jabeur, the 27th seed, became the first Arab woman to reach a Grand Slam quarterfinal at last year’s Australian Open, losing to the eventual champion, Sofia Kenin. Jabeur’s adaptability can be very difficult for opponents to handle; she can unravel an array of opponents’ weaknesses. To beat Osaka, Jabeur will need to have a strong start and not allow her opponent to get into a rhythm.John Cain Arena | 3 a.m. FridayDominic Thiem vs. Nick KyrgiosDominic Thiem, the third seed, won the United States Open in September, supplanting Marin Cilic (2014) as the most recent first-time male Grand Slam champion.A four-time Grand Slam finalist, Thiem has slowly been chipping away at the hegemony of the so-called Big Three of Roger Federer, Rafael Nadal and Novak Djokovic. Though Thiem’s U.S. Open victory came on a hard court, that is not considered his best surface. And with the unusually quick conditions in Australia, he may struggle to return to the final, where he lost to Djokovic last year.Nick Kyrgios, an Australian ranked 47th in the world, was often stereotyped as an uncouth punk for his perceived lack of interest in the sport of tennis. As the coronavirus pandemic shut down the ATP Tour, Kyrgios became a loud advocate for health and safety precautions, openly criticizing both his peers and legends like Boris Becker for choosing to socialize or complaining about safety measures. Now Kyrgios is playing in front of home crowds, and the fast-paced courts in Melbourne will aid his aggressive baseline style. However, after barely squeezing past the 29th seed, Ugo Humbert, in five sets, Kyrgios will be challenged to break down Thiem’s exceptional defensive play.Margaret Court Arena | 3 a.m. FridayDenis Shapovalov vs. Felix Auger-AliassimeDenis Shapovalov and Felix Auger-Aliassime, the two youngest members of the Canadian delegation at the Australian Open, are both aggressive, full-court players who rely on their athleticism to get through tough matches.Shapovalov, the 11th seed, reached his first Grand Slam quarterfinal at the U.S. Open before losing in five sets to Pablo Carreño Busta. Although Shapovalov, 21, lost both of his ATP Cup matches — a singles match against the seventh-ranked Alexander Zverev and a doubles match — they were tightly contested. After an impressive five-set win over the fellow up-and-comer Jannik Sinner, Shapovalov looks prepared to reach the second week of play.Auger-Aliassime, 20, has skated through his first two rounds, convincingly dismantling his opponents without dropping a set. The last time he faced Shapovalov on tour, he lost in straight sets in the first round of the 2019 U.S. Open. A year and a half later, this match will be a good test of whether he can usurp his close friend as the top Canadian men’s player.Here are a few more matches to keep an eye on:Serena Williams vs. Anastasia Potapova — 9 p.m.Milos Raonic vs. Marton Fucsovics — 1 a.m.Simona Halep vs. Veronika Kudermetova — 3 a.m.Novak Djokovic vs. Taylor Fritz — 5 a.m.
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