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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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5 กิจกรรมสนุก ๆ รับซัมเมอร์นี้
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ในที่สุดฤดูร้อนก็มาถึงแล้ว! อย่างไรก็ตามความตื่นเต้นของฤดูกาลที่รอคอยมากที่สุดได้หายไปเล็กน้อยท่ามกลางการแพร่ระบาด เป็นเรื่องปกติมากที่จะเบื่อและคิดถึงยุคโรคระบาดเพราะเราถูกขังอยู่ในบ้านอย่างปลอดภัย นั่นคือวันที่เราทำแผนฤดูร้อนเต็มรูปแบบ ทุกอย่างเป็นไปได้ตั้งแต่วันหยุดพักผ่อนไปจนถึงการสังสรรค์กับเพื่อน ๆ แต่ชีวิตเปลี่ยนไปสำหรับทุกคนและเราไม่สามารถทำอะไรกับมันได้ เพื่อให้เกิดประโยชน์สูงสุดเราได้จัดทำโซลูชันเสมือนจริงสองสามอย่างเพื่อ "รักษาความปลอดภัยและสุขภาพที่ดี" ไว้ที่บ้าน อ่านต่อเพื่อค้นหาวิธีแก้ปัญหาเหล่านี้ การเปิดตัว OTT ล่าสุดของ Binge-watch เรารู้ว่านี่เป็น "สิ่งสนุก ๆ " ที่คุณสามารถหาได้จากเว็บไซต์ออนไลน์ใด ๆ ปีที่แล้วเราเห็น OTT ออกมามากมายและมันก็คุ้มค่า มีซีรีส์และภาพยนตร์หลายเรื่องที่คาดว่าจะดึงดูดคุณได้ยาวนานที่สุดในปีนี้เช่นกัน นอกจากนี้ยังเป็นวิธีที่ดีที่สุดในการฆ่าเวลาในระหว่างการกักกัน บางทีการผูกพันกับคนที่รักอาจเป็นข้อแก้ตัวที่ดี เตรียมของว่างที่คุณชื่นชอบและเพลิดเพลินไปกับความสนุกสนานละครและความบันเทิงที่จริงจัง! การเล่นเกมออนไลน์การเล่นเกมเป็นหนึ่งในกิจกรรมยามว่างที่ได้รับความนิยมมากที่สุด ผู้ที่ไม่ใช่นักเล่นเกมจำนวนมากหันมาใช้โลกแห่งความเป็นจริงเช่นเดียวกับเกมออนไลน์เพื่อเอาชนะความเบื่อหน่ายจากการล็อก มีเกมมากมายที่คุณสามารถเล่นออนไลน์ได้ คุณสามารถเริ่มต้นด้วยเกมโปรดที่คุณชื่นชอบในโลกแห่งความเป็นจริง ตัวอย่างเช่นเหล้ารัมของอินเดียเป็นที่นิยมอย่างมากและมีผู้เล่นหลายล้านคนที่ชื่นชอบเกมนี้ ผู้ให้บริการรัมมี่ออนไลน์ยอดนิยมเช่น Junglee Rummy เป็นเจ้าภาพจัดการแข่งขันที่น่าตื่นเต้นทุกสัปดาห์และทุกเดือน ผู้เล่นสามารถแสดงทักษะของตนเองและรับรางวัลที่น่าทึ่งรวมถึงรูปีและรางวัลเงินสดเทียบเท่ากับรูปี การเล่นเกมออนไลน์อย่างรัมมี่นั้นสนุกและน่าตื่นเต้นแม้ว่าจะปิดอยู่ก็ตาม Board Game Night ใครเกลียดเกมกระดาน? ฉันไม่รู้! ในอดีตฤดูร้อนเป็นเกมกระดานทั้งหมด ตั้งแต่ลูโดไปจนถึงคาร์รอมคุณต้องเติบโตมาพร้อมกับการเล่นเกมที่ยอดเยี่ยมกับเพื่อนและครอบครัวของคุณ การรื้อฟื้นความทรงจำเก่า ๆ ในปี 2021 เป็นอย่างไรบ้าง? ทำความสะอาดสิ่งสกปรกบนกระดานคาร์อมหรือกระดานหมากรุกและเชิญเพื่อนของคุณมาร่วมสนุกกับเกมกระดานยามค่ำคืน บางทีคุณอาจวางแผนการแข่งขันทั้งหมดและเล่นด้วยเงินเดิมพันเพื่อเพิ่มความสนุกเป็นสองเท่า คุณยังสามารถให้ของว่างแก่เพื่อนของคุณเพื่อเล่นเกมหลาย ๆ เกมและจัดปาร์ตี้เล็ก ๆ เนื่องจากการแพร่ระบาดของแฮงเอาท์กลุ่มเสมือนทำให้หลายคนทำงานอยู่ที่บ้านอย่างถาวรและดูเหมือนจะขาดการติดต่อกับโลกภายนอก โชคดีที่มีหลายวิธีในการติดต่อกันโดยไม่ได้พบกับคนที่คุณรัก ด้วยเทคโนโลยีทำให้เราสามารถติดต่อกับญาติและเพื่อนทางไกลได้ ดังนั้นหากคุณพลาดโทรหรือแฮงเอาท์วิดีโอหรือส่งข้อความ แฮงเอาท์กลุ่มเสมือนได้รับความนิยมอย่างมากในช่วงปีที่ผ่านมา ผู้คนติดตั้งแอปอย่าง Google Duo หรือ Zoom และเชื่อมต่อกับผู้คนทั่วโลก !! เรียนรู้ทักษะใหม่ ๆ การเรียนรู้ทักษะใหม่ ๆ จะไม่มีวันล้าสมัย มีเวลาว่างมากมายที่คุณสามารถใช้มันได้หากคุณเรียนรู้ทักษะใหม่ ๆ หากคุณเป็นมืออาชีพในการทำงานคุณสามารถเรียนหลักสูตรออนไลน์เพื่อยกระดับทักษะของคุณได้ หากคุณเป็นนักเรียนคุณสามารถเลือกเรียนภาษาใหม่หรือการเขียนโปรแกรมคอมพิวเตอร์ได้ หากคุณมีกีตาร์อยู่ในร้านคุณสามารถเข้าร่วมหลักสูตรการเรียนรู้กีตาร์ออนไลน์และใช้งานได้ ไม่ว่าคุณจะเรียนรู้ทักษะใดคุณก็จะได้รับประโยชน์จากทักษะนั้นไม่ทางใดก็ทางหนึ่งเสมอ เราหวังว่าวิธีการเหล่านี้จะช่วยคุณและเข้าร่วมการเดินทางของเราเพื่ออยู่ร่วมกันในสัปดาห์ที่อบอุ่นของปี เล่นรัมมี่ออนไลน์และรับรางวัลสุดพิเศษเพื่อทำให้ฤดูร้อนเป็นที่จดจำ ลงทะเบียนสำหรับแพลตฟอร์มที่มีการใช้งานมากที่สุด Junglee Rummy และรับโบนัสต้อนรับ $ 5250 ในบัญชีของคุณ เกมสนุก!
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When Relationships Fall Victim to Problem Gambling
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Many celebrate love, romance, and relationships during February and on Valentine’s Day. While no relationship is perfect, some endure significant hardship due to the presence of addiction, and gambling addiction is no exception. Did you know that relationship problems have been the top reported reason for seeking help by contacts to the 888-ADMIT-IT HelpLine for more than a decade? Contrary to social stigmas, individuals who struggle with problem gambling are not able to simply stop. Gambling addiction rewires the brain much in the same way as substance abuse, yet the symptoms are unseen, leaving loved ones unaware until the gambler hits “rock bottom.” Feelings like shame, guilt, and stress also flood these individuals and leave them hiding the consequences of problem gambling, exacerbating relationship difficulties and preventing them from seeking needed supports. Family members and other loved ones often do not know the extent of the gambler’s behaviors or debt. Over the past year, 76% of 888-ADMIT-IT HelpLine contacts reported the presence of family conflict, and 52% indicated family neglect as a result of problem gambling, with some also experiencing domestic violence and abuse [1]. It is imperative to understand that for every case of problem gambling, an average of 8-10 additional people are affected — often those closest to the gambler.  Research published in the Asian Journal of Gambling Issues and Public Health found that the negative effects of their partner’s gambling problems centered on four key areas — financial loss, emotional distress, impairment of mental and physical health, and erosion of their relationship [2]. Complicating matters further, the COVID-19 pandemic is causing heightened levels of emotional distress and mental health impacts across the population, leaving those suffering from this hidden addiction even more vulnerable. HelpLine data shows that a large percentage of problem gamblers are experiencing significant anxiety (68%) and depression (67%), with more than one in five admitting to suicidal thoughts (22%) and an appreciable number (13%) reporting neurological disorders. These mental health issues understandably extend to family members and loved ones.  The good news is that help and hope can be found through the 24/7, Confidential, and Multilingual 888-ADMIT-IT HelpLine for anyone in need, including loved ones. The HelpLine can also be reached by texting 321-978-0555, starting a live chat at gamblinghelp.org, emailing fccg@gamblinghelp.org, and messaging the FCCG on social media. Get connected to the resources that make a difference, including referrals to certified treatment providers! March is Problem Gambling Awareness Month March is Problem Gambling Awareness Month (PGAM), a grassroots effort to raise awareness about gambling disorder, classified by the American Psychiatric Association as a behavioral addiction, that impacts millions of Floridians who struggle directly with gambling related difficulties or are adversely affected by a loved one’s gambling problem. This year, our campaign theme is Shine the Light on Problem Gambling: Changing the Game. During this past year, the world has been forced to grapple with crippling impacts caused by the COVID-19 Pandemic. Many Florida residents, like many Americans, are struggling given the unforeseen consequences resulting from the pandemic. For disordered gamblers and their families, the effects of the virus can exacerbate already serious financial, psychological, legal, and other problems caused by gambling. Click here to learn more about PGAM and join the movement in raising awareness about the issue of problem gambling and the help and hope available through the 24/7, Confidential, and Multilingual Problem Gambling HelpLine! [1]  24-Hour Problem Gambling HelpLine Annual Report., 2020 ed., The Florida Council on Compulsive Gambling, Inc., 2020, 24-Hour Problem Gambling HelpLine Annual Report. [2] Abbott, M., DA. Abbott, S., Boyatzis, R., V. Braun, V., EM. Chan, A., Charmaz, K., . . . Volberg, R. (1970, January 01). Impacts of gambling problems on partners: Partners’ interpretations. Retrieved February 11, 2021, from https://link.springer.com/article/10.1186/2195-3007-3-11
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Warriors Teammate Praises Steph Curry and Draymond Green’s Hall of Fame IQ
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After a bumpy start to the 2020-21 NBA season, the Golden State Warriors are getting back in form. They made several changes to their roster in the offseason and it took some time for the players to settle in. But with the All-Star break almost here, the Dubs are looking consistent. The credit for their newfound success goes to none other than their veteran duo of Steph Curry and Draymond Green. Recently, the two stars flaunted their skills against the Cavaliers in a comfortable 129-98 victory. Curry continued his hot scoring streak with 36 points against the Cavs. On the other hand, Green handled the facilitating duties for the team as he finished the game with 16 assists. The two stars have shouldered the burden for the team in the absence of Klay Thompson. But can the Warriors go all the way and win another championship? We will find out in the coming months. Steph Curry and Draymond Green: The two pillars for the Golden State Warriors Golden State Warriors forward Kent Bazemore (26) and forward Juan Toscano-Anderson (95) and guard Stephen Curry (30) and forward Draymond Green (23) during the game between the Dallas Mavericks and the Golden State Warriors at the American Airlines Center. Mandatory Credit: Jerome Miron-USA TODAY SportsFollowing this sensational victory, Juan Toscano-Anderson gave an interesting post-game interview. He said: “I am a beneficiary of these guys, their hall of fame IQ. You know Draymond [Green] had 16 assists today and that’s amazing from our starting center. Last five games, he’s in double digits assists. … Either Steph [Curry] is open or Imma be open. “I’m aware that the defense ain’t gonna leave him so I just find those gaps and get those easy buckets. I know Draymond sees everything. Sometimes he sees it a little too quick before any of us see it, but it’s great to play with a guy like that.” Draymond Green has always been an amazing playmaker for the Dubs. Even during their stretch of dominance in the mid 2010s, he took on the role of a facilitator for their championship teams. This season, he is elevating his game further in that department. READ MORE | Steph Curry and LeBron James Ready to Move On From Intense Rivalry But is this enough for the Warriors to win another championship? Feel free to share your thoughts. Get notified about breaking news and watch highlights on the go; join the Arena on NBA Hoops
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Star signing Suliasi Vunivalu stood down by Reds for off-field incident
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A Set small text size A Set the default text size A Set large text size High-profile Queensland Reds recruit Suliasi Vunivalu has been dropped from what would have been his Super Rugby AU debut for allegedly pushing a security guard in a Brisbane pub. The champion NRL winger had arrived at Ballymore fresh off a premiership with the Melbourne Storm as Rugby Australia’s big-ticket item. But on Tuesday the winger copped a club-imposed $10,000 fine alongside suspension from Friday’s season opener at Suncorp Stadium against the NSW Waratahs. The matter is before the court and will be reviewed by RA and Queensland Rugby Union once it is resolved. It is understood the security guard was not injured during the incident, which was considered minor and occurred earlier this month. Vunivalu was implicated in an NRL integrity unity investigation in 2019 when he was allegedly a victim of a coward punch at a Bali nightspot that sparked a brawl that included former Storm teammate Nelson Asofa-Solomona. The 26-year-old had already spent time in camp with the Wallabies and is considered an immense talent likely to feature in national coach Dave Rennie’s plans ahead of the 2023 World Cup. It’s an early setback for a Reds outfit hunting their first silverware since 2011, having lost the Super Rugby AU decider to the Brumbies last year. © AAP
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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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Partypoker adds new MyGame Whiz to Online Poker Client
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Every poker player wants to improve their game. It is quite common for poker players to use tools such as hand histories to review gameplay and try to make different decisions based on certain scenarios. At partypoker, the online poker platform has released a new tool called MyGame Whiz that allows players to improve their game and make fewer mistakes along the way. The new feature is an extension of the MyGame tool and works as a personal poker trainer. What is MyGame Whiz? New players can benefit from the MyGame Whiz tool for a number of reasons. Because the tool is a trainer, it helps to avoid common mistakes. The tool includes one-on-one communication to personalize the experience for each player. The tool studies each player’s game style, including how a hand is played. The tool has access to hand history and studies the hands of each player, not the opponent. Personal hand history is used to provide tips and suggestions on what you can do to improve your decision-making skills. Targeted messages allow you to make decisions in real time and improve your win/loss record. Each player will receive messages that are created for them specifically based on table actions. Interactive commentary is also provided as players compete to help with game moves. Choose to replay, save, and share hands as you like with this new tool. The more hands you play, the more advice you will receive. This helps to know how to strategize based on a wide range of poker hand situations. Another unique aspect to this tool is that questions can be asked to MyGame Whiz. By asking questions, you receive customized replays to help with any questions or advice needed. Creating a Poker Tutor Basically, partypoker has created a poker tutor for its members. With instant feedback, it’s like working with a real person online. The tool works for each player individually, just as a tutor would in real life. Every player can work to improve their game, no matter how skilled or experienced. The tool is specialized so it caters to your skill level. Partypoker officials pointed out that they wanted to create a tool that would give players something to use at the beginning of their poker journey to improve their game. It is particularly helpful for players who are brand-new to online poker. For new players, the tool includes report cards so you can track your progress. See what you have improved on as well as how you can make changes to improve in certain areas. If you have less time to study the game, the MyGame Whiz does the work for you. Simply review the details and you will be able to analyze your gaming and make smart decisions in the future as you play. Check out the new tool today by logging in to the partypoker client. Review your gaming and see what changes you can complete the improve each decision you make while playing in cash games and tournaments.
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Serena Williams shows off her unreal defense on this point
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European Golden Shoe 2020/21: Messi on the leaderboard but Lewandowski scores again
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Lionel Messi scored two goals of the highest quality in La Liga this weekend to take his tally to 15 for the season.Both of the Argentine's goals were scored from outside the box in superb fashion, as he helped Barcelona on their way to a 5-1 win against Alaves.Messi may now make our leaderboard, but he is still some way off reaching the runaway leader, Robert Lewandowski.The Bayern striker scored again on Monday in the German side's rearranged Bundesliga match versus Arminia Bielefeld which was moved due to their Club World Cup exploits over the weekend.Lewandowski now has 25 goals and 50 points.His nearest rival for the Golden Shoe is fellow Bundesliga striker Andre Silva, who has now scored 18 for the season.Liverpool may have lost against Leicester, but Mohamed Salah still scored a lovely goal to take his tally to 17.Georgios Giakoumakis of Venlo has scored an impressive 22 goals and is the highest player on our list who doesn't feature within one of Europe's top five leagues.A talented group on 16 goals for the campaign includes Cristiano Ronaldo, Kylian Mbappe, Romelu Lukaku, and Luis Suarez.2020/21 EUROPEAN GOLDEN SHOE STANDINGS 2020/21 European Golden ShoeA reminder: The five elite leagues - Premier League, La Liga, Bundesliga, Serie A and Ligue 1 - all carry a weighting of 2, meaning that a player will be awarded two points for every goal they score in these competitions. For the leagues ranked sixth to 30 in Uefa's coefficients rankings goals scored are given a weighting of 1.5, and goals scored in a league outwith the top 30, goals are given a weighting of 1. Ciro Immobile won the 2019/20 European Golden Shoe, scoring 36 goals for Lazio in a tremendous Serie A season. 2020/21 EUROPEAN GOLDEN SHOE (Summer Leagues) 2020 European Golden ShoePlayerTeamGoalsPointsKasper JunkerBomo/Glimt2740.5Amahl PellegrinoKristiansund2537.5Philip ZinckernagelBodo/Glimt1928.5Christoffer NymanNorrköping1827Rauno SappinenFlora Tallinn2626Veton BerishaViking1624Astrit SelmaniVerbergs1522.5Mushaga BakengaOdds BK1522.5Moses OgbuMjallby1421Anders ChristiansenMalmo1319.5Leke JamesMolde1219.5Maksim SkavyshBATE Borisov1919This is the 2020/21 European Golden Shoe race. If you want to see the final standing for the 2019/20 European Golden Shoe, follow this link. .
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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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