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Kyrie Irving: Uncle Drew, Little Mountain, and Enigmatic Nba Superstar

為了解決NBA trade Warriors的問題，作者Gitlin, Martin 這樣論述：

Perhaps no NBA player today is as exciting and yet enigmatic as Kyrie Irving. Martin Gitlin's biography chronicles Irving's brilliance on the court as a devastating one-on-one talent, examines the influence of his father, the untimely death of his mother, his growth as a basketball player in high sc

hool and college, and his journey in the NBA. Nicknamed the "Isolation Assassin," Irving has earned the distinction as the most incredible isolation player in the league, outperforming rivals such as Stephen Curry and Russell Westbrook with his crossover dribble, drives to the basket, stop-and-go mo

ves, and smooth, feathery jumpers, a distinction borne out, moreover, by his championship-clinching shot against Curry's Golden State Warriors in 2016. Yet while he speaks of maximizing his talent, he has shown reluctance to maximize the production of his teammates by passing the ball, as well as hi

s overall defense. Irving expresses his desire to win championships yet demanded a trade away from the franchise best suited to deliver him a second. Off the court there is no one like Irving either. An educated individual who claims that the earth could be flat and that dinosaurs perhaps never exis

ted, Irving is a man of puzzling contradictions who seeks self-actualization and contentment through a variety of pursuits, including reflection, music, and acting. Gitlin, a veteran writer who has followed Irving's career from the beginning, has much to tell about one of the most mysterious and sen

sational athletes of our time whose appeal transcends his sport. Martin Gitlin is a veteran sportswriter who worked for seven years at CBSSports.com. He has won more than forty-five awards as a newspaper journalist, including first place for general excellence in journalism from the Associated Pre

ss. Gitlin is the author of more than 150 books, including The Greatest College Football Rivalries of All Time, Powerful Moments in Sports: The Most Significant Sporting Events in American History, and The 100 Greatest American Athletes.

NBA trade Warriors進入發燒排行的影片

數位虛擬的中國大陸與美國競爭-電子遊戲的政治性與他者建構

為了解決NBA trade Warriors的問題，作者林子超 這樣論述：

本文將從政治學、國際關係學及社會學領域，以跨領域研究的觀點，綜合分析當前中國大陸與美國在電子遊戲領域內的政治性競爭及民間文化衝突，並探討歐美電子遊戲內容所存在的他者建構及文化霸權現象。本研究將從傅柯（Foucault）的「知識與權力」及「文化霸權」的角度，解構歐美遊戲開發在內容制定上的「領導權」，並從「東方主義」角度解析，電子遊戲所產生的「他者想像」以及「種族偏見」問題；其次，藉由中國大陸及美國的案例，分析雙方從「官方」及「民間」的二元視角，分析電子遊戲是如何成為官方「政治宣傳」及民間「族群衝突」的因素；最後，針對電子遊戲產生的政治性及文化議題，提出未來可研究的方向。研究方法上，本文使用混合

研究法（mixed methods），在研究過程的不同階段（phases）同時結合量化與質化的資料。研究初期以層級分析法（Analytic Hierarchy Process，AHP），實證調查遊戲內容因素。通過質化研究分析電子遊戲在社會科學領域的研究現況，並結合遊戲研究、東方主義、第三空間等理論，針對遊戲個案進行分析。最後，以實證調查法（survey method）考據中國大陸及美國雙方遊戲玩家的文化及族群衝突問題。研究結果顯示，電子遊戲由於市場性因素及開發系統結構，導致遊戲內容以歐美價值觀為主，並且內容具有種族偏見、白人男性優越及他者刻板印象等問題。且歐美遊戲在處理中國想像時，刻板性的以歐

美13世紀至19世紀歷史文獻中的東方印象為依據，創建出遠古中華的地大物博與近代中華的滯後發展，形成具有反差性的二元結構。另一方面，本文從政治宣傳及文化霸權的視角，證實軍事電子遊戲領域，內容制定與政治和軍事具有緊密的關係，且被東西方作為話語權爭奪的平台。此外，美國及中國大陸官方皆將電子遊戲視為公共外交及愛國主義宣傳的工具，藉由電子遊戲的滲透性達到直接宣傳的效果。在民間方面，中國大陸因為政策性因素，導致中國玩家虛擬移民，由此產生中美玩家建構在行為區別的族群衝突。在這衝突之中，歐美玩家將金農行為及外掛使用族群化、標籤化，與中國劃上等號；中國玩家選擇在電子遊戲內組織民族主義為中心的團體，以之抵抗。實證

調查顯示，歐美玩家「學歷」較低及「年齡」較輕，對於中國大陸玩家行為越排斥，且更容易將中國大陸玩家網路行為與現實華人社群連結，造成虛擬衝突現實化。綜上所述，本研究發現今電子遊戲開發缺乏對於社會文化議題的關注，且由於市場性因素及開發結構的系統性問題，內容的價值仍由歐美主導，隨著青年世代對於電子遊戲的接納，中美雙方也轉變立場，試圖藉由電子遊戲的沉浸感、模擬性和滲透性，做為數位時代政治權力的影響工具。

2019 Nba Champions Eastern Conference Lower Seed

為了解決NBA trade Warriors的問題，作者Triumph Books (COR) 這樣論述：

We The North. The slogan for the most successful era of Raptors' basketball was elevated to a new level with the stunning off-season acquisition of superstar Kawhi Leonard. Finally breaking through after years of knocking on the door of the Eastern Conference, the Raptors made history and brought th

e first championship home to Toronto since the Blue Jays in 1993. From an intriguing new coaching hire in Nick Nurse, to the Leonard trade, to a midseason addition of Marc Gasol, the 2018-2019 season was one of changing the identity of the team, building chemistry, and leading to the franchise's lon

g-awaited first title. From making quick work of the Magic in the first round of the playoffs, to a Game 7 classic against the 76ers, to ripping off four straight wins versus the Bucks, the Raptors were destined to take down the defending champion Golden State Warriors on their way to becoming kings

of the NBA. Packed with expert analysis and dynamic color photography, We The Champs: The Toronto Raptors' Historic Run to the 2019 NBA Title takes fans through the Raptors' historic and unforgettable journey, from Nurse and Leonard replacing Dwane Casey and DeMar DeRozan, to Pascal Siakam blossomi

ng into a star, to Leonard's unbelievable four-bounce Game 7 game-winner against the 76ers. This commemorative edition also includes in-depth profiles of Leonard, Kyle Lowry, Masai Ujiri, and other fan favorites who played key roles in Toronto's extraordinary championship run. Alex Wong is a freel

ance writer based in Toronto. He has followed the Toronto Raptors since their inception, and has covered and written about the NBA for various publications including The New Yorker, GQ, SLAM, New York Times, Yahoo Sports, The Atlantic and other places.Sean Woodley is a freelance writer and broadcast

er based in Hamilton, Ontario. He has been covering the Raptors for SB Nation’s Raptors HQ since 2015, is the host of the daily ＂Locked On Raptors＂ podcast, and is a regularly heard voice on TSN 1150 Radio in Hamilton. Above his office desk sits a framed photo of his favourite Toronto Raptor, Terren

ce Ross.Jack Armstrong is an NBA analyst and Toronto Raptors broadcaster for TSN. He has been the voice of the Raptors for two decades.

基於機器學習技術建構整合式運動賽事結果預測模式-以美國職業籃球為例

為了解決NBA trade Warriors的問題，作者陳威任 這樣論述：

運動賽事預測模型在近年運動市場蓬勃發展之下，已漸漸成為一個重要的議題。建立一個好的運動賽事預測模型，在運動博弈、球隊管理營運、媒體轉播管理上，均具有非常大的助益。現存相關研究較少使用機器學習方法進行運動賽事預測模型之建構。本研究提出一個以機器學習方法為基礎之運動賽事預測模型，使用美國職業籃球聯盟（National Basketball Association，NBA）2018-2019賽季所有賽事之攻守數據做為資料庫，預測每場賽事最終球隊總得分。本研究使用相關研究較常採納之十五項攻守數據，自最具公信力之籃球數據網站Basketball-Reference.com擷取NBA 2018-2019

賽季所有賽事之球隊攻守數據。攻守數據經過標準化後，將資料進行特徵工程（Feature Engineering），相關研究均以單一賽事延遲（Game-Lag）作為特徵建構方式，本研究採納六場賽事延遲，提高研究之完整性。本研究建構之預測模型包括二種預測程序（Process）。第一個程序由二階段預測模型組成：第一階段模型由四種機器學習方法及一種無母數回歸方法建構，經過特徵建構後之十三個預測變量進入第一階段模型進行建模及預測，並且在第一階段模型分析時，選擇預測效果較佳的賽事延遲數量。第二階段模型由特徵選擇（Feature Selection）開始，本研究採用三種內嵌式（Embedded）特徵選擇方法，

從十三個預測變量中，經由排序法（Ranking），選出六個重要預測變量，進行第二階段模型建模及預測。最後將五種方法、二階段模型共計十種不同預測結果進行比較。透過實證資料，本程序探討不同賽事延遲對預測模型之影響，得到預測效果較佳之賽事延遲資訊，並且發現二階段模型能夠取得較佳之預測結果。第二個程序著重於特徵工程中，對於特徵之組成，本研究採用適應性權重（Adaptive Weighting），將距離目標賽事較近之參考數據賦予較高之權重，並且與不同之賽事延遲進行配對，完成不同之特徵組合（Feature set），作為五種機器學習方法組成之預測模型之輸入變項，經由本程序之實證結果，得到預測效果較佳之適應

性權重及賽事延遲之組合。本研究藉由二種程序所得到之實證結果，證實適當的選擇賽事延遲及適應性權重，對於建構機器學習為基礎之籃球賽事比數預測模型具有提升的效果。