NBA stats的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列線上看、影評和彩蛋懶人包

The Last Enforcer: Outrageous Stories from the Life and Times of One of the Nba’s Fiercest Competitors

為了解決NBA stats的問題，作者Oakley, Charles 這樣論述：

In this ＂incredible read on some incredible days and nights in the old association＂ (Adrian Wojnarowski, ESPN senior NBA insider) Charles Oakley--one of the toughest and most loyal players in NBA history--tells his unfiltered stories about his basketball journey and his relationships with Michael

Jordan, LeBron James, Charles Barkley, Patrick Ewing, Phil Jackson, Pat Riley, James Dolan, Donald Trump, George Floyd, and many others.If you ask a New York Knicks fan about Charles Oakley, you better prepare to hear the love and a favorite story or two. But his individual stats weren’t remarkable

, and while he helped power the Knicks to ten consecutive playoffs, he never won a championship. So why does he hold such a special place in the minds, hearts, and memories of NBA players and fans? Because over the course of nineteen years in the league, Oakley was at the center of more unbelievable

encounters than Forrest Gump, and nearly as many fights as Mike Tyson. He was the friend you wish you had, and the enemy you wish you’d never made. If any opposing player was crazy enough to start a fight with him, or God forbid one of his teammates, Oakley would end it. ＂I can’t remember every reb

ound I grabbed but I do have a story--the true story--of just about every punch and slap on my resume,＂ he says. In The Last Enforcer, Oakley shares one incredible story after the next--all in his signature ＂unflinchingly tough, honest, and ultimately endearing＂ (Harvey Araton, New York Times bestse

lling author) style--about his life in the paint and beyond, fighting for rebounds and respect. You’ll look back on the era of the 1990s NBA, when tough guys with rugged attitudes, unflinching loyalty, and hard-nosed work ethics were just as important as three-point sharpshooters. You’ll feel like y

ou were on the court, in the room, can’t believe what you just saw, and need to tell everyone you know about it.

NBA stats進入發燒排行的影片

虛擬通貨之研究—以內線交易責任為中心

為了解決NBA stats的問題，作者鍾宇 這樣論述：

發展迅速的區塊鏈技術塑造了Web 3.0時代，伴隨去中心化金融監管議題逐漸發酵，虛擬通貨發行所涉及的市場秩序維護和投資人保護議題，開始備受各國金融監管機關關注，而本文所主要探討者，乃虛擬通貨內線交易責任的相關疑義。雖然虛擬通貨市場上確實存在某些內線交易問題，但有鑑於虛擬通貨尚有許多監管之不確定性，究竟應否將之納入內線交易法充斥不少爭議，也無怪乎國內外對於虛擬通貨內線交易相關的實務判決仍相當缺乏。然而，內線交易法目的所欲維護之市場秩序，是否會及於我們所熟知的比特幣、乙太幣乃至其他類型虛擬通貨之市場，實有其值得思考之處。有關虛擬通貨的證券法定位，各國證券主管機關透過各式官方資料，試圖說明虛擬通貨

的證券定性考量或監管策略，我國金管會亦於2019年7月正式核定「具證券性質之虛擬通貨」為有價證券，並提出相關發行規範說明，對於我國虛擬通貨的證券監理可謂一項重大突破。然而本次核定函令及相關說明，僅為虛擬通貨證券監理的開始，待未來國內出現虛擬通貨發行之實際問題時，可能會產生更多現行證券交易法適用上的疑義。以內線交易為例，內線交易法目的之思考到各項構成要件之適用，在虛擬通貨領域皆可能存在某些論點的歧異。本文主要沿襲2018年瑞士FINMA對虛擬通貨的分類，將虛擬通貨分為支付型、功能型及資產型，以輔助分析虛擬通貨於內線交易規範之適用性，並觀察我國證券交易法與期貨交易法規範，討論各類型虛擬通貨可能適用

的內線交易法規依據。在比較法上，則著重參酌美國SEC及CFTC兩大金融監管機關的實務案例處理，思索我國規範上可資借鏡之處。最後，本文提出若干我國規範上之建議，使「具證券性質之虛擬通貨」能明確適用證券內線交易規範，並期望金管會逐步核准虛擬通貨相關期貨商品，讓其他不具證券性質之虛擬通貨有機會受到期貨內線交易規範之檢核，希能透過建立明確的內線交易法制，增進投資人對國內虛擬通貨市場環境的信任。

The 20 Greatest Moments in New York Sports History

為了解決NBA stats的問題，作者Ehrlich, Todd,Kalb, Elliott 這樣論述：

Todd Ehrlich is founder and President of T-LINE TV, a television production company dedicated to broadcast, sports, and commercial television production. A five-time Emmy Award winner and twenty-two time Emmy nominee, Ehrlich has covered two Olympics, the Super Bowl, World Series, NFL Finals, NBA Fi

nals, and Triple Crown races. Ehrlich has met and interviewed the most prominent sports personalities of the era in his thirty five years in the business. Currently the executive sports producer for WPIX in New York, he has worked in television locally in New York as well as nationally including WAB

C, WNBC, WCBS, and CBS Sports to name a few. Originally from Washington, D.C., Ehrlich currently resides in New York City with his wife Debbie and son Jagger.For more than thirty-five years, Elliott Kalb has been working in the sports television industry, known nationally for decades as ＂Mr. Stats.＂

He is a 13-time Sports Emmy winner, as a writer/producer for NBC Sports, HBO Sports, and MLB Network. A noted sports historian who has authored five books, including Who’s Better Who’s Best in Basketball? and Who’s Better, Who’s Best in Baseball?, Kalb was the Senior Editorial Director of MLB Netwo

rk from 2008-2020, where he wrote, produced, and appeared on-air in hundreds of segments. He lives in New Jersey.

基於時序模型和圖神經網路之NBA季後賽勝負預測

為了解決NBA stats的問題，作者錢寧 這樣論述：

近年預測比賽勝負的研究大多有兩點問題，一是以賽後數據做為預測，也就是以比賽已經結束所記錄下的數據來預測該場比賽結果。這樣的做法並不符合真實世界的情況，因為不可能在賽前就得知該場比賽的數據，因此造成準確率失真；二是以球隊的平均數值表現進行分析和預測，這樣的作法並沒有考慮到個別球員在比賽中做出的貢獻，造成許多個別球員表現並未被充分利用，例如：球員個人的得分、失誤、犯規等…。除此之外，對於數據預測的方式多採取傳統的計算方式，例如：直接將前三場的球隊得分算平均，當作第四場的得分，這樣的作法並未考量到數據之間的相關性，造成預測的數據不精準。本論文提出基於時序模型與圖神經網路，以預測出季後賽的勝負，首先

，我們以球員當作點(nodes)，並以時序模型預測之球員表現當作點特徵(node features)，根據其在球隊上的位置關係建邊(edges)形成一張圖(graph)。其次，利用本論文所提出的圖神經網路架構進行預測，其中GAT的注意力機制(attention)將會選取圖中重要的點並計算出點表達式(node representation)，經由GCN做卷積(convolution)得出特徵向量後，再透過全連結層(fully connected)將點表達式轉換成圖表達式(graph representation)，以進行最後的勝負預測。本論文以美國職籃(National Basketball A

ssociation, NBA)2020-2021球季的資料進行實驗，傳統以三場平均(3-game-average)計算出數據並透過ANN預測，準確率為59.5%，而透過本論文所提方法進行預測的準確率達到76.9%，顯示本架構能夠有效預測比賽的勝負。