How Many Assists Did Acie Law Really Have?
※ [本文轉錄自 jimcal 信箱]
作者: jimcal.bbs@ptt2.cc (jimcal.bbs@ptt2.cc)
標題: How Many Assists Did Acie Law Really Have?
時間: Tue Oct 23 16:34:28 2007
作者: jimcal (太誇張了吧 ) 看板: WolfCave
標題: How Many Assists Did Acie Law Really Have?
時間: Tue Oct 23 15:03:46 2007
這篇文章是用 telnet 打的 希望不要有排版錯誤或是亂碼出現...
我在訂了 Baseball Prospectus 之後，想起他們新增了 Basketball Prospectus
(http://www.basketballprospectus.com/ 有興趣可以瞧瞧 :P)
瀏覽一下看到這篇文章，由於我有注意 Acie Law，就翻譯出來分享。
原則上翻譯這件事還是有侵犯著作權之虞，假裝貴版是小眾市場沒有公開散佈，
也請大家低調 XD
http://www.basketballprospectus.com/article.php?articleid=14
October 17, 2007
Hometown Scoring
How Many Assists Did Acie Law Really Have?
by Ken Pomeroy
Sometimes, the most common statistics are taken for granted as being the
truth. It's assumed that the numbers we use represent an accurate historical
record but occasionally they do not. Anyone who has ever tried to do a
little scorekeeping on their own has surely experienced the frustration of
trying to keep up with the action. Even the basics like points and rebounds
are not easy to keep accurately. Official scorers in college basketball are
no different, except that they have to record much more than points and
rebounds.
有時候，最是平常的數據往往被當作事實般視為理所當然。但這些被視為精確歷史紀錄
的數據有時並不是那麼貼近事實。任何想要嘗試親自紀錄球賽數據的人都能夠深切體
驗到那種跟不上球員動作的挫折感。即使是像分數以及籃板這種基本的數據也不是那묊麼簡單可以解決。這對於在大學籃球層級的記分員來說也是一樣，特別是他們記錄的
不只是得分和籃板。
Though the scoring operation at a Division I game is sophisticated, there
are still errors made. In large part, these are random errors. Perhaps on
rare occasions a basket is assigned to the wrong player, and a little more
frequently a rebound is given to someone erroneously. Just because Player
A gets an extra rebound credited to him in a game, however, doesn't mean
he'll see his rebound totals inflated consistently the rest of the season.
This was just an unintentional error of an otherwise diligent scorekeeper.
即使在分區賽中的計分系統十分複雜，仍然有許多錯誤。大抵來說是一些隨機的誤失ꄊ。也許在一些罕見的情況裡得分被記到錯誤的球員身上，記錯籃板可能再多一些吧。
只是球員 A 在比賽中多得了一個籃板，並不因此在剩下的球季裡籃板就會爆增
。這只是另一個勤奮的記分員無心的失誤。
The judgment stats are a little different. Some scorekeepers subconsciously
employ a different definitions for a certain stats involving judgment like
assists, steals and even blocked shots. Statistically, there is more
variability in how scorekeepers track assists than any other basic basketball
statistic.
但對於需要仰賴記分員個人判斷的數據就有些不同了。有些記分員對於像助攻、抄截
甚至是阻攻這樣的紀錄有著不同的定義。統計上來說，對於助攻這項數據，比起別的
籃球數據，記分員的判斷可能有更多的變數。
Pages 28 and 29 of The Official NCAA 2007 Basketball Statistician's Manual
http://tinyurl.com/2s4dld (warning: PDF) defines an assist for college
basketball:
NCAA 2007 紀錄組官方手冊是這樣定義大學籃球的助攻：
A player is credited with an assist when the player makes, in the judgment of
the statistician, the principal pass contributing directly to a field goal
(or an awarded score of two or three points)? Philosophy. An assist should
be more than a routine pass that just happens to be followed by a field goal.
It should be a conscious effort to find the open player or to help a player
work free?
當球員作出一個 "原則上" 的傳球，且這個傳球直接地貢獻了一個投籃命中 (或者是
被紀錄為得分的兩分或三分 ) 這個球員將獲得助攻紀錄乙次。 就球場上的認知，助
攻應該不只是個平常的傳球，後面剛好跟著一個投籃命中。應該是 "找到有空檔的球
員" 或者 "幫助球員找到空檔機會" 。
The manual goes on to detail some scenarios that further clarify when an
assist should be awarded. It's fairly specific, and it is comprehensive about
defining an assist, although in the end there is still some room for
interpretation. After reading the manual, I concluded that there's not as
much room for judgment as one might have thought. In most cases, the process
of awarding an assist is standard across college basketball.
手冊上有更多的情境深入探討怎樣可以給助攻。相當仔細且容易理解，即便在最後仍然
留有一些解釋空間。在讀完手冊之後，我的結論是當紀錄時沒有什麼時間可以去思考。
在大多數的情況，給助攻的程序在大學籃球裡就是那樣的。
With biased errors, unlike random errors, there are ways to sort out where
the biases exist, and whom those errors benefit. In this case, we can compare
how often a team is credited with an assist at home to how often they get an
assist away from home. Since scorekeepers are largely the same people at each
home game, we can single out which teams have scorekeepers that ration assists
like they're gold and those that make even the most selfish players look like
Steve Nash.
對於有意的紀錄錯誤，就不像隨機產生的錯誤一樣。有許多方式可以找出到底哪裡出了
錯，而誰因為這些錯誤而受益。我們可以比較球隊如何在主場獲得助攻以及在客場獲得
助攻。因為在主場記分員大抵都是相同的人，我們可以剔除給助攻時吝嗇得像從自己口
袋掏錢一樣以及那些把最自私的球員變得像 Steve Nash 的記分員。
The most generous scorekeepers were associated with the following five teams
in 2007
底下是 2007 年最慷慨的記分員，分屬於這五隊。
Assist Percentage (A/FGM)
Home Away
Texas A&M 78.5 45.2
Sam Houston St. 82.6 55.0
Evansville 72.1 47.3
South Florida 74.9 52.1
Cal St. Fullerton 69.0 47.9
It turns out that the king of assist bias is the table at Texas A&M. At home,
the Aggies recorded assists on 78.5% of their made field goals. It's a
percentage that is ridiculous to the point of being unbelievable.
Only one team in the country cleared an assist rate of 70% on the season
and that was Northwestern at 71.6%. A&M did play some cream puffs at home,
so perhaps a figure close to 80% could be attained over 19 games, which was
the length of their home schedule.
檯面上看到的助攻王是 Texas A&M。在家裡，Aggies 78.5% 的投籃命中都是助攻產生
。太誇張了！只有 Northwestern 的 71.6% 是全國到哪都超過 70 % (應該是這個意思
吧) A&M 的確在主場安排了一些軟柿子球隊，因此讓這個數據接近 80% 大約 19 場
，也就是上季他們在主場的場次數。
Any hope of suspending disbelief is lost by knowing that away from Reed Arena
, A&M was credited with assists on just 45.2% of their made baskets. That
figure is significantly below the national average assist rate of 55.1%. It's
a rate that, sustained for the entire season, would have ranked Texas A&M
323rd--14th-worst--in the country in sharing the basketball. So to summarize:
At home, Texas A&M was one of the best assisting teams in college basketball
history. Away from home, they were the worst major conference team in sharing
the ball.
在知道離開 Reed Arena (應是 A&M 的主場) 之後的情況，任何期待這是一場誤會的
希望都將落空。A&M 在客場僅僅有 45.2% 的投籃命中帶有助攻。這個數字低跟全國平均
助攻數的 55.1%。這個延續了一整季的數據會讓 Texas A&M 在球的流動上排在 323名，
全國倒數 14 名。結論是，在主場， Texas A&M 是大學籃球史上最會助攻的球隊，在
客場，他們是全聯盟最差的。
Away from home, A&M was playing in front of all sorts of different
scorekeepers, so it's unlikely that there was a conspiracy among all or even
most of them to not record Aggies' assists. No, the only explanation is that
assist inflation was at record levels in College Station in 2007. It was a
phenomenon that didn't go unnoticed in the rest of the conference. Texas took
the unusual step of voiding assists that were credited to its own team in a
game at Texas A&M. (Note: under NCAA rules this a step that doesn't affect
the official statistics, only Texas' internal records.)
在客場， A&M 在各種不同的計分員手下比賽，因此要說這是阿共仔的陰謀或是大部分
的記分員都沒有記到 Aggies' 並不太可能。唯一的解釋就是這個助攻的誇大創下了在
A&M 主場的紀錄。而這個現象並沒有悄悄地在聯盟裡的其他地方發生。 Texas 用不尋
常的方式避免助攻只記到他們自己球隊裡。
So how many assists did the Aggies really have? Let's use their road assist
percentage as a guide. The average NCAA scorekeeper gives the home team five
more assists per 100 made field goals than he/she gives the opponent. This
could be real, but it's probably not. You wouldn't think there would be a
home-court advantage for passing, especially since we are accounting for the
number of field goals made in this study. If we evenly distribute that 5%
bias between the home and road team, Texas A&M's true assist percentage on
the road was 45.2% +2.5%, or 47.7%. If we assume this was their true assist
percentage in all games, then we can apply that figure to the 908 field goals
A&M made for the season. This yields a "real" assist total of 433--158 fewer
than were actually recorded.
所以到底 Aggies 到底有多少助攻呢？ 讓我們用他們的客場助攻率來作為基準。平均
來說，NCAA 的記分員們每一百次出手命中當中，給主場隊伍多五個助攻。這可能是真的
，但也不見得。你不會認為在傳球上會有主場優勢，特別是我們計算的是投籃命中這個
數據。如果我們平均地分配這 5% 的偏差到主客隊，Texas A&M 真正的助攻率在客場修
正為 47.7%。如果我們將這個數字當作他們真正的助攻數，那我們可以應用這個數據到
本季他們所命中的 908 個投籃命中當中。這產生出真正的助攻總數是 433，比原來少了
158個。
Now to the question that is the basis for this article. Applying this
reduction equally to each A&M player would reduce Acie Law's assist total
from 169 to 124, or from 5.0 per game, ranking 63rd in the nation, to 3.6 and
out of the top 200. Law was credited with a career-high 15 assists in A&M's
home win over Texas in February. We don't know how many he really had, but
it's safe to say that 99% of NCAA scorekeepers would have recorded a lower
number.
現在這個問題就是本篇文章的基礎。把這個減少的助攻數平均地分配到 A&M 的球員，
將會使 Acie Law 的助攻總數從 169 來到 124，每場從 5 個，聯盟排名第63，下降
到 3.6個，聯盟排名200以外。 Law 在二月那場主場勝拿到生涯最高的 15 個助攻。
我們不知道他真正應該有多少，不過可以說 99% 的 NCAA 記分員都會記上一個更低的
數字。
Before wrapping this up, it's only natural to look at the opposite end of the
spectrum. While on balance, there's a tendency for home scorekeepers to give
their players an assist boost, this isn't true everywhere. The folks with the
strictest definition of an assist?
在下結論之前，自然得從另一個角度看看。為了平衡，主場的記分員有可能對他們的
球員給多一些助攻，不過這不是到哪都適用的。誰會是對助攻判斷最嚴厲的記分員呢？
Assist Percentage (A/FGM)
Home Away
New Mexico St. 46.3 60.1
Northern Colorado 50.9 60.6
Lafayette 57.7 67.1
Illinois 57.8 66.0
Long Island 42.3 50.4
Nobody was stingier about doling out assists than the table at the Pan
American Center, where they ignored about one out of every four assists that
their counterparts in other arenas were counting. This means that New Mexico
State point guard Elijah Ingram was better at setting up his teammates than
his stats suggest. Officially, he had 35 assists at home. Had he recorded
assists at the rate he did on the road, he would have had 47 home helpers.
沒有人會比 PAN American Center 更吝於發放助攻。相較於別的球場，他們平均四個
就忽略了一個。這代表 New Mexico State 的控衛 Elijah Ingram 比起他的數據更能
組織他的隊友。正式的來說，他在主場有 35 個助攻。要是以他在客場的表現來看，
他可以拿到 47 個。
That might not seem like a dramatic difference, but you can really get a feel
for how subjective assists are by magically trading the Aggie scorekeepers in
College Station for the ones in Las Cruces. If we could do that, our best
estimate of Ingram's home assist total would have it increasing to 78, or
more than doubling. His assist rate for the season would have risen from
17.3% to 26.4%, or from a below-average playmaker to a respectable one,
ranking him just outside the top 150 nationally. Similarly, Law's assist rate
would have decreased from 30.8% to 19.7%, making him look like a score-first
point guard--which is closer to the truth.
這或許不是相當大的差距，但是你可以感受到助攻是如何地被 Aggie 的記分員給主觀
地轉換。如果我們可以這樣做，我們預測 Ingram 的主場助攻數可以達到 78 個，甚至
是兩倍。他的助攻率可以從 17.3% 提升到 26.4%，或者說從低於平均的指揮官成為令人
尊敬的指揮官，使他成為全國 150 名的控衛。同樣地， Law 的助攻率會從 30.8% 下降
到 19.7 %，使他變成一個得分第一的控衛，而這是比較貼近真實的。
For the most part, scorekeepers across the nation have a similar view of an
assist. As long as D-I nation spans more than 300 teams, however, there will
be outliers. In this case, it may have influenced the view of Acie Law's and
Elijah Ingram's talents. More than likely, Ingram was better at setting up
his teammates, even though the stats indicate that Law was easily the better
assist man. There is no statistic in major sports as subjective as the
basketball assist, and we should consider that before reading too much into
a player's or team's assist rate.
最主要的，全國各地的記分員對於助攻都有相似的觀點，只要像這樣全國有三百隊的
分區，總是會有一些 outliers (這個我統計課學到就是這樣叫，中文是？)。在這個
例子當中，或許會影響到對 Acie Law 以及 Elijah Ingram 的天賦判斷。即使數據
上 Law 很容易被認為是個能夠助攻的人，但是 Ingram 卻可能在這件事上比他做得
更好。在主要的運動上沒有一個數據像籃球的助攻這麼地主觀，而在深入了解一個
球員或球隊的助攻率之前，我們都應該仔細的想一想。
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關於洋基、七六人的部落格
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修改了一些翻譯上的問題，也謝謝板眾的回應。的確，有時就連數據本身都不見得可以
反映出球員真正的實力，有太多球員並非在數據上表現亮眼卻是球隊不可或缺的力量。
會翻譯這篇文章的原因只是在籃球界終於也有像 Baseball Prospectus 這樣討論數據
的網站 (我之前都只有看 82games)，剛巧這篇文章的主角是貴板受矚目的新人。想說
拿來這邊比較能引起迴響吧？我也不覺得此文一出 Acie 就會被看衰，攻擊型的後衛
說不定後市還比較看好哩！(我自己 FB 也是有選他阿 XD)
※ 編輯: jimcal 來自: 220.140.209.212 (11/02 23:11)
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