"And Maradona has scored!"

「馬拉度納進球了。」

This moment goes down in history because of what the commentators could clearly see:

這個瞬間被寫入了歷史，因為評論員可以清楚地看到，

"That is why England is so furious, Maradona "has punched it in with his left hand.”

「這就是為什麼英格蘭如此憤怒，馬拉度納用他的左手把球打了進去。」

But in 1986, referees didn't have access to instant replays.

但在 1986 年，裁判員還沒有辦法即時回放。

They had to make judgment calls from the field, based on their limited perspective on what happened.

他們必須根據他們看到發生的事情的有限看法在現場做出判斷。

And their subjective view on it was that this goal was good.

而他們對這顆進球的主觀看法是，這是個好球。

This would never happen today, as technology has empowered referees to view moments again and again from multiple different angles before making a final decision.

這種情況在現在永遠不會發生，因為科技讓裁判能夠在做出最終決定之前從多個不同角度一次又一次地觀察。

And this year's World Cup features a technology that takes that a step further: 

而今年的世界杯採用了一項更進步的科技：

Judging when someone is offside — using AI.

使用 AI 判斷球員何時越位。

Alright, so, the simplest way of explaining offsides is that the offensive player has to have two defensive players between them and the goal, or be behind where the ball is.

簡單來說，越位就是，進攻球員必須在他們和球門之間有兩名防守球員，或者在球所在的位置後面。

Most of the time it's the goalkeeper plus one defender.

大多數時候是守門員加一名後衛。

For the most part, if any offensive players are behind this second to last defender while the ball is in play, they're offside.

在大多數情況下，在比賽進行中，如果有任何進攻球員在倒數第二個防守球員身後，他們就越位了。

That's Jeremiah Oshan by the way.

順便說一下，那位是 Jeremiah Oshan。

Soccer editor of SB Nation.

他是 SB Nation 的足球編輯。

Offside should be an objective call — either you're in front of this line, or behind it.

越位應該是一個客觀的判罰，你要麼在這條線的前面，要麽在它的後面。

What makes it tricky is that we're often judging with subjective perspectives, and it can be hard to tell when a player is teetering over the line.

但棘手的是，我們經常從主觀角度進行判斷，所以這很難判斷一名球員何時越位。

As this tweet by Dale Johnson of ESPN shows, the angle at which you see something really matters.

正如 ESPN 的 Dale Johnson 的這條推文所顯示的，你看待事物的角度非常重要。

These two images from the March 20th game between Liverpool and Nottingham Forest show the same moment in time from two slightly different perspectives.

這兩張來自 3 月 20 日利物浦對上諾丁漢森林的照片從兩個略有不同的角度展示了同個比賽瞬間。

In the image on the left #20 looks like he's in front of #3, but on the right, it looks like their positions are inverted.

在左邊的照片中，20 號球員看起來像是在 3 號球員的前面，但在右邊的照片中，他們的位置看起來是顛倒的。

If audience members only see an angle they feel is uncompelling, it can leave them unsure that the right call was made.

如果觀眾只看到他們覺得沒有說服力的角度，他們可能會疑惑裁判是否做出了正確的判斷。

Like in this October 7th game between England and the US.

就像 10 月 7 日英格蘭對上美國的比賽一樣。

"Maybe they're looking at an offside call potentially, but it looks like Sophia Smith is onside.”

「也許他們正在考慮判越位，但看起來 Sophia Smith 沒有越位。」

This call shocked even the commentators.

這個裁決連評述員都震驚了。

"No goal?!?"

「不算進球？！」

"Right there…is where they're saying…Sophia was offside already."

「就是這裡，這裡就是他們說 Sophia 已經越位了。」

This goal would have tied the match at 2-2, but because it was revoked, England won 2-1.

這個進球本可以將比分扳成 2-2 平手，但由於被取消，英格蘭隊以 2-1 獲勝。

It was revoked, in part, because of VAR.

進球被撤銷的部分原因是因為 VAR。

Video Assisted Referees were introduced in 2018, with the intention of making calls like this a little more objective.

影像輔助裁判（VAR）於 2018 年推出，目的是上述這樣的裁決更加客觀。

These refs are in a room, away from the match, but they have the advantage of seeing the event from 33 camera angles.

這些裁判待比賽現在外的一個房間裡，但他們有從 33 個攝像機角度觀看比賽。

If they see something they think a referee didn't or couldn't have seen, they can suggest that the footage be reviewed on the field monitor.

如果他們看到了他們認為裁判沒有看到或沒辦法看到的東西，他們可以建議在現場的螢幕上查看錄像。

This enhances the accuracy and objectivity of calls, but it still relies on perspective.

這增強了裁決的準確性和客觀性，但它仍然依賴於不同的視角。

For the 2022 World Cup, FIFA is introducing semi-automated AI offside technology.

至於 2022 年世界杯，FIFA 引進了 AI 半自動越位系統。

A sensor in the ball will relay its position on the field 500 times a second.

足球中的感應器以每秒 500 次的速度傳遞其在球場上的位置。

And 12 motion cameras mounted underneath the roof of stadiums will use machine learning to triangulate players' body positions.

還有 12 個安裝在體育館屋頂下的運動攝像機將使用機器學習來三角測量球員的身體位置。

This data can be used to create a 3D visualization of a play that can be viewed from any angle.

這個數據可用來 3D 視覺化任何觀看比賽的角度。

Like in this early test during a September match.

就像在 9 月進行的初賽一樣。

The virtual camera is able to fly around, giving an almost godlike perspective of the scenario.

虛擬攝像機能夠四處飛來飛去，為場景提供近乎神一般的視角。

There are no viewing angle limitations, no frame rate delays.

沒有視角限制，沒有幀速率延遲。

It's a near 1-to-1 recreation of the event, seemingly indisputable evidence for referees and audience members that this player's knee was offside by this much.

近乎是 1 比 1 還原比賽，對於裁判和觀眾來說，這似乎是無可爭辯的證據，可以證明這名球員的膝蓋越位。

Subjectivity isn't being totally removed from the equation though.

不過，主觀性並沒有完全從這個裁決方法中剔除。

The technology being only semi-automated means that human referees will still make the final calls, after taking what the AI shows under consideration.

該科技僅是半自動化的，這表示在查看 AI 顯示的內容後，人類的裁判仍將做出最終決定。

And that can be critical because while this tech can judge space flawlessly, it can't see everything. Like a player's intentions.

這可能很關鍵，因為雖然這項科技可以完美地判斷空間，但它無法看到一切，像是球員的意圖。

There was an MLS game between LAFC and Austin FC where a foul potentially occurred.

洛杉磯足球俱樂部和奧斯汀足球俱樂部有一場美國職業足球大聯盟的比賽，當時發生可能是犯規的情況。

The referee decided not give the penalty for subjective reasons, which was, you know, his touch was taking him away from the ball, which implied that maybe he wasn't really fouled as much as the replay made it kind of look like he was.

裁判出於主觀原因決定不判罰點球，這個癌覺得原因是，裁判認為球員的觸球讓他遠離了球，這意味著他可能並沒有真正犯規，因為重播讓他看起來像是犯規了 。

I thought that was actually a really good use of VAR, where he clearly was shown what happened and he was allowed to make a decision about whether or not he thought it was a foul or not.

我認為這是使用 VAR 一個很好例子，裁判清楚地看到發生了什麼，他可以決定他是否認為這是犯規。

Semi-automated AI offside tech is meant to make referees less reliant on subjective perspective. But it's just a tool.

AI 半自動越位系統旨在讓裁判減少對主觀判斷的依賴，但它只是一個工具。

How it'll change gameplay depends on how it gets used and ultimately, how it gets reconciled with what a human being sees on the field.

它會如何改變遊戲規則取決於使用方式，並最終取決於它如何與人們在場上看到的相協調。

Offside is a complicated rule, and this video only scratches the surface on it - but the new semi-automated AI offside system is already at work in the World Cup.

越位是一項複雜的規則，這段影片只是粗略地介紹一下，但新的 AI 半自動越位系統已經在世界杯啟用。

According to ESPN, in an early match between Qatar and Ecuador, the system made a correct offside call,

據 ESPN 報導，在卡達和厄瓜多爾的一場初賽中，系統做出了正確的越位判罰，

and the 3D representation gave fans clarity over a play that was somewhat hard to see — though there also seemed to be some dissatisfaction over how long it took to make that decision.

3D 視覺化讓粉絲們清楚地了解了一場有點難以看清的比賽——儘管似乎也有人對作出裁決所花的時間有些不滿。

In a game between Argentina and Saudi Arabia, though, the call was made much faster. 

不過，在阿根廷對上沙烏地阿拉伯的比賽中，裁決的速度快上許多。

Ultimately, while this tech can give human referees information more quickly, their decisions will always take some time.

最後，雖然這項科技可以更快地為人類裁判提供信息，但他們的決定總是需要一些時間。