Name: 【TED】籃球最狂野的動作背後的數學--拉吉夫-馬赫斯瓦蘭｜TED Talks (【TED】The Math Behind Basketball's Wildest Moves | Rajiv Maheswaran | TED Talks)
Uploaded: 2021-01-14T05:41:59.000Z
Duration: 12 min 9 s
Description: 【看影片學英語】數萬部 YouTube 影片，搭配英漢字典即點即查，輕鬆掌握單字發音與用法，長久累積看電影不必再看字幕。

動名詞

My colleagues and I are fascinated by the science of moving dots.

And we're moving in our homes, in our offices, as we shop and travel

throughout our cities and around the world.

And wouldn't it be great if we could understand all this movement?

If we could find patterns and meaning and insight in it.

where we're incredibly good at capturing information about ourselves.

So whether it's through sensors or videos, or apps,

we can track our movement with incredibly fine detail.

So it turns out one of the places where we have the best data about movement

So whether it's basketball or baseball, or football or the other football,

we're instrumenting our stadiums and our players to track their movements

So what we're doing is turning our athletes into --

So we've got mountains of moving dots and like most raw data,

it's hard to deal with and not that interesting.

But there are things that, for example, basketball coaches want to know.

And the problem is they can't know them because they'd have to watch every second

of every game, remember it and process it.

The problem is a machine can't see the game with the eye of a coach.

So what have we taught the machine to see?

We taught it things like passes, shots and rebounds.

And then we moved on to things slightly more complicated.

Events like post-ups, and pick-and-rolls, and isolations.

And if you don't know them, that's okay. Most casual players probably do.

Now, we've gotten to a point where today, the machine understands complex events

Basically things only professionals know.

So we have taught a machine to see with the eyes of a coach.

If I asked a coach to describe something like a pick-and-roll,

and if I encoded that as an algorithm, it would be terrible.

The pick-and-roll happens to be this dance in basketball between four players,

So there's the guy on offense without the ball

the ball and he goes next to the guy guarding the guy with the ball,

and they both move and stuff happens, and ta-da, it's a pick-and-roll.

So that is also an example of a terrible algorithm.

So, if the player who's the interferer -- he's called the screener --

Or if he does stop, but he doesn't stop close enough,

Or, if he does go close by and he does stop

but they do it under the basket, it's probably not a pick-and-roll.

Or I could be wrong, they could all be pick-and-rolls.

It really depends on the exact timing, the distances, the locations,

So, luckily, with machine learning, we can go beyond our own ability

So how does this work? Well, it's by example.

So we go to the machine and say, "Good morning, machine.

Here are some pick-and-rolls, and here are some things that are not.

Please find a way to tell the difference."

And the key to all of this is to find features that enable it to separate.

So if I was going to teach it the difference

I might say, "Why don't you use color or shape?"

And the problem that we're solving is, what are those things?

that let a computer navigate the world of moving dots?

So figuring out all these relationships with relative and absolute location,

that's really the key to the science of moving dots, or as we like to call it,

spatiotemporal pattern recognition, in academic vernacular.

Because the first thing is, you have to make it sound hard --

The key thing is, for NBA coaches, it's not that they want to know

It's that they want to know how it happened.

And why is it so important to them? So here's a little insight.

this pick-and-roll is perhaps the most important play.

And knowing how to run it, and knowing how to defend it,

is basically a key to winning and losing most games.

So it turns out that this dance has a great many variations

and identifying the variations is really the thing that matters,

and that's why we need this to be really, really good.

There are two offensive and two defensive players,

getting ready to do the pick-and-roll dance.

So the guy with ball can either take, or he can reject.

The guy guarding the ball can either go over or under.

His teammate can either show or play up to touch, or play soft

and together they can either switch or blitz