@@reggin_spelt_backwards Lockdown defence like how Iggy locked down Lillard in the final minutes of game 2. Though it pains me to say, the chance that Leonard would've made that shot would've been reduced significantly with a proper defender guarding him. But it's super Kawahi we're talking about so you never know!
great content Bloomberg!! As a current PhD student who works in Data Science and is a huge huge sports fan, this video really inspired me! THANK YOU !!
I don't know why she would doubt herself getting the job, she seemed like the ideal candidate. Gender aside, how many math majors also played D1 basketball?
Literally am going to be a data scientist because of this. I hope I can work for an mls team with data analytics with my soccer background. Amazing and inspiring video.
Data analytics has become very important in other sports, such as baseball (sabermetrics), and in public health, criminology, advertising and marketing, political science, military science and, of course, economics. And the mathematics is far more than number crunching. One is always looking for subtle, hidden data (signals).
3:05 love the explanation of pick & roll to a layman there, yes indeed the pick is the human shield & then once the human shield has shielded, the human shield proceeds to run to the basket
Since I'm also from Croatia, currently a Computer science student and started playing basketball since I was 7, this inspired me immensely. I even wrote Ivana an email to which she unfortunately didn't respond, so I was thinking maybe you guys have some tips and guidance how to specialize in this concrete field (which literature, courses, basketball-related tips, anything). Thanks in advance!
Not only that, she probably has a higher chance to be hired as industries try to create more diverse environments. Don't get me wrong, she probably deserves the job but bringing gender over simply the love of basketball is sad.
This is the type of stat person a team needs. She is someone who is a numbers genius but knows enough about basketball to understand that the numbers change in certain situations. For example 3 pointers are better then 2 pointers but its easier for defenders to guard the 3 point line then it is the guard mid range shooters. The thing is since she is a basketball player she understands this while others will say, "all you have to do is shoot 3s and lay ups"
Well somebeody needs to upgrade or amend the algorithm and put more situations like what its worth to shoot a 3 pointer when you have a 2 or 3+ posession lead. That is the main thing that is wrong with how the league has interpreted the data about 3 point shots. Too many teams lose leads because they keep shooting 3's when they have a lead or a fastbreak. Also, if you miss 2 or more consecutive 3 point shots, but the other team is scoring also, wouldn't it make sense to make 3 2's ins tead of bricking two 3 point shots. You could have easlily reduced your lead by shooting the easier shot in transition. I can understand taking 3's if the team is exchanging shots.
Houston went nuts with analytics shooting 3s. They are a seriously flawed team. 27 consecutive missed 3s is probably something analytics team did not anticipate happening
@@olayinkaanifowose5099 Lol that's literally what we're attempting with Machine Learning and advancing AI. A complex organism's "conscience" is an amalgamation of biological chemical circuitry, and yes- that *can* be broken into numerical values.
Gender shouldn’t matter, why do they always have to bring it up? All that did matter was that she had a profound understanding of the game of basketball and a very intellectual mathematician mind. Who cares if you’re not a male? You are hired for your mind and skills, she perfectly fits for analytics in the NBA. Edit: You’re*
@Ultra Instinkt Gender didn't matter. In fact, in a time like this where companies are chastised for not hiring more women regardless of their qualifications and pushing for equality of outcome, it would have been a lot more logical for her to assume she would have got the job. The field she's working in being male dominated is purely because most women don't study for that specific field and has less to do with companies specifically hiring males.
@Ultra Instinkt, And yet... all the evidence and facts demonstrate the opposite of your position... your biased misconceptions are not what actually is going on.
@Mark Halve I agree 100%. I don't know why they had to bring up the fact that she's in a male dominated field & has to do well cuz she's represent all women. In 2019, you'll get a job like this if you're qualified, regardless of your gender. As the video mentioned, she is extremely qualified!
I can appreciate all the Data Analytics post game. I just don't understand all these analytics needed pre-game. There will always be a % of randomization during the game that can completely change and destroy all these analytics...... Kawhi is a perfect example for this
The analytics are essential “pre game” because it provides insight into most effective strategies based on evidence rather than conjecture. It’s why when people speak of teams of the past beating today’s greats, it becomes laughable from a data and analytics perspective as today’s game has evolved to understand that efficiency matters above all else thus the transition away from the “glory days” where post ups and midrange jumpers were the norm.
Of course there will be outliers like kawhi but some are predictable you could predict if a team is gonna win by analysing various metrics example Stephs last quarter shooting percentage you might think that he’s gonna shoot more and your gonna guard him but kerr might have slowly been making Klay or Poole taking the shots cause he knows Steph is gonna be covered his subtle signals can be obtained through a analysing shoots/ quarter or shoot/ last few minutes etc and also the individual contribution to the team ( like by having this person on the court what wins are we achieving etc )could be analysed based on which salaries playing time etc can be determined
Analytics have its benefits, but going to the extreme would make the sport not human. In the playoffs, it is more important for players to exploit matchups, rather than looking at advantages in an analytical perspective.
2 minute time: Team A takes 12 three pointers only and makes 3 shots for 9 points 25%. Team B takes 12 two points and makes 6 plus 2 fouls and they make 3 out of 4 foul shots. Team B has 15 points. Even if you give Team A another three they have 12 points. Team B still wins and Team A shot 33% from three which is close to avg. The point is it matters who is tanking the threes and who is taking the FGs, not just a matter of stats, it’s both
Can you become this with just a Bachelor's in Engineering and a Masters in Data Analytics? Like not have to get a PhD? Because being a data scientist for the NBA sounds hella cool ngl
Actually just checked their job postings, yes it seems like PhD is not a requirement. But hmm you gotta still know your stuff pretty well I'm sure. Also all the jobs are in NY which I hate. Well, after getting a couple more years experience I might give it a shot! I also don't have that Masters yet :P but I hope to apply soon
Well the area they play is across the river and Camden and Philadelphia both border it. like it’s so close it’s basically philly. Camden is right next to philly connected by a bridge literally all
I’m stuck between completing a MSc in Business Analytics and an MSc in Data Science. I know the programs vary between from University to University but I am still interested in hearing all about your experience studying Business Analytics and what it’s been like for you after graduating.
You tried to imply that the three-point revolution came about because of analytics. If anyone has any doubts, it wasn't analytics that did it, it didn't even start with the Splash Brothers.
She is a data scientist, and she can't tell that the reason there are less women hired as data scientists, is because less women pursue that carreer relative to men, and not because of a bias in the hiring process. She had equal chances when she sent her postulation than the men ceteris paribus.
Contrary to what she said there's more chance you'll make it if you're a woman though due to diversity quotas, if your not then you'll have to work your ass of.
Actually it would probably be useful since it could help dictate best and most efficient shooting form based on historical data. Whether or not Ben Simmons will ever be able to do it is another question entirely
Daryl Morey and the analytics folks have been doing this for the last 20 damn years. Sabermetrics, shot value, efficiency ... and it hasn't won them a single damn Championship. Numbers only take you so far: in the end, it's all down to talent, grit and effort when everyone's arms are too damn tired to shoot the same 45 percent arc they do in the regular season. Not to say that it isn't useful, of course, but the team with the better chemistry and the better coaching adjustments beats a bunch of numbers adjudging tendency and conversion rates any day, every day.
this data works better for MLB or NFL cause in the NHL/NBA the coaches usually go with gut feeling and a name like Reddick or Leonard. Though I will say that thanks to this data now every team has deadly 3 point average compared to 20 yrs ago where you had 1 or 2 players who could shoot from behind the 3 pt line.
I don't think analytics will make Ben Simmons ace his shots..lol. At least that's not the goal. Just imagine the wealth of biometric data, and player-ball movement stats they're getting from their analytics teams. Now that's gold for the Sixers and the NBA at large.
Why is this necessary? So they analyze players game? They write up some report to the sixers? "Okay Jimmy you have a 60% chance of making all your right handed drive ins 15ft away from the basket when a pick is set"...
I think ds jobs have more males than females is not due to gender, or in this case, industry, but more due to fewer candidates with interest in STEM during education and follow through after graduation, just IMO
Jobs with people holding data scientist titles AREN'T entry level jobs for the most part. Look at who's already working in those fields.. Typically people already working with domain expertise tend to move into those jobs... probably already male dominated..
She has a better jump shot than the sixers star point guard. Lol
lol
hold this w real quick
ooof. all the science in the world couldn't stop Kawhi in that series
Name one thing that could have stopped him lol
@@reggin_spelt_backwards Lockdown defence like how Iggy locked down Lillard in the final minutes of game 2. Though it pains me to say, the chance that Leonard would've made that shot would've been reduced significantly with a proper defender guarding him. But it's super Kawahi we're talking about so you never know!
My Reply Notifications are OFF Kyle Lowry
Analytics cannot stop Embiid from acting like a shooting guard.
Daniel Sin Analytics can’t stop Embiid eating pre-game burgers on the court either
great content Bloomberg!! As a current PhD student who works in Data Science and is a huge huge sports fan, this video really inspired me! THANK YOU !!
I am studying economics, we use lots of math, but obviusly not as much as a math student. Do you think I can become a data scientist?
So happy to read this - all the best to you!
@@tomconnors5697 :)
@Aki Ito :)
@@leoperez6737 you are missing the programming portion.
She has the perfect dream career!
Yo for real! So nice!
What’s the percentage of Ben Simmons developing a jumper??
*probability
AisuruMirai you right! My bad! 🤣
never it's non existent
-10%
2%
After 2 weeks of study, the 10-man analytics team presented their result to the coaching staff. Simmons can't make a three.
Oh damn. Nobody could’ve guessed that.
More like they spent time looking at everyone else and forgot to look at themselves..
Nice one.
But then devised a plan to zig while the rest of the league zags
I don't know why she would doubt herself getting the job, she seemed like the ideal candidate. Gender aside, how many math majors also played D1 basketball?
Tim Nelson also 25# isn’t that low of a share, there were 10 people on just her research team
Tobias Bengtsson 75-25 is a very significant majority lol, not engineering school level, but still
the real problem with the world is that intelligent people are full of doubts, while stupid people are full of confidence - charles bukowski
TheMadeGuy the smarter you are, the more you realize what you don’t know. I think that’s partially where it comes from.
Jason Li considering there were ten people on her team that’d mean if the numbers Carrie over there’d be at least 2 women on it
Literally am going to be a data scientist because of this. I hope I can work for an mls team with data analytics with my soccer background. Amazing and inspiring video.
can i be your running mate?
Hey brother how is it going, have any social media handle where I could pick your brain and talk to you on?
Me too bro
I am really happy for her! Wish her the best of luck on her journey 💯
Data analytics has become very important in other sports, such as baseball (sabermetrics), and in public health, criminology, advertising and marketing, political science, military science and, of course, economics. And the mathematics is far more than number crunching. One is always looking for subtle, hidden data (signals).
Is the math mostly statistics or does it also involve linear algebra and calculus ?
I'm really glad she found her dream job with both of the things she is passionate about.
3:05
love the explanation of pick & roll to a layman there, yes indeed the pick is the human shield & then once the human shield has shielded, the human shield proceeds to run to the basket
She’s living her dream!! That’s amazing!!
thank you bloomberg! great content as always
Bloomberg is always coming up with interesting insightful stuff. Unlike others in Mainstream media outlets.
Since I'm also from Croatia, currently a Computer science student and started playing basketball since I was 7, this inspired me immensely. I even wrote Ivana an email to which she unfortunately didn't respond, so I was thinking maybe you guys have some tips and guidance how to specialize in this concrete field (which literature, courses, basketball-related tips, anything).
Thanks in advance!
You got it, I hope everything is working fine for you now.
Great content. Kudos to ya Bloomberg 👏
26% of women being data scientists does not mean they have a lower chance of being hired. How can a data scientist not understand that
That was strange to me too.
Not only that, she probably has a higher chance to be hired as industries try to create more diverse environments. Don't get me wrong, she probably deserves the job but bringing gender over simply the love of basketball is sad.
discrimination. it's real, beyond data.
the graphic showed that 26% of data scientists were women; not that 26% of women were data scientists.
today's journalism always slaps you with that prejudice stance, and are we even surprised?
This is the type of stat person a team needs. She is someone who is a numbers genius but knows enough about basketball to understand that the numbers change in certain situations. For example 3 pointers are better then 2 pointers but its easier for defenders to guard the 3 point line then it is the guard mid range shooters. The thing is since she is a basketball player she understands this while others will say, "all you have to do is shoot 3s and lay ups"
Well somebeody needs to upgrade or amend the algorithm and put more situations like what its worth to shoot a 3 pointer when you have a 2 or 3+ posession lead. That is the main thing that is wrong with how the league has interpreted the data about 3 point shots. Too many teams lose leads because they keep shooting 3's when they have a lead or a fastbreak.
Also, if you miss 2 or more consecutive 3 point shots, but the other team is scoring also, wouldn't it make sense to make 3 2's ins tead of bricking two 3 point shots. You could have easlily reduced your lead by shooting the easier shot in transition. I can understand taking 3's if the team is exchanging shots.
amazing life and career she' having!!
5:43 it is not "sort of" the ideal mix, it is a perfect mix
Houston went nuts with analytics shooting 3s. They are a seriously flawed team.
27 consecutive missed 3s is probably something analytics team did not anticipate happening
I am pretty sure the analytics people did not tell the Rockets to not play defense.
Thats team strategy, you're missing the team BUILDING strategy.. maybe they don't have the proper personnel..
Everything can be broken down into numbers. That’s why we have physics to explain life in numbers.
It can only be done by Russians and Asians though
@@archiej6386 Of course not by people like you, smh.
That's basically what chaos theory is, if you like this video you would love that.
Zachary Laid Finding Freedom break down consciousness into numbers please, then process it to generate new consciousness
@@olayinkaanifowose5099 Lol that's literally what we're attempting with Machine Learning and advancing AI. A complex organism's "conscience" is an amalgamation of biological chemical circuitry, and yes- that *can* be broken into numerical values.
Data science + business degree is lit
Sounds like Business Analytics is what you’re after
I can fully understand but it is really amazing how data science have enlarged the importance of such small areas which were neglected in the past.
Gender shouldn’t matter, why do they always have to bring it up? All that did matter was that she had a profound understanding of the game of basketball and a very intellectual mathematician mind. Who cares if you’re not a male? You are hired for your mind and skills, she perfectly fits for analytics in the NBA.
Edit: You’re*
@Ultra Instinkt Gender didn't matter. In fact, in a time like this where companies are chastised for not hiring more women regardless of their qualifications and pushing for equality of outcome, it would have been a lot more logical for her to assume she would have got the job. The field she's working in being male dominated is purely because most women don't study for that specific field and has less to do with companies specifically hiring males.
@Ultra Instinkt,
And yet... all the evidence and facts demonstrate the opposite of your position... your biased misconceptions are not what actually is going on.
Mike Halve
True
@Mark Halve I agree 100%. I don't know why they had to bring up the fact that she's in a male dominated field & has to do well cuz she's represent all women. In 2019, you'll get a job like this if you're qualified, regardless of your gender. As the video mentioned, she is extremely qualified!
It was mentioned purely for story telling purposes, It makes what she's doing seem more heroic for a lack of a better word
I can appreciate all the Data Analytics post game. I just don't understand all these analytics needed pre-game. There will always be a % of randomization during the game that can completely change and destroy all these analytics...... Kawhi is a perfect example for this
Daryl Morey's been foaming at the mouth over analytics for the last 20 years. It hasn't won him a single Championship.
The analytics are essential “pre game” because it provides insight into most effective strategies based on evidence rather than conjecture. It’s why when people speak of teams of the past beating today’s greats, it becomes laughable from a data and analytics perspective as today’s game has evolved to understand that efficiency matters above all else thus the transition away from the “glory days” where post ups and midrange jumpers were the norm.
Of course there will be outliers like kawhi but some are predictable you could predict if a team is gonna win by analysing various metrics example Stephs last quarter shooting percentage you might think that he’s gonna shoot more and your gonna guard him but kerr might have slowly been making Klay or Poole taking the shots cause he knows Steph is gonna be covered his subtle signals can be obtained through a analysing shoots/ quarter or shoot/ last few minutes etc and also the individual contribution to the team ( like by having this person on the court what wins are we achieving etc )could be analysed based on which salaries playing time etc can be determined
Pity the article devolved into more talk about male/female percentages in careers.
10 (wo)man analytics team. Very impressive.
Data analytics is actually more domain knowledge than math. The math is straightforward, but the domain knowledge goes very deep.
Awesome new segment, Bloomberg!
More power to you Ivana!
Thank you bloomberg. This was very knowledgable and it inspires me
the trend of the spread offense and more threes was started by steph and the warriors.
Take more 3 point shots... Metaphor for life
I admire your courage and passion. Keep it up!
Analytics have its benefits, but going to the extreme would make the sport not human. In the playoffs, it is more important for players to exploit matchups, rather than looking at advantages in an analytical perspective.
Great and inspirational video!
data scientist/music producer here i come!!!!
Very lucky to have such opportunities in the USA...we do not have such opportunities out here in Africa ..it's actually my dream job
2 minute time: Team A takes 12 three pointers only and makes 3 shots for 9 points 25%. Team B takes 12 two points and makes 6 plus 2 fouls and they make 3 out of 4 foul shots. Team B has 15 points. Even if you give Team A another three they have 12 points. Team B still wins and Team A shot 33% from three which is close to avg. The point is it matters who is tanking the threes and who is taking the FGs, not just a matter of stats, it’s both
Can you become this with just a Bachelor's in Engineering and a Masters in Data Analytics? Like not have to get a PhD? Because being a data scientist for the NBA sounds hella cool ngl
Actually just checked their job postings, yes it seems like PhD is not a requirement. But hmm you gotta still know your stuff pretty well I'm sure. Also all the jobs are in NY which I hate. Well, after getting a couple more years experience I might give it a shot! I also don't have that Masters yet :P but I hope to apply soon
Very inspiring. Great video!
This is such a dope story. She's revolutionizing the GAME!!!!
ese tiro de kawhi fue una locura y evento inevitable, que buen trabajo que tiene me gustaría poder llegar a donde esta algún día
I bet her data says, get rid of Ben Simmons.
Loool bro
Simmons to LA confirmed lol
Never understood why they play in Philly but practice in Jersey
Well the area they play is across the river and Camden and Philadelphia both border it. like it’s so close it’s basically philly. Camden is right next to philly connected by a bridge literally all
Its like Newark and New York almost
Brotherly Love Edits only difference is it’s by the water front away from the rest of Camden South North East and Cramer Hill
Tax break
What a dumb question
Loved this video, thank you.
Smart, nerdy and athletic... love it!
Great job.
i like how they filmed this before the playoffs, when none of this stuff matters
Amazing content. Data is simply awesome.
I would love a job like this. I'm working on my Master's in Business Analytics. Hopefully, I can land a job in something similar
You got this
I’m stuck between completing a MSc in Business Analytics and an MSc in Data Science. I know the programs vary between from University to University but I am still interested in hearing all about your experience studying Business Analytics and what it’s been like for you after graduating.
This video was awesome!
You tried to imply that the three-point revolution came about because of analytics. If anyone has any doubts, it wasn't analytics that did it, it didn't even start with the Splash Brothers.
You are a true inspiration..
She is a data scientist, and she can't tell that the reason there are less women hired as data scientists, is because less women pursue that carreer relative to men, and not because of a bias in the hiring process. She had equal chances when she sent her postulation than the men ceteris paribus.
Very moving piece. Thank you.
Very interesting and impressive! You are doing great guys!
Amazing story!! Thank you for this!!
Interesting, never thought you'd analyze sports data like this
The person with the best game plans is the person who can detect patterns
Math in sport gives you an edge. Who knew!!
Very inspiring! I will make it one day!
Contrary to what she said there's more chance you'll make it if you're a woman though due to diversity quotas, if your not then you'll have to work your ass of.
So is this how NBA 2K visual concepts are able to determine… player attributes, Tendencies, athleticism, Defense, offense and so on???
So cool!!😊
U don't need a data scientist to teach Ben Simmons how to shoot 🤔
Actually it would probably be useful since it could help dictate best and most efficient shooting form based on historical data. Whether or not Ben Simmons will ever be able to do it is another question entirely
Daryl Morey and the analytics folks have been doing this for the last 20 damn years. Sabermetrics, shot value, efficiency ... and it hasn't won them a single damn Championship. Numbers only take you so far: in the end, it's all down to talent, grit and effort when everyone's arms are too damn tired to shoot the same 45 percent arc they do in the regular season. Not to say that it isn't useful, of course, but the team with the better chemistry and the better coaching adjustments beats a bunch of numbers adjudging tendency and conversion rates any day, every day.
Hopefully I can get some kind of data analyst job before i graduate =( this looks real cool, but sadly I think ill need a masters.
this was a great cover. data science for the win!!
how can I get a career like this? I specfically want to work in sports and performance. will a masters degree in computer science/ data science help?
this data works better for MLB or NFL cause in the NHL/NBA the coaches usually go with gut feeling and a name like Reddick or Leonard. Though I will say that thanks to this data now every team has deadly 3 point average compared to 20 yrs ago where you had 1 or 2 players who could shoot from behind the 3 pt line.
Thanks, Rajiv Maheswaran!
Nice. I wish her the best!
sixers: how do we win?
data scientist: lose 300 games in a row
@Yash Agarwal the Perfect Work !
She got a better jumper than Ben Simmons for real
Shout out to njit!!! Less go!!
Love that girl, all the best and have a great future, no one can stop you 👍
The ability to diversify one's game as an individual...................
NEVERMIND
I don't think analytics will make Ben Simmons ace his shots..lol. At least that's not the goal. Just imagine the wealth of biometric data, and player-ball movement stats they're getting from their analytics teams. Now that's gold for the Sixers and the NBA at large.
I don't need PhD for that. I just need NBA 2k
and you are not paid for what you are doing
Cool job! Hope she finds some strategy that brings back the post game.
Cool, you love what you are doing!
I'm also becoming a ML Engineer!
*an ML
Why is this necessary? So they analyze players game? They write up some report to the sixers? "Okay Jimmy you have a 60% chance of making all your right handed drive ins 15ft away from the basket when a pick is set"...
Pretty sure every coach in any sport analyzes their team...
bravo Ivana!!
Analytics have made sure that all roster spots are filled with skilled players. No more 12th man ! No garbage time only fan favorites. Depth.
You sir are forgetting about TJ McConnell and the Sixers love for using him.
Maxi Kleber
There is a magnet in the ball and in the rim. NBA decide whether shot goes in or not...
She should also analyse Ben Simmons need to shoot 3s in the modern game
such an encouraging video! Best wishes to Ivana!
After current season, 6ers need to reassess the standards of competency of these data scientists lol
Who'll win?
PhD mathematicians, computer scientists a lot of math, Philly fans, Joel embiid, and the whole 76ers team.
Or
One klawy boi
She is from my country of Croatia the first Croatian women in NBA 💪💪💪💪🇭🇷🇭🇷🇭🇷🇭🇷🇭🇷
Great story! Very interesting!
I think ds jobs have more males than females is not due to gender, or in this case, industry, but more due to fewer candidates with interest in STEM during education and follow through after graduation, just IMO
Jobs with people holding data scientist titles AREN'T entry level jobs for the most part. Look at who's already working in those fields.. Typically people already working with domain expertise tend to move into those jobs... probably already male dominated..
It's obvious, she's a data scientist and can't tell that?
She is awesome
it's a new world of cross interests!
I love it
This is so cool
Curry started the rise in increase in 3 pointers