I have the feeling the reporter doesn't know what they're talking about:
"For example, if the Raptors were measuring college basketball prospects, Watson could quickly crunch the numbers and display a comparison of their stats on shooting, assists, and rebounds."
One most assuredly does not need Watson to do this.
Moreover,
"Compare that to drafts of past years, in which the Raptors would use whiteboards with player stats printed on magnets, and call up statisticians each time they wanted new information"
Does not seem it could be remotely true, given...
"Even before Watson came along, the Raptors were tech-savvy. They have access to one of the NBA’s leading analytics teams, and have developed a wide range of tools, including a way to use data from the SportVU camera tracking system to model the best moves a player could make."
I suspect the problem is not entirely with the reporter. The reporter is probably paraphrasing a press release describing a really minimal effort to apply Watson to a something that would grab some publicity. IBM and the Raptors' PR people probably put in more work than was done on the implementation. Which is why it sounds like something you could whip up in a spreadsheet. It probably does "display a comparison of their stats on shooting, assists, and rebounds" on a Web page with the Watson logo on it, and the reporter faithfully reported what he saw.
Watson is more of IBM's tool for creating the impression that IBM is a technology company and not just a systems integration shop than it is a serious deep learning project. Eventually it will become another tragic chapter among many in the decline of technology at IBM.
I predict sometime in the near future, when Apple and Google and Microsoft and others build some real businesses on deep learning systems that there will be a mournful article published about how sad and left behind Watson has become.
I'm don't think that is necessarily a conflict. The reason sport teams have these analytics teams is to help decide how limited resources should be utilized. Those limited resources include money and draft picks, but it also applies to man hours. Why spend development time to build a digital whiteboard to present that data when it would take mere minutes to print it out and put it on a whiteboard? Why build a front end for the database when you can "call up statisticians" (probably just a DBA running an SQL query) to give you the answer. It is a game of trade offs. If the high tech and more complicated solution takes time to implement, the improvement over the simpler solution needs to be large enough to justify the investment.
I've spent more time than any sane person should trying to model fantasy sports for the purpose of making money as a psuedo hobby/second job.
My day job is essentially practical applications of simulation and machine learning so this was a natural way to broaden my modelling capabilities.
I'd love to chat with anyone who has any specific insight as to what the raptors are doing. If you're in Toronto I'll buy lunch!! Contact info in my profile.
Specifically a focus on methods applicable to selecting teams for Fantasy Hockey and Football with applications to weekly/daily fantasy is mostly what I'm concerned with.
I've spent alot of time/money figuring out what doesn't work very well so I can offer 3 years of failed experiments as a trade:)
They are using the "Watson Tradeoff Analytics" product as the underpinning [1]
As others have mentioned, "Watson" is a brandname/pillar at IBM, similar to Infosphere (anything information management), Websphere (anything middleware-y), etc. It's a bunch of simple and complex, in-house-built and bought products, some of which play together well some of which don't, some of which were pretty impressive and some of which aren't.
To play with Watson Tradeoff Analytics, you can check out the documentation or get a free account with Bluemix [2]. They used to have a subset-of-functionality demo for Raptors on Bluemix as well. It seemed nifty but not groud-breaking.
My understanding is that for the real-thing, they also used the Watson Tone/Sentiment analyzers to see if players would be culturally a good fit, i.e. get along with their team-mates, not just whether they're good on paper.
[disclosure: I work for IBM... nowhere NEAR Watson, in the plain-ol'-ERP department, but I've been curious myself to figure out what the hoopla is or isn't all about]
I do some analytical work for a high school football team as well as play a good amount of fantasy football. What would be a good first step to actually making money on fantasy football?
If it's your thing, you could look up Haralabos Voulgaris - he takes on people doing advanced sports stats for betting purposes. He is straight gambling ($1m/day I think he's mentioned) rather than fantasy sports though. From following him for a while, I've had the impression that he has a team of programmers working for him at various points.
I love it, because two things are abundantly clear to even the most casual observer:
1) everyone at IBM has been told to pretend they are this huge, leading "cloud" company
2) 1) is a clear falsehood
And so you see marketing struggle to come up with all these ridiculous "case studies", because it's difficult if you have to invent them out of thin air instead of real customers.
The scary part that is that my company's IT department also talks about "Watson integration" and a lot of execs are completely impressed. I have asked in some meetings what this would exactly do and how it's better than a few SQL statements but got totally brushed off.
I think it's great that there continues to be a stream of "Watson partners with X" or "Watson is used for X" articles, but in actual usage, it feels like Google is winning the ML race. I feel like corporations are using Watson for easy PR wins. Is that just me living in my own development bubble?
My limited understanding with basketball stats is that they are only somewhat useful, as it favours player who have direct impact to the game, those who can score/assist/rebound/etc, and encourages players to game the system.
However it does not reflect how a player defends, how he fits into a particular style/role, how much support his teammates get from him other than assists, etc.
It'll be interesting to see if they use deeper analysis to figure out which player is actually better.
There are actually many advanced statistics available to NBA teams via SportsVu. It can measure who passes to who, how far people travel on a possession, gravity (how close opposing defenders are drawn to the offensive player, how much someone dribbles, and a host of other stats. I don't think the system is in place at many colleges (if any).
The tricky thing with the draft is finding players that have a high ceiling and can perform far in excess of what they were able to do in college. Sabermetrics can help you identify that some of the time but I think attitude, ability to improve specific skills, and innate physical attributes are things a team would have to evaluate in person to uncover undervalued talent.
There are many invented advanced statistics that supposedly fill those intangible gaps. For example, the defensive win shares stat is supposed to measure defensive impact.
As per my other comment, I _believe_ that for the actual application, they did use Watson Tone Analyzer / Sentiment Analyzer / etc, to figure out the "fit" of a player to Raptors culture and with other team-mates.
I've seen a demo where as part of the app, they scrape player's interviews, twitter feeds, etc to get a personality representation.
There are more stats than this, average points participated, win participation, time with ball, all of those are normalized for amount of games played and time on court.
But at the end those stats you've mentioned matter, hoops scored, rebounds caught, penalty shots, and score passes/assists are what "wins" a game.
An important part of a statistical model is to also be simple and cheap enough to implement to gain actual statistics, the chance that there is some magical player that doesn't score high on stats but somehow has a meaningful impact on the game that isn't somehow scored is very very slim and in Basketball specifically probably non-existent since it's only a 5vs5 sport which means that every player handles the ball.
Honest if potentially naive question: why can't you just measure points per minute by the player's team's opponents when the player is on versus off the court?
>My limited understanding with basketball stats is that they are only somewhat useful
One of the major fallacies surrounding sports analytics is dismissing information that isn't all-encompassing. Not picking on you, but "those stats are no good because they don't capture X!" is a common refrain.
> For example, if the Raptors were measuring college basketball prospects, Watson could quickly crunch the numbers and display a comparison of their stats on shooting, assists, and rebounds. Compare that to drafts of past years, in which the Raptors would use whiteboards with player stats printed on magnets, and call up statisticians each time they wanted new information, recalled Lenchner, who visited the Raptors’ headquarters while IBM was developing the software. In the days before Watson, the whole process was much more laborious and time consuming.
I like Watson and it's not their fault for getting publicity...but as for the reporter, c'mon, there's no way you could write that above paragraph without being ignorant of computers pre-Macintosh (or iPod) days. Perhaps the Raptors are old-fashioned but computers have been used for exponentially reducing laborious and time-consuming activities since the dawn of the airlines for solving scheduling problems. And that was much later than the era of computing used for early censuses and cryptoanalysis during the World Wars. But if you've grown up in the "there's an app for that!" age, I guess it's easy to forget how infinite the use cases for computers.
I remember seeing Watson on Jeopardy years ago. He is not quite in the same league as Mr. Butlertron from Clone High, but he's pretty good all the same.
> “[Watson could be used] for the mission to Mars,” he said. After all, that small crew will be crammed together on a spaceship for a few years at least, and getting along will be essential. “You can’t make changes once they’re up there.”
[+] [-] n72|9 years ago|reply
"For example, if the Raptors were measuring college basketball prospects, Watson could quickly crunch the numbers and display a comparison of their stats on shooting, assists, and rebounds."
One most assuredly does not need Watson to do this.
Moreover,
"Compare that to drafts of past years, in which the Raptors would use whiteboards with player stats printed on magnets, and call up statisticians each time they wanted new information"
Does not seem it could be remotely true, given...
"Even before Watson came along, the Raptors were tech-savvy. They have access to one of the NBA’s leading analytics teams, and have developed a wide range of tools, including a way to use data from the SportVU camera tracking system to model the best moves a player could make."
[+] [-] Zigurd|9 years ago|reply
Watson is more of IBM's tool for creating the impression that IBM is a technology company and not just a systems integration shop than it is a serious deep learning project. Eventually it will become another tragic chapter among many in the decline of technology at IBM.
I predict sometime in the near future, when Apple and Google and Microsoft and others build some real businesses on deep learning systems that there will be a mournful article published about how sad and left behind Watson has become.
[+] [-] slg|9 years ago|reply
[+] [-] chollida1|9 years ago|reply
My day job is essentially practical applications of simulation and machine learning so this was a natural way to broaden my modelling capabilities.
I'd love to chat with anyone who has any specific insight as to what the raptors are doing. If you're in Toronto I'll buy lunch!! Contact info in my profile.
Specifically a focus on methods applicable to selecting teams for Fantasy Hockey and Football with applications to weekly/daily fantasy is mostly what I'm concerned with.
I've spent alot of time/money figuring out what doesn't work very well so I can offer 3 years of failed experiments as a trade:)
[+] [-] NikolaNovak|9 years ago|reply
As others have mentioned, "Watson" is a brandname/pillar at IBM, similar to Infosphere (anything information management), Websphere (anything middleware-y), etc. It's a bunch of simple and complex, in-house-built and bought products, some of which play together well some of which don't, some of which were pretty impressive and some of which aren't.
To play with Watson Tradeoff Analytics, you can check out the documentation or get a free account with Bluemix [2]. They used to have a subset-of-functionality demo for Raptors on Bluemix as well. It seemed nifty but not groud-breaking.
My understanding is that for the real-thing, they also used the Watson Tone/Sentiment analyzers to see if players would be culturally a good fit, i.e. get along with their team-mates, not just whether they're good on paper.
[disclosure: I work for IBM... nowhere NEAR Watson, in the plain-ol'-ERP department, but I've been curious myself to figure out what the hoopla is or isn't all about]
[1] http://www.ibm.com/smarterplanet/us/en/ibmwatson/developercl...
[2] https://console.ng.bluemix.net/catalog/services/tradeoff-ana...
[+] [-] ericzawo|9 years ago|reply
http://www.dailymail.co.uk/sport/football/article-2340324/Fo...
[+] [-] coralreef|9 years ago|reply
[+] [-] socrates1998|9 years ago|reply
[+] [-] prawn|9 years ago|reply
[+] [-] raverbashing|9 years ago|reply
Let's stop helping IBM by publishing their press-releases
Watson means nothing. They have some APIs and that's it
Others players have a better product.
I'm not one to help IBM advertise for free
[+] [-] revelation|9 years ago|reply
1) everyone at IBM has been told to pretend they are this huge, leading "cloud" company
2) 1) is a clear falsehood
And so you see marketing struggle to come up with all these ridiculous "case studies", because it's difficult if you have to invent them out of thin air instead of real customers.
[+] [-] oh_sigh|9 years ago|reply
[+] [-] maxxxxx|9 years ago|reply
[+] [-] danvoell|9 years ago|reply
[+] [-] analyst74|9 years ago|reply
However it does not reflect how a player defends, how he fits into a particular style/role, how much support his teammates get from him other than assists, etc.
It'll be interesting to see if they use deeper analysis to figure out which player is actually better.
[+] [-] GVIrish|9 years ago|reply
The tricky thing with the draft is finding players that have a high ceiling and can perform far in excess of what they were able to do in college. Sabermetrics can help you identify that some of the time but I think attitude, ability to improve specific skills, and innate physical attributes are things a team would have to evaluate in person to uncover undervalued talent.
[+] [-] kevinwang|9 years ago|reply
[+] [-] unknown|9 years ago|reply
[deleted]
[+] [-] NikolaNovak|9 years ago|reply
I've seen a demo where as part of the app, they scrape player's interviews, twitter feeds, etc to get a personality representation.
[+] [-] dogma1138|9 years ago|reply
An important part of a statistical model is to also be simple and cheap enough to implement to gain actual statistics, the chance that there is some magical player that doesn't score high on stats but somehow has a meaningful impact on the game that isn't somehow scored is very very slim and in Basketball specifically probably non-existent since it's only a 5vs5 sport which means that every player handles the ball.
[+] [-] endtime|9 years ago|reply
[+] [-] forgetsusername|9 years ago|reply
One of the major fallacies surrounding sports analytics is dismissing information that isn't all-encompassing. Not picking on you, but "those stats are no good because they don't capture X!" is a common refrain.
Some data is better than no data.
[+] [-] danso|9 years ago|reply
I like Watson and it's not their fault for getting publicity...but as for the reporter, c'mon, there's no way you could write that above paragraph without being ignorant of computers pre-Macintosh (or iPod) days. Perhaps the Raptors are old-fashioned but computers have been used for exponentially reducing laborious and time-consuming activities since the dawn of the airlines for solving scheduling problems. And that was much later than the era of computing used for early censuses and cryptoanalysis during the World Wars. But if you've grown up in the "there's an app for that!" age, I guess it's easy to forget how infinite the use cases for computers.
[+] [-] pboutros|9 years ago|reply
[+] [-] 415Kathleem|9 years ago|reply
[+] [-] SolarNet|9 years ago|reply
So IBM does end up making HAL...
[+] [-] notsrg|9 years ago|reply
[+] [-] frugalmail|9 years ago|reply
[deleted]
[+] [-] bpowers|9 years ago|reply