ESPN's Way too Early BPI has WSU #1, UL #2, UK #13
- Thread starter Smashcat
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BPI is pretty meaningless before you have any current season data.
Especially for programs like UK and Duke that have crazy roster turnover every year. Our top recruits can end up like a Skal or a Bolden or play like a Winslow or MKG.
Wichita State has a very high floor though. I'd be shocked if they weren't a top 10 team all season with them bringing everyone back from their team from last year.
And pretty meaningless after you do.
They've factored in ceiling hits per game.
If there are 12 other teams better than this one I will gladly pucker up and kiss arse at the ole courthouse.
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#2 is perfect for UL because that entire program is a pile of shit.
All of these formulas are crap. So many are caught up in them foolishly. It's like 2015, the ones that saw the weaknesses weren't shocked by the loss. Data obsessed fans still can't understand it, so they look for other data to point to as a reason for why. "Oh we stopped platooning". Charts, graphs, See? See?
Games are won on the court, numbers can't provide the story as long as humans play the games, not AI. There's too much to account for that cannot be included in data.
Games are won on the court, numbers can't provide the story as long as humans play the games, not AI. There's too much to account for that cannot be included in data.
Well Pimptino did say this will be the most athletic team he has had since 1996. Nevermind the very next year he had Anderson, Mercer, Padgett, Nazr, and Magloire who all played in the NBA along with Turner, Epps and Edwards.
Yeah, but in his defense he won't be coaching at U of L.
Analytics don't provide the story. They contextualize what you see with your eyes. "All" of the formulas aren't crap, they just don't exist to predict the future. They explain the past.
Besides, you can look at the data and see that Wisconsin was historically efficient on offense, particularly at the spots where we struggled on defense.
I'd actually argue it's the fans who don't understand numbers that were shocked. "But we have all these players I've heard of and that are tall and good, how can we lose to a team with players I don't know?"
The one area where it was inconsistent that season is that the team that played Wisconsin wasn't the same squad that all the numbers represented.
This is my point. And as a former athlete in college, I understand first hand that data cannot be used to determine outcomes at all. Data is used in baseball for example routinely. You play the numbers, and they don't always work out.
It's not necessarily the data I have a problem with, its people who rely so heavily on it because they're ignorant to the game itself and it becomes an issue.
@GonzoCat90 figured I'd reply here.
I don't think anyone with a brain uses data to try and definitively predict outcomes. But it does give you an idea of what to expect.
Now, preseason, stuff like this is stupid because it actually lacks data. They don't have a way to account for new players, progression, etc. I'm just saying it's nuts to act like the eye test beats concrete data gathered over a long period of time. It's like Billy G saying we lost because we weren't tough enough.
WSU will be good but not any better than any other WSU team. returining all those guys is great but none of them are going to push them over the top.
I mean look the game is played by humans on a basketball court. With all sports, there's a element of luck as well as other factors not captured by data.
Even if we were to perfectly assess a team through data and statistics, it doesn't mean results won't vary quite drastically on a game by game basis. Players and teams have good days and bad days just like anyone else.
Having said that, you could learn an awful lot about teams by looking at the data.
I disagree about Wisconsin. If anything, the people that had the stats knew what the people that didn't have the stats didn't know. They understood that Wisconsin was historically good on offense that year. They understood that the gap was far closer than anyone would have liked to admit.
Even if we were to perfectly assess a team through data and statistics, it doesn't mean results won't vary quite drastically on a game by game basis. Players and teams have good days and bad days just like anyone else.
Having said that, you could learn an awful lot about teams by looking at the data.
I disagree about Wisconsin. If anything, the people that had the stats knew what the people that didn't have the stats didn't know. They understood that Wisconsin was historically good on offense that year. They understood that the gap was far closer than anyone would have liked to admit.
As stated it's way too early. We still don't know a lot about this team. I am confident this will be one of Cal's best teams at UK. We have done better when we have a good PG, great shot blocker and we are excellent at the SF spot. We still don't know if we have that shot blocker but this is the best group of SFs in Cal's tenure. If we can block shots at all this is a final four team.
Data can certainly be used to create a predictive model. But there's a reason that model may be run thousands of times. You are getting a range of possible results and the likeliest of outcomes.
Then the actual game is only played once. Who is reffing? Who is nervous? Who stubbed their toe?
How many shots will go in and out on this particular night?
I'm a firm believer that many refs tamp down the variance, i.e., they know what the spread is supposed to be (as predicted, mostly, by the data), and they work to keep the score within striking distance of that spread.
But the idea that data can absolutely predict the future flies in the face of what we think we know about physics. Whole point being there are infinite possibilities, infinite directions you can go in any given moment.
Then the actual game is only played once. Who is reffing? Who is nervous? Who stubbed their toe?
How many shots will go in and out on this particular night?
I'm a firm believer that many refs tamp down the variance, i.e., they know what the spread is supposed to be (as predicted, mostly, by the data), and they work to keep the score within striking distance of that spread.
But the idea that data can absolutely predict the future flies in the face of what we think we know about physics. Whole point being there are infinite possibilities, infinite directions you can go in any given moment.
Kind of what I was thinking. Wonder if ESPN took into consideration a new coach, putting in a new style of play?
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