The two stats correlated most to Winning% are Runs Scored & ERA.
I think most of us could have guessed that scoring more runs than you’re allowing is a good recipe for success.
2/
Thread: I compiled all D1 team stats listed on the NCAA site from the last full NCAA softball regular season and here’s what I found from 297 teams.
⬇️
1/
The two stats correlated most to Winning% are Runs Scored & ERA.
I think most of us could have guessed that scoring more runs than you’re allowing is a good recipe for success.
2/
I also added the correlation between Stolen Bases per Game & Runs per Game. I was surprised by this, are you?
3/
4/
5/
The elite teams appear to separate themselves a little bit.
6/
They do say, “Defense wins Championships”
7/
8/ https://t.co/mTl9MpMJlU
As a softball coach, how do I train my players on defense? I did a project during the 2019 NCAA D1 Regionals to find out. (A thread)
— Deven Boland (@Bolandev3) September 12, 2019
More from For later read
This response to my tweet is a common objection to targeted advertising.
@KevinCoates correct me if I'm wrong, but basic point seems to be that banning targeted ads will lower platform profits, but will mostly be beneficial for consumers.
Some counterpoints 👇
1) This assumes that consumers prefer contextual ads to targeted ones.
This does not seem self-evident to me
Research also finds that firms choose between ad. targeting vs. obtrusiveness 👇
If true, the right question is not whether consumers prefer contextual ads to targeted ones. But whether they prefer *more* contextual ads vs *fewer* targeted
2) True, many inframarginal platforms might simply shift to contextual ads.
But some might already be almost indifferent between direct & indirect monetization.
Hard to imagine that *none* of them will respond to reduced ad revenue with actual fees.
3) Policy debate seems to be moving from:
"Consumers are insufficiently informed to decide how they share their data."
To
"No one in their right mind would agree to highly targeted ads (e.g., those that mix data from multiple sources)."
IMO the latter statement is incorrect.
@KevinCoates correct me if I'm wrong, but basic point seems to be that banning targeted ads will lower platform profits, but will mostly be beneficial for consumers.
Some counterpoints 👇
That targeted ads allow for "free" products for consumers is a common talking point and we're going to see more of it in the coming months.: https://t.co/Xty3My3f0u (1/14)
— Kevin Coates (@KevinCoates) February 16, 2021
1) This assumes that consumers prefer contextual ads to targeted ones.
This does not seem self-evident to me
Great post by @Sherman1890 got me thinking about the future of targeted ads.
— Dirk Auer (@AuerDirk) February 12, 2021
More and more tools (privacy labels, ad blockers, GDPR) enable consumers to opt-out from targeted ads - can limit the data platforms receive or block ads altogether.
The end of targeted ads? \U0001f9f5\U0001f447 https://t.co/MA6A3BrUWq
Research also finds that firms choose between ad. targeting vs. obtrusiveness 👇
If true, the right question is not whether consumers prefer contextual ads to targeted ones. But whether they prefer *more* contextual ads vs *fewer* targeted
2) True, many inframarginal platforms might simply shift to contextual ads.
But some might already be almost indifferent between direct & indirect monetization.
Hard to imagine that *none* of them will respond to reduced ad revenue with actual fees.
3) Policy debate seems to be moving from:
"Consumers are insufficiently informed to decide how they share their data."
To
"No one in their right mind would agree to highly targeted ads (e.g., those that mix data from multiple sources)."
IMO the latter statement is incorrect.
