Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Saturday notes: The Frick and curve balls
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Saturday notes: The Frick and curve balls
Uncategorized

Saturday notes: The Frick and curve balls

StephenBaker1
StephenBaker1
4 Min Read
SHARE

Vermeer’s ‘Officer and Laughing Girl‘

Yesterday, after lunch in Midtown, I walked up to the Frick Collection. It’s a spectacular collection of European art–like a highly condensed version of the Louvre. The Web site lets you explore and zoom in on the paintings. Check out, for example, the sleeve on this Rembrandt self portrait.

Henry Clay Frick was a coal (coke) baron in Western Pennsylvania and made his money from the steel industry. He ordered the deadly crackdown at the Carnegie mill at Homestead, in 1892. This piqued my interest in the Goya that he bought (below), which features steelworkers.

More Read

An update of the most read articles on this site
BI on the Go: About Functionality and Level of Satisfaction
Enterprise IT experts on Twitter
CTO Perspectives on Cyber Security Bill
Will Larry Turn Oracle-Sun Into the New AS/400?

Speaking of steel, I’m heading out to Pittsburgh next week for a reporting trip, following a Lunch forum Monday at Penn State.

Goya’s ‘The Forge’

***

In my baseball geeky way, I’m enjoying this statistical study on the effectiveness of fastballs. The conclusion, based on the crunching of millions of pitches and the weighing of hundreds of variables, is that pitchers rely too much on the fastball.

A common example…

Vermeer’s ‘Officer and Laughing Girl‘

Yesterday, after lunch in Midtown, I walked up to the Frick
Collection
. It’s a spectacular collection of European art–like a
highly condensed version of the Louvre. The Web site lets you explore
and zoom in on the paintings. Check out, for example, the sleeve on
this Rembrandt self portrait.

Henry Clay Frick was a coal (coke) baron in Western Pennsylvania and made his money from the steel industry. He ordered the deadly crackdown at the Carnegie mill at Homestead, in 1892. This piqued my interest in the Goya that he bought (below), which features steelworkers.

Speaking of steel, I’m heading out to Pittsburgh next week for a reporting trip, following a Lunch forum Monday at Penn State.

Goya’s ‘The Forge’

***

In my baseball geeky way, I’m enjoying this statistical study
on the effectiveness of fastballs. The conclusion, based on the
crunching of millions of pitches and the weighing of hundreds of
variables, is that pitchers rely too much on the fastball.

A common example. Let’s say a
pitcher is behind in the count, 3-1, to a good hitter. One more ball and the batter
walks. So the batter is expecting a fastball, which is easier for the
pitcher to control. He’s ‘sitting’ on the pitch, in baseball parlance.
And his chance of getting a hit are higher. Cagey pitchers with great
control, like Greg Maddux and Jamie Moyer, built careers from throwing
change-ups and curves in hitter’s counts.

Statistics indicate that others should do the same. The danger of
walking the batter by throwing a bad curve, it appears, is less than
the risk that comes from throwing a fastball he’s ready for. This is
the way pitchers throw to great hitters like Albert Pujols. Now it
seems they should treat every batter like a superstar. (For those eager to dive deeper into baseball math, here’s a post on how outfielders calculate the trajectory of fly balls.)

Link to original post

TAGGED:statistical analysis
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Hidden AI, a risk?
Hidden AI, Real Risk: A Governance Roadmap For Mid-Market Organizations
Artificial Intelligence Exclusive Infographic
unusual trading activity
Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
Analytics Exclusive Infographic
Ai agents
AI Agent Trends Shaping Data-Driven Businesses
Artificial Intelligence Exclusive Infographic
Why Businesses Are Using Data to Rethink Office Operations
Why Businesses Are Using Data to Rethink Office Operations
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

It Takes Courage to Compete on Analytics

6 Min Read

R and the Next Big Thing

7 Min Read

The impact of the drug war in Mexico

3 Min Read

Side-by-side statistical analyses in R, SAS, SPSS

3 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?