keynote: cross industry lessons from moneyball analytics

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DO NOT REDISTRIBUTE WITHOUT PERMISSION OF ARI KAPLAN Ari Kaplan 312-513-0091 [email protected] 12/10/2012 Property of Ari Kaplan. Copyright 2012

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Ari Kaplan keynote presentation at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012 Presentation title: "Cross Industry Lessons from Moneyball Analytics", by Ari Kaplan, "Moneyball" advisor to Major League Baseball teams and President of AriBall Ari Kaplan is a leading figure in sports analytics. Known throughout the Major Leagues for revolutionizing and modernizing player assessment, Ari's use of analytics and technology helps coaches prepare for games, players understand their strengths and weaknesses, General Managers forecast future performance and risk of player contracts and draft picks, and more. In this presentation, Kaplan discusses how professional sports teams and players use analytics and data visualization in the Major Leagues. Through his 23 years of experience in over half of all MLB organizations, he will discuss the changes that took place and where analytics will continue to innovate in the future.

TRANSCRIPT

Page 1: Keynote: Cross Industry Lessons from Moneyball Analytics

DO NOT REDISTRIBUTE WITHOUT PERMISSION OF ARI KAPLAN

Ari Kaplan 312-513-0091

[email protected] 12/10/2012 Property of Ari Kaplan. Copyright 2012

Page 2: Keynote: Cross Industry Lessons from Moneyball Analytics

“What’s more important than the will to win is the will to PREPARE to win” – Coach Wooden

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Page 3: Keynote: Cross Industry Lessons from Moneyball Analytics

Prepare to win!

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Page 4: Keynote: Cross Industry Lessons from Moneyball Analytics

…then give actionable answers

Seek open-ended questions…

Why is a batter struggling?

Why aren’t we selling as much as we thought?

Is an injury affecting a pitcher’s mechanics?

What would happen if we acquired this company?

What should our next steps be?

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Apply analytical models again

and again to get answers Above the Field

Player forecasting Economics of contracts Roster modeling Trade-deadline analysis Drafts

On the Field Game Preparation: Advance Scouting Pro-Scouting Amateur Scouting International Scouting Player Development Injury prediction and management

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Multistructural Data Sources

(externally collected)

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Play-by-play (MLB Advanced Media)

Statistics (MLB, STATS, AriBall, Inside Edge)

Defense (BIS)

Pitch & hit mechanics (SportVision, Trackman)

Contracts & Financials (eBIS, Stadium

operations)

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Multistructural data sources

(internally collected)

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Organizational Video

MiLB Coach Reports

Pro-Scouting Reports

Amateur Scouting Reports

Injury & Medical

International Scouting Reports

Advance Scouting Reports

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Understand and manage risks

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Analytics for past, present, future

Learn these three points: What has happened? What is happening? What will happen?

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Page 10: Keynote: Cross Industry Lessons from Moneyball Analytics

Barry Zito’s Fastball release points come down and over a foot

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Find actionable patterns in the data

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Find events preceding a

business issue

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Track consistency and deception of release points and velocity as the season progresses. See how injuries, trades, or assignments from the Minors affect mechanics.

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Predict what might happen from

time-series information

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Page 13: Keynote: Cross Industry Lessons from Moneyball Analytics

Refocus workers from the mundane

to the strategic What happened? What is happening? What will

happen?

Scoutable™ reports: based on full coverage of every pitch, every game. The reports are presented in the same formats that many scouts and organizations use today.

Habits: threw FB whenever there was a 3-ball count. Never threw

consecutive pickoff moves.

Strengths: changeup had a big fading action. Kept first-pitches

down 48% of the time (25% was avg). Plus control of his FB.

Summary: Threw FB 91-94 (34% of all pitches), cutter 88-91 (12%),

sinker 91-94 (28%), curveball 75-78 (13%), changeup 85-87 (13%)

Last game compared to before: threw sinkers 16% less often and

cutters 14% more often

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Find the “signal from the noise” Example: is a player’s hurt knee affecting their swing?

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Before injury: white

circles are hits, green are

misses

After injury

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Use intelligence to find

opportunities

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• Where did a pitcher generate outs? What pitch types and locations? Below shows FB up and slider low/away.

• Where did he allow hits? FB inner half, BB up in zone outer half. • These reports can be for pitcher/batter matchups, across years, and much more

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The “Human Element”: Quantifying

the subjective

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Which umpires made the most

frequent bad calls?

What was Hunter Wendelstedt’s strike zone?

Umpire Strike Zones

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Use intelligence to better “defend”

yourself

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Competition: put yourself in their shoes

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The future of batter analysis

Contact point

Speed off bat

Elevation angle

Field direction

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Image source: Sportvision

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The future of batter analysis

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Image source: Sportvision

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The future of fielding analysis

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Image source: Sportvision

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The future of fielding analysis

The pivot 6-4-3 Double plays

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Play # Time from SS to 2B* Pivot time**

1 .60 .60

2 .40 .40

3 .27 .60

4 .53 .40

5 .53 .40

6 .53 .53

7 .67 .33

* From SS releasing the ball to 2B getting the ball ** From 2B getting the ball to 2B releasing the ball

Image source: Sportvision

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Create the ULTIMATE game-plan

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Image source: Sportvision

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