Juiced Baseballs, Corked Bats, and other Myths of Baseball

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Transcript Juiced Baseballs, Corked Bats, and other Myths of Baseball

Baseball and Mathematics:

It’s More Than Batting Averages ---Alan Nathan 1

The Baseball/Physics Connection

1927 Yankees: Greatest baseball team ever assembled MVP’s 1927 Solvay Conference : Greatest physics team ever assembled 2

A good book to read….

Prof. Bob Adair 3

Another very useful reference…

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Topics I Will Cover

• Dynamics of the ball-bat collision – How a bat works – Wood vs. aluminum • The flight of the baseball – Drag, lift, and all that – Fancy techniques for baseball analysis 5

“You can observe a lot by watching” ---Yogi Berra

• forces large, time short – >8000 lbs, <1 ms • ball compresses, stops, expands – like a spring: KE  PE  KE – bat recoils • lots of energy dissipated – distortion of ball – vibrations in bat 6

What Determines B atted B all S peed?

• pitch speed • bat speed • “collision efficiency”: a property of the ball and bat BBS = q v pitch + ( 1+q ) v bat • typical numbers: q = 0.2 1+q = 1.2

example: 85 + 70 gives 101 mph (~400’) • v bat matters much more than v pitch !

– Each mph of bat speed worth ~6 ft – Each mph of pitch speed worth ~1 ft 7

The simple stuff: kinematics BBS = q vpitch + ( 1+q ) vbat q = e-m/M eff eff  0.2

1. m/M eff

= ball mass/effective bat mass bat recoil

2. e = elasticity of collision

0.50

• •

0.25 “ball-bat coefficient of restitution” (BBCOR)

harder stuff: dynamics!

3. For m/M eff <<1 and e

1, q

1

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Dynamics of Ball-Bat Collision: A Toy Model q ball Mass= 1 2 e A 0.7

0.6

0.5

 << 1 m on M a (1 on 2) 0.4

flexible 0.3

0 2 4  6 4  >> 1 m on M a +M b (1 on 6) 8 bat 10 rigid 9

The Ball-Bat Force (from real data) Force (lb) 10000 8000 6000 4000 2000 0 0 160 mph 80 mph 2  (ms) 1.6

1.2

collision time versus impact speed 0.8

0.4

0 20 40 60 80 100 120 140 impact speed (mph) 0.2

0.4

time (ms) 0.6

0.8

Vibrational modes with f<2 kHz are important

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Experimental Studies of Bat Vibrations www.kettering.edu/~drussell/bats.html

f 1 = 179 Hz f 3 = 1181 Hz 1 0.5

R 0 -0.5

-1 -1.5

0 f 2 = 582 Hz f 4 = 1830 Hz 5 10 t (ms) time 15 0 5 FFT(R) 0.15

10 15 20 25 0.1

30 35 582 frequency 1181 20 0.05

179 1830 0 0 500 1000 1500 frequency (Hz) 2000 2400 11 2500

5 20 10 15 y Dynamics of the Bat-Ball Collision AMN, AJP 68, 979-990 (2000) 20 20  2  z 2   EI  2 y  z 2     A   t 2 2 y  F(z, t) 0 -5 y -10 z -15 1. Solve eigenvalue problem for normal modes of free bat (F=0) -20 0  10 15 20 25 30 35 5 modal frequencies and shapes y n (z),f n 2. Couple ball to bat via the ball-bat force F 3. Expand y in normal modes • Only modes with f n < ~2kHz matter 4. Solve coupled equations of motion for ball and bat (Runge-Kutta) 

Vibrations, BBCOR, and the “Sweet Spot” 0.6

0.5

0.4

e 0.3

0.2

0.1

0

4 nodes 3 2 1

Ball-Bat COR 50 40 v f 30 20 E vib 10 vibrational energy 5 10 distance from tip (inches) 15 0 at ~ node 2

+

vibrations minimized COR maximized BBS maximized best “feel” 13

Vibrations and the ball-bat collision outside “sweet spot” 14

Vibrations and Broken Bats pitcher movie 0.000

5.000

10.000

15.000

20.000

catcher 25.000

30.000

35.000

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Independence of End Conditions • strike bat on barrel—look at movement in handle • handle moves only after ~0.6 ms delay • collision nearly over by then v (m/s) 30.00

• nothing on knob end matters • size, shape, hands, grip • boundary conditions • confirmed experimentally 20.00

10.00

0.00

-10.00

Batter could drop bat just before contact and it would have no effect on ball!!!

-20.00

-30.00

0 1 2 t (ms) 3 4 16 5

BBCOR and the Trampoline Effect (hollow bats)

The Ping!

Lowest Hoop (or wineglass) Mode

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The “Trampoline” Effect: A Simple Physical Picture • Two springs mutually compress • Energy shared between “ball spring” and “bat spring” Sharing depends on relative “stiffnesses” of springs • Energy stored in ball mostly dissipated (~80%!) • Energy stored in bat mostly restored • Net effect: less overall energy dissipated ...and therefore higher ball-bat COR …more “bounce”—confirmed by experiment …and higher BBS • Also seen in golf, tennis, … demo 18

Forces on a Spinning Baseball in Flight

v •

Drag slows ball down

F = D 1 2 C D ˆ ω F M F D •

Magnus + mg deflects ball from straight line

F = M 1 2 C L mg

Runge-Kutta techniques used to solve eqns. of motion

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Consequences

• Drag – Fly balls don’t travel as far (factor of ~2!) – Pitched balls lose ~10% • Magnus – Movement on pitches (many examples later) – Batted balls • Backspin  • Topspin  longer fly balls; tricky popups nosedive on line drives; tricky grounders • Sidespin  balls curve toward foul pole 20

New tools to study flight of baseball • PITCHf/x – Video tracking of pitched ball trajectory • HITf/x – Video tracking of initial batted ball trajectory • TrackMan – Doppler radar tracking of full pitched and batted ball trajectories • Hittracker – Careful observation of landing point and flight time of home runs 21

PITCHf/x and HITf/x

• Two video cameras @60 fps – “high home” and “high first” – tracks every pitch in every MLB ballpark • all data publicly available on web!

– tracks initial trajectory of batted ball • Used for analysis, TV broadcasts, MLB Gameday, etc.

Image, courtesy of Sportvision 22

Analyzing Batted Balls

Combining HITf/x with Hittracker – Initial position and velocity vectors, landing point r f =(x f ,y f ,z f ), and flight time (T) – Unknowns: ,  b ,  s – Use non-linear least-squares fitting to fit to r f (T) • Get the full trajectory • Amazingly robust 23

Example 1: Bonds record home run 24

Example 2: The “carry” of a fly ball

(379,20,5.2)

Motivation: does the ball carry especially well in

the new Yankee Stadium? “carry” ≡ (actual distance)/(vacuum distance) for same initial conditions

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HITf/x + hittracker Analysis: 4354 HR from 2009

Cleveland Denver Yankee Stadium

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An aside: Pitching at High Altitude Denver

7.5% 10% loss of velocity

Toronto

total movement 8”

Denver

12”

Toronto PITCHf/x data contain a wealth of information about drag and lift!

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TrackMan Data from StL, 2009

R vs. v 0 R vs.

0 USEFUL BENCHMARK 400 ft @ 103 mph ~5 ft per mph peaks @ 25 o -35 o

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What Constitutes a Well-Hit Ball?

BABIP V 0 >90 w/o home runs Basis for outcome HR independent batting metrics

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Pitched Ball Analysis: Using PITCHf/x to discover how pitchers do what they do

“Hitting is timing. Pitching is upsetting timing.”

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Ex 1: Mariano Rivera: Why is he so good?

?

Home Runs home plate Three Reasons: Location, Location, Location

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Ex 2: “Late Break”: Truth or Myth Mariano Rivera’s Cut Fastball View from above: actual trajectory ------- linear extrapolation - - - 32

Ex 3: A Pitcher’s Repertoire

4-seam fastball slider/cutter 2-seam fastball changeup curveball Catcher’s View

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Ex 4 Jon Lester vs. Brandon Webb

15 inches Brandon Webb is a “sinkerball” pitcher: Almost no rise on his fastball

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Ex 5 The Knuckleball

Tim Wakefield is a knuckleball pitcher: Chaotic Movement

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Now try to figure out this one…

In the video clip (4/29/11, TOR@NYY), look at… • spin axis – In what direction “should” the ball break?

• catcher’s glove – In what direction is the ball actually breaking?

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Stuff that keeps me busy

• Collision experiments & calculations to elucidate trampoline effect • More studies of baseball trajectories • Careful studies of PITCHf/x cameras and sources of systematic error • Experiments on high-speed oblique collisions – To quantify spin on batted ball 37

Final Summary

• Physics of baseball is a fun application of basic (and not-so-basic) physics • Check out my web site if you want to know more – go.illinois.edu/physicsofbaseball – [email protected]

• I am living proof that knowing the physics doesn’t help you play the game better!

@ Red Sox Fantasy Camp, Feb. 1-7, 2009

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