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Baseball Aerodynamics

Alan M. Nathan, University of Illinois a-nathan@illinois.edu webusers.npl.uiuc.edu/~a-nathan/pob. Baseball Aerodynamics. Introduction State of our previous knowledge What we are learning from newer technologies… --about baseball aerodynamics --about the game itself Summary. F M. F d.

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Baseball Aerodynamics

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  1. Alan M. Nathan, University of Illinois a-nathan@illinois.edu webusers.npl.uiuc.edu/~a-nathan/pob Baseball Aerodynamics • Introduction • State of our previous knowledge • What we are learning from newer technologies… • --about baseball aerodynamics • --about the game itself • Summary APS/DFD, Nov. 2009

  2. FM Fd mg Forces and Torques on a Spinning Baseball in Flight The goal: determine the coefficients of drag, lift, and moment APS/DFD, Nov. 2009

  3. Real vs. “Physics 101” Trajectory: Effect of Drag and Magnus • Reduced distance on fly ball • Reduction of pitched ball speed by ~10% • Asymmetric trajectory • Optimum fly ball angle~30o APS/DFD, Nov. 2009

  4. FM Fd mg Some Effects of Spin • Backspin makes ball rise • “hop” of fastball • increased distance of fly ball • tricky popups • Topspin makes ball drop • “12-6” curveball • topspin line drives nose-dive • Sidespin makes ball break toward foul pole • Breaking pitches due to spin • curveballs, sliders, cutters, etc. APS/DFD, Nov. 2009

  5. So what do we know about CD, CL, and CM? …prior to 2 yrs ago APS/DFD, Nov. 2009

  6. What do we know about CD? Depends on …. • Reynold’s Number • Re= Dv/ • Re~1x105 @ 45 mph • surface “roughness” • seam orientation? • spin? • Summary: • Existing data show factor of ~2 discrepencies • Character of the “drag crisis” not well determined • CD above ~100 mph not well determined APS/DFD, Nov. 2009

  7. What do we know about CL? Depends on …. • spin parameter S  R/v • Seam orientation? • Reynold’s number @ fixed S? • best evidence in “no”, in region of 50-100 mph In region of importance for baseball (S=0.05-0.30), data are consistent at 20% level APS/DFD, Nov. 2009

  8. What do we know about CM? • Almost nothing experimentally! • For golf…. CM = S  0.012S   19-24 sec @ 100 mph   [M/R2]/v (8% larger for baseball) • Therefore estimate   20-26 sec @ 100 mph APS/DFD, Nov. 2009

  9. New Technologies • The PITCHf/x system • The TrackMan Doppler radar system APS/DFD, Nov. 2009

  10. The PITCHf/x Tracking System • Two video cameras track baseball in 1/60-sec intervals (usually “high home” and “high first”) • Software to identify and track pitch frame-by- frame in real time  full trajectory • Installed in every MLB ballpark Image, courtesy of Sportvision APS/DFD, Nov. 2009

  11. What kind of “stuff” can one learn? • Pitch speed to ~0.5 mph • at release and at home plate • Pitch location to ~0.5 inches • at release and at home plate • “movement” to ~2.0 inches • both magnitude and direction • Initial velocity direction • Pitch classification • more on this later • And all these data are freely available online! APS/DFD, Nov. 2009

  12. Example: Pitch Speed--PITCHf/x vs. the gun • Pitched ball loses about 10% of speed between pitcher and batter • Average speed <v> is ~95% of release speed vf v0 APS/DFD, Nov. 2009

  13. 10% 7.5% loss of velocity total movement 12” 8” Example: Pitching at High Altitude Denver Toronto Toronto Denver PITCHf/x data contain a wealth of information about drag and lift! APS/DFD, Nov. 2009

  14. Example: CD from Pitchf/x Cd vs. v0 <Cd> vs. v0 in 2 mph bins 20k pitches from Anaheim, 2007: Fluctuations consistent with x1 inch! APS/DFD, Nov. 2009

  15. Drag Coefficient:no evidence for “drag crisis” Good approximation: Cd = 0.35±0.05 in range 70-100 mph APS/DFD, Nov. 2009

  16. catcher’s view Example: Pitch Classification: LHP Jon Lester, 8/4/07 • pitches fall into neat clusters: • I: 4-seam FB • II: 2-seam FB • III: slider (note the reduced spin) • IV: CB APS/DFD, Nov. 2009

  17. Compare with knuckleball pitcher Tim Wakefield FB CB APS/DFD, Nov. 2009

  18. What makes an effective slider?—C. C. Sabathia Josh Kalk, THT, 5/22/08 This slider is very effective since it looks like a fastball for over half the trajectory, then seems to drop at the last minute (“late break”). side view APS/DFD, Nov. 2009

  19. New Tools to Study Trajectories of Batted Balls • Hitf/x • Uses Pitchf/x cameras to track initial trajectory • v0,, • Hittracker (www.hittrackeronline.com) • Measure landing point and flight time for home runs • TrackMan Doppler radar • Tracks full batted ball trajectory • Determines initial spin • Possibly spin decay APS/DFD, Nov. 2009

  20. Example: The “carry” of a fly ball • How much does a fly ball “carry”? • Motivation: does the ball carry especially well in the new Yankee Stadium? • “carry” ≡ (actual distance)/(vacuum distance) • for same initial conditions APS/DFD, Nov. 2009

  21. The “carry” of a fly ball819 home runs from April 2009 APS/DFD, Nov. 2009

  22. CD Fly ball trajectory from TrackMan(Safeco Field experiment) New TrackMan pitch data Conclusion: Simple prescription for drag and Magnus fits data beautifully. APS/DFD, Nov. 2009

  23. Summary • We are on the verge of major breakthrough on our ability to track baseballs and determine the aerodynamic effects • In the near future we should be able to address some outstanding issues: • more precise values for Cd • in “crisis” region • for v>100 mph • spin-dependent drag? • dependence of drag & Magnus on seam orientation, surface roughness, … • time constant for spin decay? APS/DFD, Nov. 2009

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