APS/DFD, Nov The Flight of a Baseball Alan M. Nathan, University of Illinois Introduction PITCHf/x and HITf/x Using baseball to learn about physics Using physics to learn about baseball -how pitchers do what they do -how batters do what they do

APS/DFD, Nov Forces on a Spinning Baseball in Flight mg FDFD FMFM Drag slows ball down Magnus + mg deflects ball from straight line

APS/DFD, Nov Real vs. “Physics 101” Trajectory: Effect of Drag and Magnus

APS/DFD, Nov PITCHf/x and HITf/x Two video 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

APS/DFD, Nov Minimal parametrization of the trajectory –Constant acceleration works very well for pitched ball –Batted balls: ??? Determining Magnus acceleration –“spin movement” important for studying pitching Dealing with noisy data, miscalibrations, etc. Keeping everyone honest –Measurements have uncertainties! So what good is a physicist in all this?

APS/DFD, Nov Baseball Analysis: Using PITCHf/x to discover how pitchers do what they do “Hitting is timing. Pitching is upsetting timing.”

APS/DFD, Nov home plate Ex 1: Mariano Rivera: Why is he so good? ? Three Reasons: Location, Location, Location Home Runs

APS/DFD, Nov Ex 2: “Late Break”: Truth or Myth Mariano Rivera’s Cut Fastball View from above: actual trajectory linear extrapolation

APS/DFD, Nov Josh Kalk, THT, 5/22/08 Ex 2a: What makes an effective slider 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 >90 mph mph <80 mph Ex 3: A Pitcher’s Repertoire LHP Jon Lester, August seam fastball 2-seam fastball curveball slider Catcher’s View 4-seam fastball 2-seam fastball curveball slider

APS/DFD, Nov Ex 4 Jon Lester vs. Brandon Webb Brandon Webb is a “sinkerball” pitcher: Almost no rise on his fastball 15 inches

APS/DFD, Nov Ex 5 The Knuckleball Tim Wakefield is a knuckleball pitcher: Chaotic Movement

APS/DFD, Nov Studies of Batted Balls HITf/x  v 0, ,  Hittracker (Greg Rybarczyk) –Landing point –Flight time Together these constrain the full trajectory

APS/DFD, Nov Hitting a Long Fly Ball R vs. v 0 R vs.  0 USEFUL BENCHMARK mph ~5 ft per mph 25 o -35 o

APS/DFD, Nov What Constitutes a Well-Hit Ball? w/o home runs home runs HR BABIP V 0 >90

APS/DFD, Nov Putting Spin on Batted Balls undercutting/overcutting  backspin/topspin –upward/downward Magnus force In front or behind  sidespin –sideways Magnus force friction normal force v friction

APS/DFD, Nov Some Familiar Effects Due to Spin Balls hit to left/right break toward foul line

APS/DFD, Nov  Extract sidespin vs.  from trajectory CF RF break to right break to leftLF Balls break toward foul pole Break increases with angle Ball hit to CF slices LHH/RHH asymmetry Tilt in bat RF RHH LHH LFRF

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APS/DFD, Nov Some Familiar Effects Due to Spin Balls hit to left/right break toward foul line Topspin makes line drives nose-dive Backspin keeps fly ball in air longer Tricky popups to infield ???

APS/DFD, Nov Paradoxical Popups Watch for fielder’s confusion and for bounce of ball

APS/DFD, Nov HITf/x+hittracker Analysis: The “carry” of a fly ball Motivation: does the ball carry especially well in the new Yankee Stadium? “carry” ≡ (actual distance)/(vacuum distance) for same initial conditions (379,20,5.2)

APS/DFD, Nov HITf/x + hittracker Analysis: 4354 HR from 2009 Denver ClevelandYankee Stadium

APS/DFD, Nov Summary We are on the verge of major breakthrough on our ability to track baseballs and determine the aerodynamic effects The new tools I have discussed are already revolutionizing baseball analysis And the tools are getting better…. So, fun times ahead for me… …shown here doing experimental baseball physics