Deconstructing the Home Run Surge: A Physicist’s Approach Alan M. Nathan, University of Illinois a-nathan@illinois.edu @pobguy baseball.physics.illinois.edu From Ben Lindbergh, The Ringer

Possible Reasons for Surge Increased COR of baseball Ball carries better Batters alter swing

1. Increased COR (“bounciness”) Increased CORhigher exit speeds-> more HR I discussed this topic in my 2016 Saberseminar presentation See Lindbergh/MGL Ringer article, May 2017 I won’t further discuss here

2. Better “carry” Physics 101 (vacuum!): Fly ball distance completely determined by EV, LA Real life: drag and lift… Properties of air Properties of ball Ball carries better when travels farther for identical initial conditions i.e., EV, LA, direction, spin, spin axis lift gravity drag

Reasons for different carry Atmospheric conditions changed Temperature, altitude, wind, … Can control for this w/covered stadium Properties of ball changed Drag or lift coefficients CD, CL Size of ball A Want to control the first to study the second

CD Variation from PITCHf/x (controlled for atmospheric effects) Lots of variation of drag coefficient

MMP Experiment (Saberseminar 2015) EV=96 mph LA=280 80-ft spread!

Physics Interlude CD is largest on smooth ball (“laminar flow”) CD is smaller on rough surface (“turbulant flow”) Plumbing: corregated pipes improve flow Golf: dimples reduce drag Baseball: seams reduce drag But…. But if seams too high, CD increases Where is crossover?

Drag and Seam Height EV=96 mph LA=280 MLB NCAA MiLB

Rob Arthur’s Analysis Use PITCHf/x or Trackman pitch-tracking data to extract average CD values Look at correlation with HR/FB

My Approach Use Trackman batted-ball trajectories from TBA atmospheric effects constant Use 2016-b data to fix model for CD and CL “training” data 5 parameters for dependence on spin, speed With fixed model & given initial conditions, calculate trajectory for 2015-E, 2015-L, 2016-a, 2017-E Compare calculated with actual landing point Speed, angles, spin rate, spin axis

Fitting to Training Data 153 batted balls EV>90 mph, LA=200-350 rms=2 ft

The Results: Actual-Calculated ~ 5 ft

Some Comments ~5 ft There is considerable ball-to-ball variation in CD Only makes sense to compare averages Each data set has 100-200 trajectories Data shows ~5 ft increase from 2015-E to 2016, then constant Estimate: 5 ft~15% more HR

Into the weeds…. CD = 0.02  (distance) ~8.5 ft  ~25% more HRs optional CD = 0.02  (distance) ~8.5 ft  ~25% more HRs

Conclusion There is evidence suggesting some (~15%) of increase in HR between 2015 and 2016 is due to reduced drag Reminder: atmospheric effects held constant at TBA Better carry must be due to properties of ball Data are consistent with no change in drag from 2016 to 2017

Afterthought Original motivation for this analysis was to build a new 3D Trajectory Calculator Spreadsheet to calculate trajectories, given EV,LA,SA,spin rate,spin axis Beta version is ready baseball.physics.illinois.edu/TrajectoryCalculator-new-3D.xlsx Feedback welcome

3. Batters alter swing

wOBA vs. EV-LA (actually, wOBAcon) Launch Angle (deg) Exit Speed (mph)

Possible Hitting Strategies To get 1B hit hard and 100-150 To hit xBH hit hard and 250-300 To minimize timing errors swing “level” Question: How does batter adjust swing to optimize outcome?

Issues for swinging the bat (*things I will consider) *Timing Getting bat in right place at right time Swing speed High! *Aim—where on bat impact occurs Along axis of bat (“sweet spot”) *Perpendicular to axis of bat (“offset”) *Swing plane

Ball-Bat Collision Model (2D version) Batter controls:  = swing plane (attack angle) E= offset (“aim”) ~Max EV when =CL Physics Model: (,E)EV,LA

Swing Plane + Offset  EV+LA HR 1B

Max wOBA: ~240 swing plane ~1.1” offset

Ex 1: Kris Davis wOBAcon=0.488 200 ~200 swing plane

Ex 2: Ryan Zimmerman wOBAcon=0.346 70 ~100 swing plane

Timing & Swing Plane Suppose swing mistimed by ~±3 ms, or ~±4” “Level” swing: E does not change 240 swing: E changes by ~ ±0.8” (!) “level” weak grounder uppercut optional popup

Timing & Swing Plane grounder popup ±0.8” optional

Summary LA for max EV related to swing plane In general, for given max EV, wOBA increases as swing plane increases I have not done a complete statistical analysis Work in progress

And finally…. The beat goes on with the COR story Some evidence for reduced drag starting in 2016 New Trajectory Calculator a by-product EV-LA a potentially useful tool My view: The question of why the HR surge is still not fully answered