Title: Modern Technologies for Tracking the Baseball
1Modern Technologies forTracking the Baseball
Alan Nathan University of Illinois and Complete
Game Consulting
2Heres what Ill talk about
- Brief review of baseball aerodynamics
- The new technologies
- Camera-based systems
- PITCHf/x and HITf/x
- Doppler radar-based systems
- TrackMan
- Using these technologies for analysis
- Lots of examples
3Review of Baseball Aerodynamics Forces on a
Spinning Baseball in Flight
FM
- Drag slows ball down
- Magnus mg deflects ball from straight line
FD
mg
See Michael Richmonds talk
4Example Bonds record home run
5Familiar (and not so familiar) Effects
- Drag
- Fly balls dont travel as far (factor of 2!)
- Pitched balls lose 10
- Magnus
- Movement on pitches (many examples later)
- Batted balls
- Backspin ? longer fly balls tricky popups
- Topspin ? nosedive on line drives tricky
grounders - Sidespin ? balls curve toward foul pole
6PITCHf/x and HITf/x
Marv White, Physics, UIUC, 1969
- Two video cameras _at_60 fps
- high home and high first
- tracks every pitch in every MLB ballpark
- data publicly available
- tracks initial trajectory of batted ball
- data not publicly available
7PITCHf/x and HITf/x
- Used for TV broadcasts, MLB Gameday, analysis,
- See http//www.sportvision.com/baseball.html
8Camera Registration
- T(x,y,z) ? screen coordinates (u,v)
- 7 parameters needed for T
- Camera location (xC,yC,zC)
- Camera orientation (pan, tilt, roll)
- Magnification (focal length of zoom lens)
9Details of Tracking Process
- Each camera image determines LOP
- If cameras were synchronized
- LOP intersection ? (x,y,z)
- Cameras not synchronized
- Need a clever idea
10Sportvisions Clever Idea
- Physics ? trajectory is smooth
- Parametrize smooth trajectory mathematically
- e.g., constant acceleration (9 parameters)
- Adjust parameters to fit pixel data
- We then have full trajectory
11Possible Parametrizations
- Constant acceleration
- x(t) x0 vx0t ½axt2 (etc. for y,z)
- Solve simultaneous linear equations for 9P
- This is scheme used in PITCHf/x
- Constant jerk
- x(t) x0 vx0t ½ax0t2 1/6jxt3
- Solve simultaneous linear equations for 12P
- exact
- Non-linear least-squares fit to get 9P
- x0,y0,z0,vx0,vy0,vz0,Cd,Cl,?
129P vs. Exact Trajectory
vy(t)
x(t)
Many studies like this show that 9P works
extremely well
13All useful parameters derived from 9P
- Release point NOT measured
- x0,z0 are locations at y050 ft
- easily extrapolated to 55 ft
- Derived parameters
- v0, vf speed at y50,HP
- px, pz location at yHP
- pfxx, pfxz movement y40-HP
- spin axis related to direction of movement
- Cd, Cl related to vf/v0 , pfx
- Spin rpm is NOT measured
- but approximate value inferred from pfx values
14PITCHf/x PrecisonA Monte Carlo Simulation
- Start with exact trajectories
- Use cameras to get pixels
- Add random noise (1 pixel rms)
- Get 9P and derived quantities
- Compare with the exact quantities
15exact-inferred
- Central values close to exact ? 9P works well
- 1 pixel rms ? rms on following quantities
- v0 0.23 mph x0, z0 0.4 px, pz 0.7
pfx_x, pfx_z 1.6
16Some Comments on Registration
- In-game monitors
- blue-field vs. actual field
- LOP error
17Registration Studies in Progress
- Could accuracy be improved with additional pole
calibrations? - Can the data themselves be used to recalibrate
the cameras? - An example follows
18Drag Coefficient Anaheim, 2009
Camera registrations changed between days 187,188
19Some Remarks on Hitf/x
- Pixel data fit to constant velocity (6P)
- Not enough of trajectory to do any better
- Impact location inferred from intersection of
pitched and batted ball trajectories - BBS and VLA are systematically low due to drag
and gravity - Not a big effect
- One could correct for it fairly easily
- Balls hitting ground in field of view are
somewhat problematic
20Phased Array Doppler Radar TrackMan
21Measurement principle I
fD Doppler Shift FTX - FRX ? 2FTX(VR/c)
Example FTX 10.5 GHz c0.67 Gmph VR90
mph fD ?2.82 kHz
22Frequency/Velocity vs. Time
Doppler shift
Radial velocity
Time ?
23Measurement principle II
Measurement principle II
Phase Shift
Phase shift 2?DFTXsin(?)/c
24Measurement principle II
Phase Shift
25Spin Measurement principle
Doppler frequency modulated by rotation frequency
? sidebands
26Summary of Technique
- Doppler radar measures radial velocity
- VR ? R(t) distance of ball from radar
- provided initial R is known
- 3-detector array to measure phase
- two angles ?(t), ?(t) ? location on sphere
- R(t), ?(t), ?(t) gives full 3D trajectory
- Spin modulates to give sidebands
- spin frequency ?
27Additional Details
- Need location and orientation of TM device (just
like PFX) - Need R(0)
28TrackMan Capabilities I
- Full pitched ball trajectory
- Everything PITCHf/x gives plus.
- Actual release point ? perceived velocity
- Total spin (including gyro component)
- Many more points on the trajectory
- But given smooth trajectory, additional points
are not necessarily useful
29Comment about Spin
- Tracking (either TM or PFX) only determines
component of spin in the x-z plane - No deflection due to y (gyro) component
- Many pitches have a gyro component
- Especially slider
- Combining TrackMan total spin with the indirect
determination of x-z component gives 3D spin axis - a potentially useful analysis tool
30TrackMan Capabilities II
- Full batted ball trajectory, including
- Batted ball speed, launch spray angles
- Equivalent to HITf/x
- Landing point coordinates at ground level and
hang time - Equivalent to Hittracker
- Initial spin
- and more, if you want it
31TrackMan Data Quality I
- Comparisons with Pitchf/x
- Pitch-by-pitch comparisons from May 2010 in StL
and Bos look excellent - Comparable in precision and accuracy to PFX
- Our Red Sox friends could tell us more, if we ask
them really nicely! ?
32TrackMan Data Quality II
- My Safeco Field experiment, October 2008
- Project fly balls with pitching machine
- Track with TrackMan
- Measure initial velocity and spin with high-speed
video camera - Measure landing point with a very long tape
measure (200-300 ft)
33Landing Point Comparison
TrackMan high by about 2.5 ft. Could be R0 issue
34Spin Comparison
35Summary of Safeco Results
- Initial velocity vector excellent
- Initial spin mostly excellent
- But sometimes off by an integer factor (?)
- Landing point correlates well
- But systematic difference 2.5 ft
36One final point about batted balls
- We need a convenient way to tabulate batted ball
trajectories - Current TM scheme
- Initial velocity vector
- Landing point and hang time, both extrapolated to
field level - Constant jerk (12P) might work
37Some Examples of Analysis
- Pitched ball analysis
- Dan Brooks will do much more
- Batted ball analysis
38Ex 1 Late Break Truth or MythMariano
Riveras Cut Fastball
39Ex 2 Ubaldo Jimenez Pitching at High Altitude
vf/v0
"Every time that I come here to San Diego, it's
always good. Everything moves different. The
breaking ball is really nasty, and my fastball
moves a lot. So I love it here."
Denver
Denver
Denver
Denver
40Ex 2 Ubaldo Jimenez Pitching at High Altitude
vf/v0
Denver
Denver
Denver
Denver
41Ex 3 Effect of batted ball speed and launch
angle on fly balls TrackMan from StL, 2009
R vs. v0
R vs. ?0
USEFUL BENCHMARK 400 ft _at_ 103 mph 5 ft per mph
peaks _at_ 25o-35o
42Ex 4 What Constitutes a Well-Hit Ball? Hitf/x
from April 2009
w/o home runs
Basis for outcome-independent batting metrics
43Combining HITf/x with Hittracker
- HITf/x ? (v0,?,?)
- Hittracker ? (xf,yf,zf,T)
- Together ? full trajectory
- HFXHTT determine unique Cd, ?b, ?s
- Full trajectory numerically computed
- T ? ?b
- horizontal distance and T ? Cd
- sideways deflection ? ?s
44How well does this work?
- Test experimentally (Safeco expt)
It works amazingly well!
45Some examples of HFXHTT Analysis
- Windy Yankee Stadium?
- Quantifying the Coors Field effect
- Home runs and batted ball speed
46HITf/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
-
47HITf/x Hittracker Analysis4354 HR from 2009
Denver
Cleveland
Yankee Stadium
48Average Relative Air Density
49The Coors Effect
26 ft
50Phoenix vs. SF
Phoenix 5.5 ft
SF -5.5 ft
51Home Runs and BBS
- 4 reduction in BBS
- 20 ft reduction in fly ball distance (5)
- 50 reduction in home runs
- NOTE typical of NCAA reduction with new bats
52Now that you (think you) understand everything
Slo-mo video here
53My Final Slide
- Lots of new information from tracking data
- We have only just begun to harvest it
- These new data will keep us all very busy!