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1. 1 What Have We Learned from the PITCHf/x System?A report from the summit
What is PITCHf/x and how does it work?
What are we learning from it?
Outlook for future 1. Maddox pitch sequencing
http://mvn.com/mlb-stats/2008/05/08/mound-chess-a-look-at-greg-madduxs-pitch-sequencing/
2. Anatomy of a Pitch--slider
http://www.hardballtimes.com/main/article/anatomy-of-a-pitch-slider/
3. How fast should a fastball be?
http://www.hardballtimes.com/main/article/how-fast-should-a-fastball-be/
4. Wakefield K-ball analysis
http://www.baseballprospectus.com/article.php?articleid=6374
5. Pitch classification
http://www.hardballtimes.com/main/article/fastball-slider-changeup-curveball-an-analysis/
6. Hanging curve, late break
7. Dan Brooks analysis of batter swing preferences
http://brooksbaseball.blogspot.com/2008/06/selectivity.html
8. Drag coeff...show vf/vi vs. vi (constant slope), cd vs. v (with Hubbard superimposed)
9. What's a screwball (Mike Fast)
http://www.hardballtimes.com/main/article/what-a-screwball/
10. Pitching at Coors (Josh Kalk)
http://www.hardballtimes.com/main/article/what-to-pack-for-denver/
Other things:
How does PITCHf/x work.
Info it provides:
v0,vf,x0,z0,xf,zf,dx,dz
1. Maddox pitch sequencing
http://mvn.com/mlb-stats/2008/05/08/mound-chess-a-look-at-greg-madduxs-pitch-sequencing/
2. Anatomy of a Pitch--slider
http://www.hardballtimes.com/main/article/anatomy-of-a-pitch-slider/
3. How fast should a fastball be?
http://www.hardballtimes.com/main/article/how-fast-should-a-fastball-be/
4. Wakefield K-ball analysis
http://www.baseballprospectus.com/article.php?articleid=6374
5. Pitch classification
http://www.hardballtimes.com/main/article/fastball-slider-changeup-curveball-an-analysis/
6. Hanging curve, late break
7. Dan Brooks analysis of batter swing preferences
http://brooksbaseball.blogspot.com/2008/06/selectivity.html
8. Drag coeff...show vf/vi vs. vi (constant slope), cd vs. v (with Hubbard superimposed)
9. What's a screwball (Mike Fast)
http://www.hardballtimes.com/main/article/what-a-screwball/
10. Pitching at Coors (Josh Kalk)
http://www.hardballtimes.com/main/article/what-to-pack-for-denver/
Other things:
How does PITCHf/x work.
Info it provides:
v0,vf,x0,z0,xf,zf,dx,dz
2. 2 PITCHf/x is a pitch-tracking system installed in every MLB venue—a joint venture of Sportvision & MLBAM
3. 3 How Does PITCHf/x Work? 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
4. 4 What kind of “stuff”? Pitch speed to ~0.5 mph
at release and at home plate (they are different!)
Pitch location to ~0.5 inches
at release and at home plate
“movement” to ~2.0 inches
both magnitude and direction
Initial velocity direction
Type of pitch
more on this later
And all of this can be correlated with what the batter does!
a complete digital record exists!
5. 5 And the good news is…. …all these data are freely available online! For info on how to download, establish data base, etc., see …
mvn.com/mlb-stats/2008/01/14/a-pitchfx-primer/
Mike Fast
http://brooksbaseball.net/pfx/
Dan Brooks
http://blog.stealingfirst.com/2008/03/07/how-to-link-pitchfx-to-retrosheet/
Dan Turkenkopf
6. 6 What can we potentially learn from these data? Things of interest to physicists
Effect of air drag and spin
The mysteries of the knuckleball
Things of interest to players, scouts, fans
What do pitchers thrown and when do they throw it?
What are their most/least effective pitches?
What makes an effective fastball, curveball, slider, …?
speed, break, location, …
How do hitters perform against different pitch types, locations, speeds, etc.?
What is effect of pitch sequencing?
Other questions limited only by one’s imagination What is the purpose of pitch classification?
• Understanding the game as a fan – What is the pitcher doing?
• Profiling and scouting pitchers
– What do they throw and when do they throw it?
– What are their strengths and weaknesses?
• Enabling research
– How do hitters perform against different pitch types?
– What makes an effective fastball or curveball (speed, break, etc.)?
– What effect does the sequence of pitch types have?
– etc.
The PITCHf/x data set has the potential to revolutionize our understanding of baseball, and accurate pitch classification is the key to unlocking much of this information.
What is the purpose of pitch classification?
• Understanding the game as a fan – What is the pitcher doing?
• Profiling and scouting pitchers
– What do they throw and when do they throw it?
– What are their strengths and weaknesses?
• Enabling research
– How do hitters perform against different pitch types?
– What makes an effective fastball or curveball (speed, break, etc.)?
– What effect does the sequence of pitch types have?
– etc.
The PITCHf/x data set has the potential to revolutionize our understanding of baseball, and accurate pitch classification is the key to unlocking much of this information.
7. 7 skipskip
8. 8
9. 9 Example 2: Pitching at High Altitude:Higher <v>, less movement in Denver vs. Toronto
10. 10 Using PITCHf/x to Classify Pitches Most techniques based on …
Speed
Horizontal and vertical movement due to spin (“pfx”)
Same as deviation from straight line, with gravity removed
Examples:
FB w/backspin ? upward movement
CB w/topspin (12-6) ? downward movement
Sidespin ? sideways movement Remove common effect of gravity to enhance differences between pitchesRemove common effect of gravity to enhance differences between pitches
11. 11 I don’t see changeup. I do see two different types of FB.I don’t see changeup. I do see two different types of FB.
12. 12 By comparison, look at Brandon Webb
13. 13 PITCHf/x tackles the knuckleball – John Walsh Classify pitches using vertical and horizontal break plus speed
Compare “normal” pitcher (C.C. Sabathia) with k-baller (Tim Wakefield)
“Randomness” of k-ball break is evident in PITCHf/x data Example analysis: What happens when knuckleball does not “knuckle”?
Split k-balls into 3 groups – small, medium, large break
14. 14
15. 15 Can we map how players behave differently in a particular at-bat depending on what the count is?
Take all of the thousands of pitches thrown to RHH this year and normalize all hitters based on an average strike zone, then ask, “Given a particular pitch location in a particular count, what are you likely to swing at?”
Can we map how players behave differently in a particular at-bat depending on what the count is?
Take all of the thousands of pitches thrown to RHH this year and normalize all hitters based on an average strike zone, then ask, “Given a particular pitch location in a particular count, what are you likely to swing at?”
16. 16 Scouting Players with PITCHf/x: Roy Oswalt 2008 Mike Fast The study covers Roy Oswalt’s first 12 starts in 2008, through May 29. Pitches were classified manually on a game-by-game basis by looking at the pitch speed measured by the PITCHf/x system and the approximate spin axis and spin rate as calculated from the accelerations on the baseball due to the Magnus force.
The pitch trajectories as seen from the batters’ boxes are oblique projections of the average pitch trajectory seen by right-handed and left-handed batters for each of Oswalt’s pitch types. Details of the transformation can be found at http://fastballs.wordpress.com/2008/06/15/view-from-the-batters-box/.
The strike zone location charts show the location of each pitch where it crossed the plane at the front of home plate. The strike zone box includes one radius of a baseball on each side of the plate, and the top and the bottom of the zone are for a batter of typical height.
Run values for the pitches were computed using linear weights batting runs. The run value of each ball-strike count was computed, and the value of each pitch is compared to the average run value at that count. The results of balls in play are attributed completely to the pitcher. The run value context was not adjusted for the ballpark, the game situation (other than the count), or the quality of the hitter and pitcher. The slider has been Oswalt’s best pitch in 2008, and the curveball has been his worst pitch.The study covers Roy Oswalt’s first 12 starts in 2008, through May 29. Pitches were classified manually on a game-by-game basis by looking at the pitch speed measured by the PITCHf/x system and the approximate spin axis and spin rate as calculated from the accelerations on the baseball due to the Magnus force.
The pitch trajectories as seen from the batters’ boxes are oblique projections of the average pitch trajectory seen by right-handed and left-handed batters for each of Oswalt’s pitch types. Details of the transformation can be found at http://fastballs.wordpress.com/2008/06/15/view-from-the-batters-box/.
The strike zone location charts show the location of each pitch where it crossed the plane at the front of home plate. The strike zone box includes one radius of a baseball on each side of the plate, and the top and the bottom of the zone are for a batter of typical height.
Run values for the pitches were computed using linear weights batting runs. The run value of each ball-strike count was computed, and the value of each pitch is compared to the average run value at that count. The results of balls in play are attributed completely to the pitcher. The run value context was not adjusted for the ballpark, the game situation (other than the count), or the quality of the hitter and pitcher. The slider has been Oswalt’s best pitch in 2008, and the curveball has been his worst pitch.
17. 17 skip
fastballs outside don't depend much (if at all) on speed for their effectiveness;
conversely, inside fastballs are more effective the harder they are thrown (this one I already knew);
most of the observed effect appears to come from home runs: outside pitches are rarely hit for homers and when they are, a fast pitch is as likely to be hit out of the park as a slow one;
a pitch thrown hard is more susceptible to the ump's bad call than a soft toss. skip
fastballs outside don't depend much (if at all) on speed for their effectiveness;
conversely, inside fastballs are more effective the harder they are thrown (this one I already knew);
most of the observed effect appears to come from home runs: outside pitches are rarely hit for homers and when they are, a fast pitch is as likely to be hit out of the park as a slow one;
a pitch thrown hard is more susceptible to the ump's bad call than a soft toss.
18. 18 From PITCHf/x to HITf/x:Tracking Batted Balls What can be measured with existing cameras?
Speed of ball off bat
the ultimate metric of good hitting
Horizontal and vertical angle
Together, these highly constrain full trajectory—where does the ball land?
use to evaluate hitting
use to evaluate fielding
19. 19 A computational example: V0=90 mph, ?0=350
measured by PFX cameras
? = 1462-2284 rpm
not measured by PFX cameras
A model for drag and lift
20. 20 Summary PITCHf/x data have the potential to revolutionize the analysis of baseball
Some excellent and creative analyses have already been done
Expect more as time goes on
Lobby hard for HITf/x, which adds another dimension to the revolution