GEOVISUALIZING SPATIO-TEMPORAL PATTERNS IN TENNIS

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GEOVISUALIZING
SPATIO-TEMPORAL
PATTERNS IN TENNIS:
An Alternative Approach to
Post-match Analysis
@damiendemaj : Geospatia...

THE PROBLEM
A typical summary of tennis fails to
answer important questions about a
match.

WHERE?
WHEN?
MAPS?

Geospatial and visual analysis.
A real opportunity in tennis.

Within sport but outside of
tennis, some spatio-temporal
research has been completed.

In tennis however,
spatio-temporal analytics is a
relatively new area of study.

THE SERVE
The most important shot in tennis?

Unpredictable differences in
serve location makes your
opponents life a lot more
difficult.
“
”

The results of tennis matches are
often determined by a small
number of important points.
“
”

QUESTION
Which player served with more
spatio-temporal variation at
important points?

WHO?
Roger Federer v Andy Murray
© Getty Images
© Getty Images

WHERE?
Olympic Gold
Medal Match,
London, UK
Sunday Aug 5, 2012

DATA
1706 attributed spatial points
Source: 3D GIS & streaming video

METHOD
Plot x,y serve bounces in GIS
78 pts for Federer
86 pts for Murray

PART 1 of 4
Identify the visual structure of
each serve pattern using K. Means
algorithm tool in ArcGIS.

K. MEANS Algorithm
Looks for natural
clusters in the
data.

K. MEANS Algorithm
Allows user to define similarity of
serves by attribute (direction of
serve) and number of groups.
Fede...

W
B
T
T
B
W
RESULT 1 of 4
Expected clusters in data.
Classify data:Wide – Body – T

PART 2 of 4
Arrange the data into a temporal
sequence to see who served
with more spatial variation.
Temporal sequence =
s...

Q: How do we measure spatial
variation between serve
locations?

Create
EUCLIDEAN LINES
p1 (x1,y1) and p2 (x2,y2), p2 (x2,y2) and p3 (x3,y3), p3 (x3,y3)
and p4 (x4,y4) etc
in each service...

LARGE MEAN
EUCLIDEAN distance
= more spatial serve variation
Small mean
Euclidean distance
= less spatial serve variation

RESULT 2 of 4
Federer served with greater
spatial variation than Murray

PART 3 of 4
Tag the most ‘important’ serves
Most important points in tennis:
30-40 and 40-Ad
Source: Morris 1977, [21]

SELECT
Important points only
Recalculate euclidean distance

RESULT 3 of 4
Murray served with more spatial
variation at the most important
points than Federer.

PART 4 of 4
Overlay successful serves onto
important points to determine
visual relationship.

RESULT 4 of 4
Murray had more success on his
serve at important points than
Federer.

METHOD SUMMARY
1.Visual analytics
2. Introduced K Means Algorithm
3. Euclidean distances
4. Feature overlay

WRAP UP
GIS provided an effective
means to geovisualize
spatio-temporal sports data.
Reveal potential new patterns
within ...

NEXT STEP…
Real-time authoritative data
More data variables
Integrate sports professionals

OTHER TECH
OPPORTUNITIES…

GOOGLE GLASS in sport

REFERENCES[1] M.J. Smith et el,“Geospatial Analysis, a comprehensive guide to principles, techniques and software tools”, ...

QUESTIONS?
@damiendemaj
gamesetmap.com
esri.com

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