A Comparative Study of the
Indicators of Success on the PGA
Tour: A Panel Data Analysis
Authors:
Amarendra Sharma, Patrick Reilly
Elmira College
Introduction
• Increase in the use of statistics in sports.
• Main golf statistics of interest• The drive (driving accuracy and driving distance)
• The approach (greens-in-regulation)
• The putt (average putts per round)
• “Slow and steady loses the race?”
• The need for different variables.
• Purpose- To study the predictability of scoring, earnings, and top ten
performances among golfers on the PGA Tour.
Literature Review
•
•
•
•
•
•
•
•
•
•
Peters (2008)
Rinehart (2009)
Watkins, Jr. (2008)
McHale and Forrest (2005)
Fried and Tauer (2011)
Heiny (2008)
Connolly and Rendleman, Jr. (2008)
Coate and Goldbaum (2006)
Ehrenberg and Bognanno (1990)
Shmanske (1992)
Fried and Tauer (2011)
• Estimating “mental toughness”
• Effects of age
Heiny (2008)
• Effects of technology
• Increase in driving distance
• Importance of driving accuracy found to be diminishing
• Putting and greens in regulation still dominate the forecasts.
Data
• Data set includes 20 professional golfers over a 13 year period from
2000-2012.
• Variables
•
•
•
•
•
•
•
Scoring average (SA)
Top 10 finishes per event (T10/E)
Earnings per event (E/E)
Driving distance (DD)
Driving accuracy (DA)
Greens in regulation (GIR)
Putts per round (P/R)
Data (continued)
Variables
Mean
Std. Deviation
Minimum
Maximum
T10/E
0.25
0.19
0
1
E/E
121239.4
116038.4
1700
962500
SA
70.24
0.73
67.79
72
DD
289.47
8.25
269.1
316.1
DA
62.48
5.44
46.43
77.6
GIR
66.36
3.21
52.8
75.2
P/R
29.08
0.51
27.79
20.39
Econometric Model
• Three equations
Additionally,
• Interact driving distance and driving accuracy to form..
Hypotheses/Expected Signs
X Variables
Scoring Average
Earnings/Event
Top 10/Event
DD
-
+
+
DA
-
+
+
GIR
-
+
+
P/R
+
-
-
DD*DA
-
+
+
Scoring Average Results
Variables
Pooled OLS
Fixed Effects
Random Effects
DD
-0.05*
-0.05*
-0.05*
(0.005)
(0.006)
(0.006)
-0.03*
-0.03*
-0.03*
(0.008)
()
()
-0.1*
-0.1*
-0.1*
(0.06)
(0.06)
(0.06)
0.7*
0.65*
0.06*
(2.05)
(2.5)
(2.3)
73.2*
75*
74*
(2.05)
(2.5)
(2.3)
0.61
0.62
DA
GIR
P/R
Intercept
Overall RSquared
Adj. R-Squared
0.614
• * Denotes significance at 1%. Robust standard errors are provided in parentheses.
Earnings per Event Results
Variables
DD
DA
GIR
P/R
Intercept
Pooled OLS
Random Effects
5904*
4393*
48999*
(973)
(1054)
(999)
-26.5
-291.8
-368.5
(1551)
(1529)
(1502)
16907.8*
12074.34*
13499.95*
(2203)
(2094)
(2081.7)
-89432.18*
-54671.4*
-64683.66*
(11395.7)
(11227.9)
(11031)
-107394.9
-343501.5
-288685.8
(397924.5)
(434353.8)
(413617.4)
0.4345
0.4365
Overall R-Squared
Adj. R-Squared
Fixed Effects
0.4305
• * Denotes significance at 1%. Robust standard errors are
provided in parentheses.
Top Ten Finishes per Event Results
Variables
DD
DA
GIR
P/R
Intercept
Pooled OLS
Random Effects
0.01*
0.008*
0.009*
(0.001)
(0.002)
(0.001)
0.005**
0.005**
0.005**
(0.002)
(0.002)
(0.002)
0.03*
0.03*
0.03*
(0.003)
(0.003)
(0.003)
-0.186*
-0.16*
-0.17*
(0.01)
(0.02)
(0.02)
0.19
0.28
0.21
(0.5)
(0.6)
(0.6)
0.596
0.597
Overall R-Squared
Adj. R-Squared
Fixed Effects
0.59
• * Denotes significance at 1%. ** Denotes significance at 5%.
Robust standard errors are provided in parentheses.
Scoring Average with Interaction Term Results
Variables
DDDA
GIR
P/R
Intercept
Pooled OLS
Random Effects
0.00002
-0.00001
-0.000002
(0.00004)
(0.00006)
(0.00004)
-0.15*
-0.13*
-0.14*
(0.012)
(0.02)
(0.02)
0.58*
0.58*
0.58*
(0.08)
(0.11)
(0.09)
63.3*
62.4*
62.6*
(2.17)
(3.32)
(2.42)
0.4638
0.4661
Overall R-Squared
Adj. R-Squared
Fixed Effects
0.4683
• * Denotes significance at 1%. Robust standard errors are
provided in parentheses.
Earnings per Event with Interaction Term
Results
Variables
DDDA
GIR
P/R
Intercept
Pooled OLS
Random Effects
-18.9*
-9.4
-11.3
(7.35)
(5.8)
(8.3)
22962.9*
14956.33*
16292.96*
(4183.8)
(3433.3)
(3287.8)
-72598.4
-48106.82
-52502.3
(14508.15)
(13578.7)
(12592.2)
1049805*
697497.1*
770699*
(340931.1)
(328299.7)
(340557.4)
0.309
0.3103
Overall R-Squared
Adj. R-Squared
Fixed Effects
0.3114
• * Denotes significance at 1%. Robust standard errors are
provided in parentheses.
Top Ten Finishes with Interaction Term Results
Variables
DDDA
GIR
P/R
Intercept
Pooled OLS
Random Effects
-0.00001
0.000002
-0.0000008
(0.000009)
(0.00001)
(0.00001)
0.04*
0.03*
0.03*
(0.004)
(0.006)
(0.005)
-0.16*
-0.15*
-0.15*
(0.02)
(0.03)
(0.02)
2.36*
2.3*
2.3*
(0.5)
(0.77)
(0.56)
0.4645
0.4681
Overall R-Squared
Adj. R-Squared
Fixed Effects
0.4739
• * Denotes significance at 1%. Robust standard errors are
provided in parentheses.
Conclusion
• Putting and approach ability strongly affect scoring, earnings, and top
10 finishes on the PGA Tour.
• Top 10 finishes per event is a better measure of success than earnings
per event.
• Unique perspectives• Shows the importance of top 10 finishes.
• The only paper that exploits the panel nature of the data that allows us to
control for the player specific heterogeneities in a dynamic setting.
References
•
Coate, D. and Goldbaum, D. (2006), Skills, effort, and performance in tournaments: A dynamic model and empirical analysis. (Working Paper Rutgers
University #2004-007).
•
Connolly, R. A. and Rendleman, R. J. Jr. (2008), Skill, luck and hot hands on the PGA tour, Journal of the American Statistical Association, 103(481): 7488. doi:10.1198/
•
Ehrenberg, R. G. and Bognanno, M. L. (1990), The Incentive Effects of Tournaments Revisited: Evidence from the European PGA Tour, Industrial and
Labor Relations Review, 43(3), 74S-88S.
•
Fried, H.O. and Tauer, L.W. (2011), The impact of age on the ability to perform under pressure: golfers on the PGA tour, Journal of Productivity Analysis,
35: 51 – 59.
•
Heiny, E. L. (2008), PGA tour pro: Long but not so straight, Chance, 21(1): 11-21. doi:10.1007/-008-0005-7.
•
McHale, I. and Forrest, D. (2005). The importance of recent scores in a forecasting model for professional golf tournaments, IMA Journal of
Management Mathematics, 16: 131-140. doi:10.1093//.
•
Peters, A. (2008). Determinants of performance on the PGA Tour, Issues in the Political Economy, 17.
•
Rinehart, K. L. (2009). The economics of golf: An investigation of the returns to skill of PGA tour golfers, Major Themes in Economics, 57-70.
•
Shmanske, S. (1992). Human capital formation in professional sports: evidence from the PGA tour, Atlantic Economic Journal, 20(3): 66-78.
•
Watkins, J. R., Jr. (2008). Drive for show, putt for dough: Rates of return to golf skills, events played, and age on the PGA tour, Michigan Journal of
Business. 1: 35-61.
Questions
1. Given the format of winnings in professional golf tournaments, how
could it be beneficial to be a streaky player?
2. Does the data show that it is always better to hit more fairways,
even when it is at the expense of distance?
3. What are the two main variables that consistently impact scoring,
earnings, and top 10 finishes on the PGA Tour?
4. One would expect that earnings per event and top 10 finishes per
event would be able to predict success on the PGA Tour to about
the same degree. Does the data show that one is better than the
other?