An Investigation into Putt Distance, Slope, and Conversion Rate
Dr Paul Hurrion – Quintic Consultancy Ltd.
WSCG 2024 – 11th World Scientific Congress of Golf, Loughborough University, UK
10-12 July 2024
Introduction
It is widely conceived when putting, the closer the ball is to the hole, the higher the conversion rate. The proximity a ball finishes to the hole and strokes gained putting are two common statistics measured within both professional and amateur golf. Strokes Gained Putting [1] quantifies a golfer’s putting performance relative to the field, considering the initial distance of each putt, see Table 1 [2]. Therefore, holing a 10ft putt scores higher than holing a 6ft putt. However, how many times do you hear a commentator say, “They have left themselves a tricky putt here?” When faced with certain putts during a round of golf, why do some putts feel easier than others, even though the putt may be longer?
I can find an 8ft putt that most players of a single figure handicap would be disappointed if they missed and yet I can find another 8ft putt that the chance of even the best players in the world holing is 10% at best – why is this? The proximity to hole is certainly a contributing factor for success rate, however, the following research study was designed to highlight that this is not the only consideration.
Table 1: Make %, 3 Putt % [2] and Strokes Gained data from ShotLink, recorded on the PGA Tour [3]
(Please note highlighted in red font: distances used in this study are between 8 – 13ft)
Methods
The Quintic Overhead Putt Tracker system [4] uses a high-resolution camera (2024 x 1200 pixels) recording at 100 frames per second (fps) positioned 2.70 metres above the playing surface. The overhead camera was placed in the centre of the Zen Green Stage [5]. The dimension of the stage used for the study was 16ft x 8ft with the artificial surface stimping at 10.5 on the ‘Level’ setting.
The following parameters were recorded for each putt: impact ball speed, start direction, point of true roll, apex, separation point, entry speed, entry angle, total distance travelled, time to hole, sliding phase %, rolling phase %, decay phase %.
Figure 1 : Example Putt captured with Quintic Overhead Putt Tracker
The six different putts chosen for the study were replicas of six famous putts in golfing history. The order of the six putts were randomised for each of the 35 subjects. Once the Zen Green stage had come to rest in the new putt gradients, video footage of the successful putt was played to the subject prior to performing that specific putt. The data capture was “embedded” into a competitive game format whereby the participants were asked to compare their performance against historically significant putts. This further encouraged the players to exhibit more representative performance behaviours. In addition, it also provided additional information regarding reading the putt, notably ball speed, slopes and direction the golf ball moved during the putt. The subject was then allowed a further 40 seconds to read and execute the putt. Each of the six putts were attempted by 35 golfers (handicap ranging from 24 to +3).
Table 2: Putt description and slope gradient of the Zen Green Stage for each of the six putts
Figure 2 is a representation of all 35 attempts for Putt 6. The straight-line distance for this putt was 13’ 3” with the Zen Green stage set to the following gradients, 1.5% Downhill and 4.5% Left to Right. The average distance travelled for the putt was 14’ 5” for the three holed putts (an 8.4% increase in the straight-line distance).
Figure 2: A visual representation of all 35 subjects attempt of ‘Putt 6’
John Rahm, 2021 US Open Torrey Pines 17th Green
Results
The first part of the study was to investigate the percentage make rate for the 6 different putts.
35 putts were made for each putt location.
Table 3: Putt description and slope gradient of the Zen Green Stage
The highest make percentage was Putt 1, 8ft with a subtle 1% Downhill and 1% Left to Right break. 13 out of the 35 putts were successful (37%). This is still significantly lower than the PGA Tour average 46.6% conversion rate.
Putt 2 Seve Ballesteros, 1984 Open Championship winning putt on the 18th green of St Andrews had an 11% conversion rate (the PGA Tour average for 11ft is 32.4%). It is interesting to note that this was the only uphill putt of the 6 putts analysed.
The lowest conversion rates (9%) were Putts 3 & 6, both of 13ft feet in length and with considerable break.
However, Putt 5 (13ft in length) Phil Mickelson, 2004 Masters, Augusta National 18th Green had a success rate of 26%, the second highest and over double that of Putts 2, 3, 4 and 6.
Figure 3 : Graphical representation of all 6 putts (35 subjects)
Table 4: Putt number with the average, Standard deviation, range for all 35 attempted putts
The lowest range in start direction was Putt 4, 9.23° (but only an 11% conversion rate). The largest range was Putt 6 28.98° (9% conversion rate)
Putts 2 and 4 were of 11ft in length. Putt 4 has a lowest range in start direction range along with a higher average impact ball speed (both putts had an 11% conversion rate).
Putts 3, 5 and 6 were all of 13ft in length. Putt 6 has the highest range in start direction and the highest average impact ball speed.
Figure 4 : Graphical representation of all successful holed putts for the six different start positions.
Table 5: Average, Standard deviation, range for all successful putts
The above table highlights the data from all successful putts for the six different putt locations
The putts that had the highest success rate also had the greatest range in impact ball speed. Putt 1 (8ft) 37% success rate had an impact ball speed range of 1.29 mph for the 13 successful putts. Putt 5 (13ft) 26% success rate had an impact ball speed range of 1.96 mph for the 9 successful putts. The remaining 4 putts had a success rate lower than 11%. It is interesting to note that ranges for the ball speeds for successful putts was 0.27 mph for Putt 2, 0.79 mph for Putt 3, 0.47 mph for Putt 4 and 0.62 mph for Putt 6.
Figure 5 : Image of a successful holed putt (Putt Location 5)
Straight Line Distance 12’ 10”, Total Distance Travelled until inside hole 13’ 0”,
Area under the curve 1.6 sq ft (Light green section), Apex Distance 3”
Time Taken 2.49 seconds (Start position to fully inside the Hole)
Figure 6 : Image of a successful holed putt (Putt Location 6)
Straight Line Distance 13’ 2”, Total Distance Travelled until inside hole 14’ 4”,
Area under the curve 18.84 sq ft (Light green section), Apex Distance 2’ 6”
Time Taken 3.76 seconds (Start position to fully inside the Hole)
Table 6: Average, Standard deviation, range for all successful putts:
% increase in distance travelled, area, apex distance from straight line and time taken
Table 6 highlights the data from all successful putts for the six different putt locations. The % distance increase, apex, area, and time taken for the successful putts are highlighted. Putt 2 and Putt 4 had the lowest area (sq ft), however both only had an 11% conversion rate. Putt 4 and Putt 5 both had similar time to hole (3.18 and 3.10 seconds respectively) but had very different conversion rates (11% and 26%). Putt 6 had the greatest Apex distance (2’ 6”) but still had the same conversion rate as Putt 3 (Apex distance 6”). The % increase (Straight-line distance vs Actual Distance travelled) is a very small amount for 5 of the 6 putts, despite some of the putts having over 2% slope. Putt 6 had an 8.4% increase in distance.
Discussion
The putt with the highest % conversion rate was Putt 1 (8ft distance). This was the closest putt from all six putts recorded. It is interesting to note that only two putts missed left (high) of the hole, the remaining 57% missed low. Putt 1 was a very subtle 1% Left to Right and 1% downhill. Can the human feel the 1% slopes? 15 putts (43%) of Putt 2 were short – they never even made it past the hole. Again, asking the same question, can a human feel 1% slopes, this time uphill? Putt 6, prior to the experimental testing, would have been deemed the hardest putt of all six. With a 9% conversion rate, it could easily have been lower, given one person was extremely lucky to hole the putt with a ball entry speed of 2.2mph. At this entry speed, the effect cup size is significantly reduced, and if it had missed it was going to be a long way away! This putt took only 2.69 seconds, whereas another holed putt for Putt 6, which had an entry speed of 0.8mph, took 5.25 seconds to reach the hole.
The putts that had the highest success rate also had the greatest range in impact ball speed. Putt 1 (8ft) 37% success rate, had an impact ball speed range of 1.29 mph for the 13 successful putts. Putt 5 (13ft) 26% success rate had an impact ball speed range of 1.96 mph for the 9 successful putts. The remaining 4 putts had a success rate lower than 11%. The lowest ranges for the ball speed for successful putts was 0.27 mph for Putt 2, thus requiring a very consistent touch and control of the putter head speed, acceleration and ball impact location.
Figure 7: The effects of ± 50 percent errors in the initial trajectory (left) compared to the effects
of only ± 10 percent errors in the putt speed (right). [6]
The ability to control ball speed can often be overlooked in coaching. The data reported in this study goes to further corroborate the results stated by Dewhurst (2015) “Speed is more important than target line” [6]. Ball speed is one of the four reasons as to why a putt might miss [7]. The ability to control the speed of the putter head with controlled face aim, along with green reading, are also primary determinants of putting consistency [8].
Putt locations from both clock face positions 2 o’clock and 10 o’clock have the lowest conversion rates, because you have a smaller margin for error with ball speed in these starting positions [9]. (Note: 12 o’clock straight downhill, 6 o’clock directly uphill). Ball speed is not only influenced by clubhead speed at impact, but also length of backswing and clubhead acceleration during impact, time taken and the tempo of back vs through swing along with the % speed drop at impact. As the slope gets steeper the variance in how the ball slows down (Launch angle, vertical bounce, sliding/rolling/decay phases of the putt) creates inconsistency in final distance. The smaller uphill angles are more forgiving of speed variances than cross-hill or downhill angles.
Therefore, from a strategic perspective of playing the game of golf, it should be obvious where the ideal position to putt from is and from a performance perspective it is important to understand that having consistent ball speed control will have a big effect on distance control. Despite this, some natural variance in speed must be expected (golf is an outdoor sport), and when facing a steep fast downhill putt, it is dramatically harder to make than the equivalent uphill putt [10] [11].
Putt 5 had a 26% conversion rate, despite being 2nd longest putt tested (13ft). Putt 1 (8ft) had the highest conversion rate of 37%. This study is a preliminary investigation into the notion that not all putts of the same length are equal. The proximity to hole is certainly a contributing factor for success rate, however, this research highlights that this is not always the case. Severity of slope, ability to read the slope, start direction, time the ball is in motion, area under the curve, ball speed, apex and ball entry speed are all factors that contribute to the ‘difficulty of the putt.’
This is an area for further research to understand all the various parameters that contribute to making a successful putt. Ball speed variation has been identified as a key variable for indicating success, but until we further investigate this topic by increasing the number of subjects and putt locations, we are left with proximity to the hole and strokes gained as the key factor for success in putting. This study provides a rationale to challenge the current metrics and statistical methods and opens up new opportunities to capture data that may identify how the player acquires greater awareness of their adaptative behaviours within a performance environment.
Figure 8: Image of a two successful holed putts (Putt Location 6)
14.92° difference in start direction, but only a 0.36mph difference in impact ball speed
Finally, take for example the John Rahm winning putt on the 18th green at Torrey Pines, 2022 US Open (Putt 6). In Figure 8 above you can clearly see two different ways to achieve the same result, a holed putt. The putts have very different entry speeds, therefore consequently they have very different start directions. There is a lot more tolerance than people might think – attention can be focused on different areas of the task, as opposed to be thinking it is all about start line. Quintic Overhead Putt Tracker enables you to analyse the whole putt and break down the various phases of the putt. During this research study it became obvious to that golfers need to broaden their horizons, enhancing their perception and visualisation of the putting landscape. The golfer needs to be much more mindful about the environment they are facing. How do you correctly access the green contours, slope, grain, wind and ultimately visualise the ball’s path and entry speed into the hole?
The second putt takes almost twice as long to reach the hole, resulting in a ball entry speed of 0.8mph. As a result, the effective hole size is much larger than when a ball reaches the hole at 2.11mph. Quintic provides the numbers to help support the feeling and sensation of the player. The ability to constantly challenge the golfer by moving the Zen Green Stage to a new location, in combination with the Quintic data, adds texture and meaning to the whole learning experience.
The existing learning space is constrained. Practice putting greens are large and generally flat, the access to the golf course where the greatest opportunity to learn is often restricted. The combination of Quintic and the movable putting stage transforms the existing practice and learning space. It explores new opportunities to enhance the coach’s knowledge base and coaching practices, as well as the providing the essential interface between the practice and performance landscape. The ability to provide a greater array of realistic putt trajectories releases new opportunities to enrich practice environments. This enables the player to explore the task, gain meaningful feedback from essential data and broaden their appreciation of the key aspects that improve performance such as coupling perception and action e.g: 10 & 2 o’clock putt results on the clockface. How people practice ball impact speed and pace control is an area of further investigation. You can’t choose your start line until you know what speed the ball is going to enter the hole!
References
- Broadie, M. (2014) Every shot counts. Penguin Publishing Group
- Stagner, L. (2019) https://x.com/LouStagner/status/1200806231352528896
- https://www.pgatour.com/stats/putting
- 2024. “Putting Analysis Software Systems – Quintic Ball Roll.” https://www.quinticballroll.com/Quintic_Ball_Roll_Systems.html
- Zen Green Stage (2024) https://zen.golf/
- Dewhurst, P. (2015). The Science of the Perfect Swing. Oxford: Oxford University Press.
- Cochran, A. J. & Stobbs, J. (2005). Search for the Perfect Swing. Chicago: Triumph Books.
- Karlsen, J., Smith, G, Nilsson, J (2008). The stroke has only a minor influence on direction consistency in golf putting among elite players. Journal of Sports Science, February 1st 2008; 26(3): 243-250
- Hurrion, P. (2016) Speed Changes Everything – an investigation into the effect of launch characteristics on putting performance WORLD SCIENTIFIC CONGRESS OF GOLF, July 18-22 2016 : St Andrews, Scotland, UK.
- Holmes, B. W. (1991). Putting: How a golf ball and hole interact. American Journal of Physics, 59, 129-136.
- Wesson, J. (2008). The Science of Golf. Oxford: Oxford University Press.