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The Value of Performance Statistics in Golf
Statistics are a very important part of modern professional sports. In soccer we have statistics of team possession, territorial control, corners and shots on goal, to name just a few. In horse racing we have a wide variety of statistics for horses, trainers and jockeys. In tennis we have statistics on first serve percentages, aces, service returns, points won at the net and many more. Sport provides fertile ground for statisticians, and golf is no different.
But how useful are these performance statistics? What do they really tell us? Do they give us a genuine idea of a player’s game strengths and weaknesses or are they just meaningless numbers?
Professional golf is riddled with statistics
If you take a look at the official websites of the US or European Tours, you will see a lot of statistics. The US Tour website is especially fond of statistics, some useful and some pretty meaningless. While there is definitely something of value to be gained from looking at the most significant stats, they should be treated with caution. That famous phrase ‘lies, damn lies and statistics’ is always worth keeping in mind.
Performance statistics can be useful, especially when trying to understand the strengths and weaknesses of a golfer’s game. For example, they can provide an idea of whether a golfer drives the ball a long distance or whether he is a good putter. The trick is to make sure you use the correct stats, interpret the stats sensibly, and not jump to conclusions that aren’t there to be made.
So which stats are useful and which are dangerously insignificant? Let’s start with the driving statistics.
The driving distance statistic measures the average number of yards per unit measured. These units are measured at only two holes per round. Although care is taken to select two holes facing opposite directions, to counter the effects of wind, the fact that only two holes are chosen leaves much to chance. Over the course of any given season, a tour professional will be measured between 150 and 250 units. Now, that’s not a large sample, so the reliability of the statistic is somewhat reduced.
Since the sample size for drive statistics is so low, the drive distance statistic should only be used to give an indication of a player’s length off the tee. It should not be used as a precise measure of the length of a driver off the tee. A difference of less than 10 yards is unlikely to be statistically significant. Larger differences can mean something and the statistic is probably more useful in identifying those at the two extremes, ie the very long hitters and the very short hitters.
The other widely used statistic is driving accuracy. This statistic is defined as the percentage of times a player is able to hit the fairway with their tee shot. Unlike the driving distance statistic, the driving accuracy statistic is measured on every par 4 and par 5 hole played. Therefore, the sample size of each player over an entire season is often in excess of 1,000 tee shots, and this provides a much more statistically significant result.
However, there is a big inherent problem with the driving accuracy stat, namely the further a ball travels, the more it deviates from a true straight line. This means that long hitters are likely to always have relatively low driving accuracy stats, simply because they hit the ball farther.
It’s not uncommon to read statements like ‘player X goes astray off the tee as he hits only 56% of the fairways’. Such a statement shows a complete lack of understanding of the basic factors that affect good driving. In fact, the player could be considered wayward if he is a low driver. However, if he’s a very long driver, hitting 56% of the fairways is pretty good performance.
The key to understanding a player’s driving ability is to read the distance and accuracy stats together. In general, you can expect to see an inverse relationship between the two stats. However, if a player performs well on both stats, then it can be assumed that he is a good ball driver. Similarly, if a player ranks low in both categories, he clearly has a problem.
The other consideration when evaluating a player’s performance off the tee is to think about their ability to make decisions. In 2004, Phil Mickelson showed better form, much of which he attributed to his greater inclination to show restraint off the tee. In years past, Phil would simply hit the ball off the tee, not giving enough thought to the benefits of controlled positional play. Whether driving statistics can capture this type of decision-making ability is debatable. In theory, better decisions would translate into better performance statistics. However, it is not clear that this is the case, so a broader understanding of the game and the player is helpful when evaluating capabilities off the tee.
Green in Regulation
The regulation greens statistic, which measures the percentage of times a player hits the green in regulation, is similar to the shot accuracy statistic in terms of sample size. In fact, it’s even more reliable, as it’s based on every hole, every tournament. This means an annual sample size of between 1,000 and 2,000 for most golfers.
The GIR stat is an invaluable measure of how a player’s long game is performing. However, the common mistake with this stat is to assume that it simply measures a player’s iron game. This is an oversimplification and does not take into account the effect conduction has on reaching the good pin. A player who drives the ball well will have a much better chance of reaching the green in regulation time. So, if that same player scores poorly on the greens in regulation, despite having a high driving rating, then he probably isn’t a good iron player. The implication would be that, despite approaching the green from good fairway positions, the player does not hit the green often enough.
Used alone, the GIR statistic tells us how well a player’s overall long game is performing, including both driving and iron play. Used in conjunction with driving statistics, it is possible to extrapolate some game analysis with a player’s irons. If you start from the assumption that a good driver should, all things being equal, achieve good GIR stats, then any deviation from this will actually provide some indication of a player’s iron game.
There are two commonly used putting statistics, namely putts per round and average putt (or putts per green in regulation). The putts per round statistic is the less reliable of the two, as it does not take into account how players get to the green. A player who continually misses the green and chips onto the green from a short distance will generally start to put from closer to the hole. Therefore, he should make fewer putts per round. However, this is as much a reflection of his poor approach play as it is of his skills with the flat stick.
The most reliable indicator of a player’s putting prowess is the putting average, as it removes the effects of chipping close and one putt. As the average putt is recorded on all greens hit in regulation, the sample size is large, generally measured between 750 and 1,500 greens during each season. Statistics should give a fair indication of a player’s putting form.
However, a word of caution should be kept in mind when using putting average. The stat is still affected by the initial proximity of the ball to the hole, which can never be constant between players. The better a player is at attacking the pin with his iron shots, the shorter the distance of his putts. A player who is more aggressive with his approach game is likely to cover a shorter distance with his putts per green in regulation than a player who is cautious with his approach game and faces, on average, longer putts per green in regulation. green reached in regulation. Often it is the best players in the world, who are focused on winning and can afford to be aggressive, who tend to get closer to the pin. Players struggling to hold onto their card often cannot afford to take the same level of risk and therefore play safer, less aggressive approach shots. Therefore, cautious players will face longer putts and will likely score less highly in average putting stats. However, this may have as much to do with your approach game as it does with your putting abilities. In general, it’s hard to gauge exactly how much approach play affects the average putting stat, but there’s no denying that it does have an effect. Although putting average is by far our best guide to a player’s putting ability, it should nonetheless be treated with a degree of caution.
sand saved and scrambled
An important element of any golfer’s game is being able to get out of trouble. In this regard, two stats have been developed to measure a player’s recovery powers, namely the arena save percentage and the scrambling stat.
The sand save stat is the percentage of time a player was able to “walk up and down” once in a greenside sand bunker. Although well intentioned, the problem with this statistic is that it has a very small sample size. Each season, a tour pro is likely to end up in a greenside bunker between 75 and 200 times. The lack of available data makes this statistic unscientific. Furthermore, the stat not only measures a player’s proficiency from the sand, but also his ability to put. Therefore, the advice is to ignore this statistic.
The coding stat is a better guide to a player’s recovery powers. Measures the percentage of time a player misses the green in regulation, but still makes par or better. Although this stat does include an element of ability to put, it is based on a better sample size. Over the course of a season, each player will face this situation an average of 400-600 times. So while not purely a chipping and sand judge, it does provide a better basis for judging a player’s abilities on the green.
The most useful way to use statistics.
If what’s written above doesn’t make you wary of relying too much on performance stats, then the arena is probably the best place for your head. Performance statistics, if used wisely, can be useful in indicating a player’s strengths and weaknesses. However, statistics should never be treated as gospel and simple judgments should never be made based on these figures.
When analyzing a player’s strengths and weaknesses, performance statistics should never be used in isolation. Performance statistics are best used in a broader context, as one tool among a variety of analysis techniques. Other forms of analysis can provide valuable information. These include swing analysis, observation, and tracking quotes from golfers, coaches, and other experts. Used in collaboration, these various elements of analysis become much more insightful. Used alone, they can be tricky. So don’t throw stats away, put them in context and use them wisely.
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