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A Quick-Start Guide to Putting Green Data Collection

Published on 12/15/2022

Chris Hartwiger, director, USGA Agronomy

You don’t need much equipment to get started with data collection and your program can easily expand over time.

Key Takeaways

Data collection can be overwhelming, but it doesn’t have to be.
Using a simple framework of observation, interpretation and application ensures that the data you collect is useful in your decision-making process.
Start small with one or two key performance indicators (KPIs) such as green speed or clipping volume.
Make sure that the data collection process is performed consistently over time – e.g., make plans for weekends or staff absences. Failure to do so will lead to disappointing results.
To stay on track, ask yourself: “Am I serving the data or is the data serving me?”

The quest for continuous improvement is a fascinating aspect of turfgrass management. There is not a part of the industry that has not been improved over the last 100 years. With that said, not every innovation has stuck. Over time, the helpful ones have been adopted and the others were tossed aside. This brings us to the current era of data, sensors and analytics. Superintendents have the ability to collect mountains of information, but they must discern which information is most valuable to their turf management program.

Whether or not a golf course superintendent should embark down the road of data collection is not the best question to ask. A better one is, “How far down the data collection road should a superintendent go?” Golf course superintendents already collect data every single day – whether it is checking the rainfall total, tracking the amount of fertilizer applied, or taking a quick look at the clippings in a mower basket. In a sea of details, what are the most important data points to focus on? How much data collection is too much?

The USGA Green Section article “A Year of Measuring Putting Green Performance” provided a detailed account of a thorough data collection process that was used at six different golf courses and described the benefits of that work. This article is written to encourage those superintendents who are on the fence about data collection and provide a framework for how data collection can help optimize a putting green management program. A structure of what to do every day will be provided along with resources for taking these concepts further. Finally, a few cautionary notes will be offered to avoid common pitfalls.

Why Collect Information?

There are at least three reasons to collect information that warrant consideration, but the real test is if the benefits of the information are greater than the time commitment required to collect it.

Influence Future Decisions: Information collected over time and displayed graphically makes it easy to identify trends or areas of concern. If green speeds are measured daily, what happens to speed when the greens are double mowed three days in a row? What happens to green speed if a weekly topdressing is made? How long does it take for a fertilizer application to result in a higher clipping volume? When does clipping volume peak after a fertilizer application? Having simple measurements on hand can answer these questions and influence future decisions.

Clarity of Communication: When information is collected systematically and stored in a central location, the superintendent is in control of the written record. This can improve communication to the turf management team or to other officials and managers at the golf course. It has been said that a golf course is only as good as a golfer’s last round. When they offer comments about putting green playing performance, are their perceptions rooted in the actual conditions or how they played that day? With a written record, this is easy to address. Without one, it can be difficult to resolve disagreements. Additionally, a historical record can help the superintendent and decision-makers link course conditions with the golfer experience to deliver conditions that satisfy most golfers most of the time.

Budget Management: Imagine walking into a budget meeting armed with a graph of key performance indicators such as putting green speed and clipping volume and being able to confidently state: “For 2022, our daily green speeds were in our target range 90% of the time as shown on this graph. The amount of turf growth needed for recovery under our levels of play is X ounces of clippings per 1,000 square feet. To achieve these results, here is the list of labor hours, inputs and cultural practices needed.” Providing this level of detail is the fruit of daily data collection.

A great playing surface is something to celebrate but a data collection program can quantify what it took to produce the surface. This is important for budgeting and communication.

Collecting Information – A Three-Step Process

The model outlined below is simple and powerful. Every superintendent already follows this theme in many ways, but it can be improved by collecting information regularly and systematically.

Step 1: Observation - What do I see?

Observations are everywhere. A superintendent may notice scalping on the putting greens, an outbreak of disease, the healing of aeration holes, the quantity of clippings in the basket, the presence or absence of dry spots – the list could go on. What are the one or two items that someone could or should track every day to make sure the putting greens are meeting expectations and are in line with the budget?

These one or two items are called key performance indicators (KPIs). Ideally, these KPIs should be easy to measure, provide insight into performance and help guide future decisions. For example, many golfers use their individual strokes gained putting statistics to guide future practice.

For golf course putting greens, KPIs that are easy to measure and track daily are green speed and clipping volume. More advanced KPIs include organic matter content, firmness and soil moisture.

Step 2: Interpretation - What does it mean?

An observation has been made. Now is the time to interpret the observation by asking what it means. For example, let’s say today’s green speed is 9 feet, 7 inches. Is this high, low or normal? Does it vary significantly from yesterday or last week? If the expected standard at the course is between 9 and 10 feet every day, we have learned that the standard was achieved. We may also note how many days in a row green speed was in the desired range.

If clippings are measured, a superintendent will be able to see how the plants are responding to the fertilization program and whether the response in clipping volume is higher, lower or on par with what is expected. A second level of interpretation involves comparing KPIs week over week or even year over year.

Step 3: Application - How do I use the information at my course?

The last step is where the observations and interpretation pay off. The information collected and interpreted is applied to future decisions and communications. If green speed is in the desired range and has been for some time, what are the cultural practices and inputs that are needed over the upcoming days to stay in the desired range? Because clipping volume is so dependent on nitrogen levels and temperatures, when should the next fertilizer application be scheduled? The same line of thinking is applied through all the cultural practices and inputs related to playing quality. Simply stated, performance data can help you understand whether various inputs should be increased, decreased or stay the same to deliver the desired results.

Take time to measure the amount of sand topdressing applied. This information will be helpful in matching future topdressing rates with growth – which can be measured, too.

Building Your Data Collection Program

The structure of a data collection program is important. It must be organized in a way that can be repeated daily. If not, consistency will suffer, the program will fall apart and the value of the information will be diminished greatly. Below are some steps to get started:

1. Start with the putting greens. They involve 80% of the shots in a typical round and greatly influence the golfer experience.

2. Identify your KPIs. The simplest KPIs for putting greens are speed and clipping volume. More advanced KPIs include organic matter content, surface firmness, surface smoothness and trueness.

3. Identify inputs or cultural practices that influence the KPIs. This is where things can start to get complex and overwhelming. Identify and record the items that influence clippings and green speed. Examples include mowing height, mowing and rolling frequency, grooming/brushing events, nitrogen rate, topdressing rate, growth regulator use and temperature. These factors should be logged every day. This information will prove to be valuable. At some point, recording only green speed will lead you to wonder what is required to produce those results. This is where tracking cultural practices and inputs becomes important.

4. Decide how many putting greens to focus data collection on. USGA agronomists are often asked how many putting greens should be measured. The best way to think about it is in terms of time required versus benefit. There is a huge return on measuring one putting green versus zero. We advise starting with one until the process is established and ingrained in the maintenance routines. Once this occurs, add more putting greens as you see fit.

5. Set up the details of the day-to-day collection program. It is important that the green speed be measured on the same putting green(s) in the same location. This will require identifying a relatively flat area and marking two small spots about 9-12 feet apart that will serve as your measuring points. A black magic marker or spray paint are good options for creating these semipermanent marks.

6. Clippings are best measured by volume and not weight. Sand picked up by mowers has a much greater influence on weight than volume. An easy way to measure clippings is to leave a 5-gallon bucket next to the putting green(s) that are going to be measured. The operator starts mowing the putting green with an empty basket and then dumps the clippings into the bucket. At the maintenance facility, the clippings can be dumped into an even smaller bucket that has graduated measurements. The smaller the final container, the easier it is to detect small differences in clipping volume.

7. Set up the chain of command. Data collection is a 365-days-a-year process in many parts of the country. Identify who is responsible for collecting and entering information. Train workers such as mower operators to contribute to the process. Make plans for weekends or staff absences to make sure there is no disruption in the program.

An Example of Observation, Interpretation and Application

Below is a simple example of the process of observation, interpretation and application. During the observation phase, make as many observations as possible. Move to interpretation and try to figure out what these observations mean. Last but not least, apply this information to your management program and practices. Don’t be discouraged if there is room for improvement in your process or results. Both the superintendent and other decision-makers will still benefit from a deeper understanding of what is required to reach the standard and stay there.

Let’s go through the process with this graph of green speed at a golf course over a 12-month period.

This simple graph of one year’s green speed measurements can offer tremendous insight into season-long performance and areas for improvement.

Observations – What do I see?

Green speed generally remained within the target range.
A big drop in green speed occurred in July following a core aeration event.
The length of time it took for green speed to return to the standard was about three weeks.
Green speed trended down for about five weeks from late April into May.
Green speed stayed more consistently within the target range in the fall.
Green speeds peaked in September around a special event at the course.

Interpretation – What does it mean?

Aeration was disruptive to the desired standard for a significant amount of time.
The downward trend of green speed in April and May was due to higher clipping volume associated with rising temperatures.

Application – How can the information be used?

A different aeration recovery strategy can be implemented and the time it takes to return to the desired standard can be recorded. If clippings are higher than desired through this period, less fertilizer can be applied. If the presence of unhealed holes and too much sand is causing slower speeds, more fertilizer can be added. Year-over-year results can be compared. Over time, the turf team will be able to optimize recovery for their site and it will be based on what they have observed over the years.
An increase in growth can be expected every spring when temperatures begin to rise. Management programs can be implemented to lessen the impact this flush of growth has on green speed and communication efforts during this time can educate golfers about what to expect.

Cautionary Notes

Although data collection is valuable, it is important to avoid several pitfalls. A turf team must avoid the trap of serving the data. The data must serve their turf management program. If data collection becomes a task just for the sake of collecting data, the program will fail in the long run and it will not produce enough actionable information. Data collection should create a resource that can be used in many ways, over and over again. This is why it is advisable to start small and build over time.

"A turf team must avoid the trap of serving the data. The data must serve their turf management program."

A second word of caution is to make sure the procedures for collecting information are consistent and accomplished on time. Measuring clippings should be just as important as mowing the putting greens. If they are scheduled to be mowed, clippings should be collected. This may seem obvious, but it is far more likely for a worker to forget to collect the clippings than for a worker to forget to mow a putting green. Any breakdown in data collection occurs not because of time, but because the collection process is flawed. Data collection must take into account the training of all staff involved and there have to be backup plans when staff are absent from work.

Golfers take performance on the putting greens seriously. A well-constructed data collection program can help superintendents meet expectations as much as possible throughout the year.

Conclusion

Data and measurements are all around us, so it is no surprise that data-driven decision making has arrived in the turf management world. This article provides a simple structure to make sure the insights gained from data collection aid in future decisions, instead of getting lost beneath a sea of numbers and graphs. Investing a small amount of time into collecting a few pieces of information can provide a superintendent with huge returns.

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