GolfHandicap.ai

Tag: Score Prediction

  • What’s Next? The Age of Agency

    What’s Next? The Age of Agency

    Congratulations to the MGCA on its 50th anniversary! That’s a milestone to celebrate — with reflection and a look ahead. And because Handicomp has evolved alongside technology, if you think the last 50 years have been transformative, you haven’t seen anything yet.

    My memories of the summer of 1976 center around Mark “The Bird” Fidrych. He captivated not just Michigan, but the entire country. At the same time, I was at Handicomp helping my dad process golf handicaps. It was prior to personal computers, yet even then, we were setting the table for modern golf tech.

    At the course level? A phone system, an adding machine, maybe a cigar box. That was it. No systems. No connectivity. From a tech standpoint, courses were essentially deserted
    islands.

    Then came disruption — PCs, the internet, and mobile. Each wave didn’t just improve golf — it rewired it. We computerized operations, connected courses, and linked golfers. Ideas once impossible — like statewide league competition — became reality.

    And yet, through all of it, the industry largely viewed technology the same way: as a tool. Something to support the business and make things easier.

    With AI, that mindset is being shattered.

    Artificial Intelligence isn’t just another upgrade — it’s a dividing line. Two paths are forming: those leaning in and rethinking operations, and those waiting, assuming it’s just another trend. That gap is widening fast, because AI isn’t just better software — it’s technology that acts — with agency.

    So where does that put us in fifty years? That’s too far out to predict. But 10-15 years? The trajectory is already visible. Let me be clear — I believe what’s coming will challenge how owners think about running a golf course.

    Here are a few thoughts to ponder:

    First, the course that runs itself.

    In the near future, AI won’t just assist — it will run operations. Tee sheets will optimize themselves, pricing will shift in real time, F&B will anticipate demand, maintenance will be self-managed, and staff will assist.

    Sound far-fetched? We already have riderless mowers, smart irrigation, AI-driven scheduling, and virtual golf environments that run themselves. This isn’t speculation — it’s acceleration.

    And here’s the uncomfortable question: If your course can run itself… what is your role? Not less important — more important, but different. Human interaction becomes the premium layer: the experience, the relationship, the brand. Everything else? Automated. Employees? I’ll let you speculate on that one.

    Second — Sim golf.

    It’s creating new golfers and already outpaces “real” golf in rounds played, a shift that took just over a decade to complete — and won’t reverse. As Sim becomes more capable and affordable — and as course property values rise — “real” golf has some thinking to do.

    And third, the golfer that isn’t human.

    This one may push you. Think of it as a reverse Sim — the course is real and the golfer is the simulation, in the form of a robot. I believe within 10-15 years there will be an autonomous robot golfer capable of playing 18 holes — and beating the best score on any course. We already have robots that can walk, swing a club, think, and see. It’s just a matter of integration.

    In the future, golfers won’t just compete against others — they’ll compete against their bot-self. Their data — every round, every hole, every tendency — can create a digital twin. It’s something we’re already doing with AI score prediction and AI Subs (in leagues). Paired with robotics, golfers could rent a robot that carries their clubs, suggests shots, and plays against them in any style — including their own.

    That’s not science fiction. In 1997, when Deep Blue beat Garry Kasparov, it felt like a stunt. Today, machines outperform humans in complex tasks every day — and no one blinks.

    That’s how fast “impossible” becomes “expected.”

    So where do you stand?

    For 50 years, technology has been weaving golf together — connecting courses, players, and operations. The next 50 years will be different. Technology won’t just connect the game — it will participate in it. It will make decisions, take actions, and even compete. And that leaves every operator, association, and leader with a choice:

    Lean in — or lose your place in the game.

    Fifty years ago, golf technology was a seedling. Today, it’s a tree. Tomorrow, it’s the forest.

    May 8, 2026 – Published in the MGCA Tee-Off Times, Spring 2026 Edition

    Stu Healey, President

    Handicomp, Inc.

  • The Most Honest Match in Golf

    The Most Honest Match in Golf

    You compete against par, against your handicap, against other golfers, or sometimes just against your last good round. What’s missing is a consistent, fair benchmark that reflects how you’re actually expected to play on a given day on a given course and tee.

    That’s where playing a match against your AI self comes in.

    Inside the Electronic Scorecard, AI score prediction allows us to turn expectation into an opponent — one that shows up every time, plays the same course and tee you do, and reflects your game, not someone else’s.

    What Does It Mean to Play Your AI Self?

    Your AI self isn’t a “best case” version of you. It isn’t your worst round either. It’s a prediction of your expected performance, built from your scoring history, the course, the tee, and how you tend to play.

    Hole by hole.

    When you play against your AI self, you’re answering a much more honest question than Did I beat par? or Did I win my match?

    You’re answering:
    Did I beat expectation?

    That’s a powerful lens for golfers who care about improvement, fairness, and understanding their real game.

    Making AI Match Play Like Real Golf

    AI predicts strokes per hole to the hundredths — numbers like 4.86 or 5.72. That level of precision is critical for accuracy and fairness, but golf still needs whole numbers on a scorecard.

    So AI Match uses normalized AI scoring as part of the core feature.

    The idea is simple:

    • Preserve which holes are harder or easier for you
    • Convert fractional predictions into whole-number hole scores
    • Ensure the total score matches the AI’s predicted round score (rounded)

    The result is a believable, playable scorecard:

    • Match play works
    • Stroke play works
    • Hole difficulty still makes sense
    • Nothing feels random or artificial

    Your AI opponent looks and behaves like a real golfer — because it’s modeled after you.

    Target Score Adjustment: Choosing the Challenge

    Not every round has the same goal.

    Sometimes you want a tough test.
    Sometimes you want confidence.
    Sometimes you want a target you should beat.

    That’s why AI Match includes Target Score Adjustment.

    Instead of locking you into a single expected score, the system lets you choose how often you want to beat your AI self.

    Here’s how to think about it:

    • 25% target → a hard opponent
      You’ll beat this AI score about one quarter of the time.
    • 50% target → a true expectation
      You’ll beat it about half the time.
    • 80% target → a more forgiving opponent
      You’ll beat it most of the time.

    Under the hood, the AI uses your scoring variability (standard deviation) to adjust the prediction realistically — not by guessing, but by modeling what your good, average, and off days actually look like.

    The important part:
    No matter the target, the scorecard remains believable, normalized, and fair.

    Why This Works Better Than Handicaps Alone

    Handicaps are designed to level competition between golfers.

    AI Match is designed to measure competition within a golfer.

    It:

    • adapts to trends,
    • reflects course and tee difficulty,
    • doesn’t lag behind your current form,
    • and isn’t distorted by who you’re playing with.

    You can’t sandbag your AI.
    You can’t get unlucky against it.

    It’s the cleanest comparison golf offers.

    Built Into the Electronic Scorecard

    AI Match lives inside the Electronic Scorecard in the Golf Mobile Network application. There’s no special setup, no extra rules, and no administrative burden.

    It simply becomes another way to play:

    • a personal match,
    • a practice tool,
    • a confidence builder,
    • or a competitive side game.

    Why This Matters

    Golfers will always enjoy competing against each other. But the most honest competition in golf might be the one where excuses disappear.

    Playing against your AI self gives golfers:

    • a fair benchmark,
    • meaningful feedback,
    • and a way to measure progress that isn’t clouded by luck or context.

    It’s not replacing traditional golf.
    It’s clarifying it.

    A Different Kind of Opponent

    Golf has always valued integrity. Playing a match against your AI self extends that value into the data era.

    No guesswork.
    No distortions.
    Just you — versus who the data says should show up today.

    And that’s a match worth playing.

    February 4, 2026

    Stu Healey, President

    Handicomp, Inc.

  • More Than a Novelty – AI Score Predictions

    More Than a Novelty – AI Score Predictions

    Every golfer has asked the same question on the way to the first tee:
    “What am I going to shoot today?”

    For decades, that question lived somewhere between hope, guesswork, and superstition. Today, AI offers something different — an answer grounded in data.

    If AI is good at anything, it’s making predictions. Nearly everything you experience with AI is a response to input shaped by training on large volumes of real-world information. Golf scores are no different. With enough scores, from enough golfers, across enough courses, tees, conditions, and days, AI can learn to predict what you’re likely to shoot today or tomorrow based on how you’ve played before.

    At first glance, score prediction might sound like a novelty. Interesting. Maybe even impressive. But once you look closer, it turns out to be something much more important.

    The Prediction Is Just the Beginning

    A predicted score, by itself, is just a number.

    The real value lies in what that prediction unlocks.

    Once you can reliably estimate how a golfer is expected to score — hole by hole and tee by tee — entirely new possibilities open up. Many of the biggest challenges in golf, especially around fairness, suddenly become solvable.

    Better Handicaps Start with Bias Elimination

    At the heart of GolfHandicap.ai is a simple belief:
    The best handicap isn’t the most complex — it’s the fairest.

    Traditional handicap systems are man-made formulas, designed with good intentions, but they struggle to balance accuracy, precision, and bias elimination at the same time. As most golfers eventually discover, a system can be accurate on average and still be unfair if it consistently favors certain golfers, tees, or playing conditions.

    AI score prediction changes the conversation. Instead of inferring ability indirectly, we can measure expected performance directly — and then test outcomes against par in a meaningful way. This makes it possible to detect and reduce bias across skill levels, tees, and playing environments.

    That’s why this entire site exists. Fairness doesn’t come from elegant math alone. It comes from understanding expectations — and AI makes that possible.

    Playing Against Yourself: AI Match

    One of the more fun applications of score prediction is AI Match, available as a feature of the Electronic Scorecard in the Golf Mobile Network application.

    In this mode, you’re not playing against par or another golfer — you’re playing against your AI self: a prediction of how you normally perform on that course and tee, under similar conditions.

    Did you beat expectations? Fall short? Match them exactly?

    Suddenly, a casual round becomes a personal challenge. It’s golf, gamified — but rooted in reality, not gimmicks.

    Course and Tee Difficulty: Choosing the Right Challenge

    Most golfers want to be challenged — just not embarrassed.

    Some days you want to stretch yourself on a tougher tee, or see how you’d handle a course you’ve never played. Other days you just want to enjoy the round and stay competitive. Traditionally, tee selection has been driven by ego, habit, or guesswork.

    AI score prediction removes that uncertainty. By showing predicted scores by tee, golfers can make informed choices:

    • Want to play to a target score?
    • Curious how moving back a tee will really affect your round?
    • Looking to balance challenge with enjoyment?

    Instead of guessing, you can choose the tee that fits your game — that day.

    This also gives leagues and courses a clearer picture of true tee difficulty, based on how golfers actually score, not just what’s printed on the scorecard.

    Confidence, Range, and Expectations

    Predictions aren’t just about averages — they’re about range.

    Golfers don’t just want to know what they’ll probably shoot. They want to know:

    • What’s my best-case round?
    • How bad could it get if things go sideways?
    • If I’m chasing a target score, what are my odds?

    Using statistical measures like standard deviation, absolute deviation, and average score relative to net par, AI can estimate not just a prediction, but a confidence range — essentially, the likelihood of different outcomes.

    Understanding that range builds confidence and sets realistic expectations. It also provides a far better measure of improvement than a single great (or terrible) round ever could.

    AI Ghost (AI Sub): Solving the No-Show Problem

    As discussed in our most recent post, AI score prediction enables something leagues have struggled with for decades: handling no-shows fairly.

    With an AI Sub, a missing golfer is replaced by a prediction of their own hole-by-hole scores. The golfer who shows still plays the matchup they were scheduled for — not par, and not a random ghost.

    Handicaps remain intact. A/B positions don’t get confused. League rules still apply.

    This simply isn’t possible without AI score prediction — and it’s one of the clearest examples of prediction being far more than a novelty.

    Why This Is Different from “Just Another Formula”

    AI score prediction isn’t trying to sync with a particular handicap formula. It isn’t chasing averages or potential. It’s doing something simpler — and more powerful.

    It’s answering a single question:

    Given everything we know, what is this golfer most likely to shoot next?

    That distinction matters. It’s why AI adapts to trends, course and tee difficulty, and individual golfer behavior in ways static formulas never can.

    And This Is Only the Beginning

    Perhaps the most exciting part of AI score prediction is this:
    we don’t yet know all the ways it will be used.

    Every time we explore the data, new opportunities emerge — new features, new insights, new ways to make the game fairer, more engaging, and more fun. Many are already in development. Many more haven’t been imagined yet.

    That’s the difference between a static formula and a learning system.

    AI score predictions aren’t just another golf stat. They’re a foundation — one that supports fair handicaps, better decisions, smarter leagues, and a more honest understanding of how we actually play the game.

    And we’re just getting started.

    January 24, 2026

    Stu Healey, President

    Handicomp, Inc.

  • AI Ghost (AI Sub)

    AI Ghost (AI Sub)

    After another break focused on product development, it’s time to return to one of the most practical benefits of AI score prediction — solving the long-standing problem of league no-shows.

    For decades, golf leagues have struggled with how to handle a missing golfer who doesn’t show up and can’t secure a substitute. The usual solutions were imperfect at best: drafting a random “ghost” from players who did show, or playing against some version of par. Both approaches introduce confusion, unfairness, and unnecessary bias.

    That’s no longer necessary.

    Introducing the AI Sub

    In the Golf League Network application, we’ve introduced the AI Sub — sometimes called an AI Ghost. Because we can accurately predict a golfer’s hole-by-hole scores, we can replace the missing golfer with an AI-generated representation of that specific golfer.

    In effect, the golfer who shows up still plays against the opponent they were scheduled to face — not a random stand-in or an abstract par value. Handicaps remain intact, A/B positions stay correct, and the integrity of the match is preserved.

    This is a fundamental shift: the matchup stays real, even when one golfer isn’t.

    Configurable by League Rules

    Of course, leagues need flexibility — and the AI Sub is fully configurable.

    For example:

    • If a league doesn’t want the absent golfer to earn points, that’s easily enforced.
    • If the league wants to give the golfer who showed up a slight advantage, the AI Sub’s handicap can be adjusted by a stroke or two.
    • If points, skins, or other side games need special handling, those parameters can be set as well.

    In short, leagues can decide how strict or forgiving they want to be — without sacrificing fairness or clarity.

    A Word on Handicapping and Reactivity

    There is one important concept to understand: reactivity.

    Different handicap systems respond to change at different speeds:

    • A Custom average-based handicap (for example, averaging the last 3 scores) can react very quickly.
    • A system like WHS™, which emphasizes potential, dropping poor rounds from a large number of 9-hole scores, tends to change much more slowly.
    • AI score prediction, on the other hand, isn’t trying to mirror a specific handicap formula at all.

    That’s intentional.

    The AI Sub isn’t designed to “sync” to a handicap system — it’s designed to predict the golfer’s next score as accurately and fairly as possible, based on their scoring history, trends, and context.

    This means:

    • In leagues using very reactive handicaps, AI may appear smoother.
    • In leagues using slow-moving handicaps, AI may appear more responsive.

    That’s not a flaw — it’s the point.

    Why AI Handicaps and AI Subs Belong Together

    If a league wants AI Subs to align perfectly with its handicapping philosophy, the most natural solution is to use the AI handicap formula itself.

    When AI predicts scores and determines handicaps:

    • Reactivity is aligned.
    • Bias is minimized.
    • Net results stay closer to par.
    • Fairness is preserved even when golfers miss a round.

    It’s no surprise that since introducing AI handicapping in the Golf League Network, more and more leagues have adopted it. And we believe the introduction of AI Subs will accelerate that trend even further.

    The Bottom Line

    AI Subs solve a real, persistent league problem — no-shows — in a way that’s fair, configurable, and easy to understand. They eliminate random ghosts, reduce bias, and keep matches intact.

    When paired with AI handicapping, they create something leagues have never truly had before: continuity, fairness, and realism — even when a golfer doesn’t show up.

    January 13, 2026

    Stu Healey, President

    Handicomp, Inc.

  • Trend and Course/Tee Bias

    Trend and Course/Tee Bias

    In my previous post, “Understanding Bias in Handicapping,” I used a league example to compare four handicap formulas and explain why some perform better than others. That analysis showed AI and a Custom average (middle 3 of last 5 scores) as the best options for that particular league.

    In this post, we’ll go deeper — comparing AI with the optimal score average formula, which is the average of the last 13 scores, as discussed in the earlier post “Average of Last X Scores.”

    The Test

    To test fairness and predictive accuracy, our system randomly selected 2,000 golfers who had at least 20 hole-by-hole scores for 18-hole rounds. Using our golfer look-back method, the system generated 8,841 comparisons between AI and the Average-of-13 method.

    ResultCount%
    Average of Last 13 Wins2,87132%
    Ties2,16725%
    AI Wins3,80343%
    MetricAvg of Last 13A.I.
    Average Handicap2018
    Exact Correct Predictions9%9%
    Mean+0.03–0.01
    Absolute Difference3.93.6
    Median00
    Standard Deviation5.204.77

    What the Numbers Tell Us

    These results represent average golfers — the kind of players who benefit most from an accurate and fair handicap system.

    • Exact Correct Predictions: Both formulas predict identical exact matches 9% of the time. This number isn’t the key takeaway — it’s just context. Lower-handicap golfers tend to have higher prediction accuracy overall, and higher-handicap golfers lower, which is expected.
    • Mean: The small positive mean for the average-based method (+0.03) shows a slight upward skew — scores tend to be a little higher than expected because it’s easier to shoot 10 over your handicap than 10 under. By contrast, AI’s near-zero mean (–0.01) shows it compensates for that natural skew — a sign of bias correction in action.
    • Absolute Difference: This is the big one. On average, AI’s predictions are 0.3 strokes closer to actual results than the average-based method. That might sound small, but across 8,841 comparisons, it’s statistically significant — a clear indicator of better predictive precision.
    • Standard Deviation: AI again outperforms with a lower SD (4.77 vs. 5.20), meaning more consistent results round to round and golfer to golfer.

    Why AI Wins

    AI outperforms the best pure average because it accounts for factors averages can’t — things like:

    • Trend bias: Whether a golfer’s scores are improving or declining.
    • Course and tee difficulty: Adjusting for real-world variability between rounds.
    • Golfer-specific behavior: Performance patterns unique to each player.

    Averages assume every round is equal, but golf is never played in a vacuum. AI captures the dynamic reality — it adapts as players improve, decline, or move between courses and conditions.

    That 0.3-stroke edge is enormous when scaled across thousands of rounds, leagues, and golfers. It’s the difference between fairness in theory and fairness in practice.

    Why This Matters

    Scratch golfers rarely need handicaps — their skill levels are already stable and self-correcting. But for the vast majority of golfers who aren’t scratch, a fair handicap is everything.

    The scratch player doesn’t care how many strokes they get (it’s always zero). What matters is how many strokes they’re giving — and whether that number is fair. That fairness depends entirely on eliminating trend bias and course/tee bias — things AI is uniquely built to handle.

    Key Takeaway

    AI performs better than the best average because it understands context.

    • It adapts to trends.
    • It adjusts for course and tee difficulty.
    • It produces more consistent and less biased results.

    In short, AI doesn’t just predict — it learns. And that’s what makes it the most reliable foundation for modern golf handicapping.

    October 7, 2025

    Stu Healey, President

    Handicomp, Inc.

  • Average of Last X Scores

    Average of Last X Scores

    Finding the Optimal Number of Scores for an Average-Based Handicap

    When golfers are first asked their handicap, the common response is to say they average a certain score — for example:

    “I usually shoot 90 for 18 holes, so subtract par 72 and that gives me a handicap of 18.”

    In their mind, that makes perfect sense. Golfers instinctively understand that handicaps should reflect what they typically score, not just what they shoot on their best day.

    But that leads to an important question:

    If handicaps are based on averages…

    how many scores should be included in the average?

    Too few scores and the handicap becomes overly reactive, swinging wildly from round to round.

    Too many scores and the handicap becomes diluted, slow to recognize improvement or decline.

    Somewhere in the middle lies an optimal balance between:

    • accuracy,
    • precision,
    • responsiveness,
    • and fairness.

    So we decided to test it.

    The Test

    Using a large volume of league scores, we generated handicap calculations based on averaging the golfer’s last:

    • 1 score
    • 2 scores
    • 3 scores
    • …
    • all the way to 20 scores

    We then measured:

    • Mean → bias relative to par
    • Standard Deviation → consistency and precision
    • Absolute Difference → closeness to actual outcomes (accuracy)

    The lower the Standard Deviation and Absolute Difference, the better the formula performs.

    The testing was separated into:

    • Men’s 18-hole
    • Men’s 9-hole
    • Women’s 18-hole
    • Women’s 9-hole

    The results were remarkably consistent across all four datasets.

    The Results

    Across all four groups, the same overall pattern emerged:

    • Very small score samples (1–3 rounds) produced highly volatile handicaps.
    • As additional scores were included, variability dropped and predictions tightened.
    • Around the middle range, performance stabilized.
    • Beyond that point, additional scores produced diminishing returns while responsiveness began to decline.

    The strongest overall performance consistently clustered around:

    13 scores

    That consistency across:

    • genders,
    • hole formats,
    • and golfer populations
      is important.

    It strongly suggests this is not coincidence, but a natural balance point between randomness and stability.

    By the time the calculation reached roughly 13 rounds:

    • Mean remained close to neutral,
    • Standard deviation flattened,
    • Absolute difference stabilized,
    • and additional scores added very little predictive benefit.

    In short:

    13 scores appeared to provide the best balance between stability and responsiveness.

    Why 13 Makes Sense

    What makes this especially interesting is that the number 13 appears repeatedly in other predictive industries.

    Not because 13 is magical — but because many systems naturally converge around an optimal balance between:

    • signal,
    • noise,
    • recency,
    • and stability
      when using roughly that amount of historical information.

    Examples include:

    Finance

    Financial trend models frequently rely on:

    • 12–14 period moving averages,
    • 13-week trend windows,
    • and quarterly rolling models
      to smooth volatility while remaining responsive to change.

    Insurance & Actuarial Modeling

    Risk models seek enough historical observations to stabilize prediction without overweighting outdated behavior.

    Sports Analytics

    Player projection systems often use rolling windows in this range because:

    • too little data overreacts,
    • too much data ignores trend.

    Machine Learning & Time-Series Forecasting

    Predictive systems repeatedly discover that:

    • recent behavior matters most,
    • but enough history is needed to separate randomness from true pattern.

    Golf appears to behave similarly.

    Why Not Use More Scores?

    This is where many handicap systems begin to struggle.

    Using too many scores creates what is better described as:

    score dilution.

    As more and more rounds are added into the calculation, each individual score carries less weight. The result is a handicap that becomes increasingly anchored to long-term history instead of current reality.

    Older rounds continue influencing the handicap long after they stop representing the golfer:

    • old injuries,
    • old swing mechanics,
    • previous skill levels,
    • different playing frequency,
    • or even entirely different competitive environments.

    The problem isn’t merely slow reaction.

    The problem is dilution of meaningful change.

    A golfer improves…
    but the handicap remains inflated by older poor rounds.

    Or the golfer declines…
    and the handicap stays artificially low because stronger historical scores continue pulling it down.

    Either way, the handicap stops reflecting who the golfer is now.

    That’s why the optimal number of scores matters:

    • too few creates volatility,
    • too many creates dilution,
    • and somewhere in the middle lies the balance between responsiveness and stability.

    In our testing, that balance consistently landed around:

    13 scores.

    Why This Matters

    Most golfers instinctively think about handicaps as averages — and they’re not wrong.

    But averages only work well when:

    • the playing environment remains reasonably consistent,
    • enough rounds smooth randomness,
    • while not including so many that current ability becomes diluted.

    That’s especially true in contained environments like golf leagues, where:

    • golfers often play the same course,
    • rotate between familiar tees,
    • compete under similar conditions,
    • and maintain consistent frequency of play.

    In those settings, average-based handicapping can work surprisingly well — provided the number of scores used is optimized correctly.

    Our testing suggests that balance point is:

    13 scores.

    Not 3.
    Not 20.
    Not “best 8 of last 20.”

    About 13.

    Final Thought

    Golf handicapping has spent decades trying to estimate future performance from past scores.

    The interesting part is this:

    Even before AI enters the discussion, the data itself quietly points toward balance, trend, and prediction — not simply raw averaging.

    And in our testing, that balance consistently landed on:

    13 scores.

    Not because 13 is special, but because it appears to represent the point where:

    • randomness becomes smoothed,
    • trends still remain visible,
    • and the handicap best reflects who the golfer actually is right now.

    September 5, 2025

    Stu Healey, President

    Handicomp, Inc.

  • OK, I’m beginning to Understand (I think)!

    OK, I’m beginning to Understand (I think)!

    S: In discussing this blog with others, one common point of confusion often arises: understanding the difference between automation and AI. Getting a handle on this distinction is key to fully grasping how AI will impact the landscape of the golf industry. Therefore, I’ll start by having a chatbot detail what sets the two apart, followed by a real-world example to demonstrate their differences.

    S: What is the difference between automation and AI?

    ChatGPT: Automation and Artificial Intelligence (AI) are both important concepts in the field of technology, but they are fundamentally different and serve different purposes. Here’s a simple breakdown:

    1. Automation: Automation is the use of technology to perform tasks without human intervention. This involves following pre-defined and repeatable rules, and making things more efficient. For example, a car assembly line uses automation to install parts, a smart thermostat might adjust your home temperature based on the time of day, or a software script might be written to sort and organize files on your computer.
    2. Artificial Intelligence (AI): AI, on the other hand, refers to the simulation of human intelligence processes by machines, especially computer systems. It involves learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction. AI is designed to make decisions based on data inputs, often making decisions or identifying patterns that aren’t pre-programmed by developers. AI technologies include machine learning, neural networks, and natural language processing.

    So, while both automation and AI can accomplish tasks without human intervention, the primary difference lies in the complexity and adaptability of the tasks they can accomplish. Automation can perform predefined tasks more efficiently than humans, but it doesn’t learn from experience or adapt to new situations. AI, in contrast, can learn from data and improve its performance over time without being explicitly programmed to do so, enabling it to carry out much more complex tasks.

    It’s important to note that AI can drive automation. This is seen in fields like machine learning where systems can automatically learn and improve from experience without being explicitly programmed. This type of AI-driven automation is referred to as intelligent automation.

    S: In my first blog post “Teeing off with A.I.” ChatGPT suggested AI will have an impact on Course Management and Maintenance. Without going into depth (as we’re still in the early stages of this blog), I’m going to ask a chatbot about the future of golf course lawn and weed maintenance.

    S: Is is possible to kill a weed with a laser?

    Bard: Yes, it is possible to laser a weed to kill it. Laser weeding is a new technology that uses high-powered lasers to target and kill weeds. The laser beam is focused on the weed’s leaves, and the heat from the laser causes the leaves to vaporize, killing the weed.

    Laser weeding is a more precise and environmentally friendly way to control weeds than traditional methods, such as herbicides. It is also more efficient, as it can kill weeds much faster than herbicides.

    There are a number of companies that are developing laser weeding technologies. One company, Carbon Robotics, has developed a self-driving robot that uses lasers to kill weeds. The robot can be used to control weeds in a variety of settings, including farms, golf courses, and roadsides.

    Laser weeding is still a relatively new technology, but it is gaining popularity as a more effective and environmentally friendly way to control weeds. It is likely that laser weeding will become more widely used in the future.

    Here are some of the advantages of using lasers to kill weeds:

    • Precise: Lasers can be used to target weeds very precisely, leaving surrounding plants unharmed. This is important in areas where crops or other plants are growing.
    • Effective: Lasers can kill weeds very effectively. The heat from the laser vaporizes the water in the weed’s leaves, killing the plant instantly. This is much more effective than herbicides, which can take several days or even weeks to kill the weed.
    • Environmentally friendly: Lasers do not release any harmful chemicals into the environment. This makes them a more sustainable option for weed control than herbicides.

    However, there are also some disadvantages to using lasers to kill weeds:

    • Cost: Laser weeding systems can be expensive. This may make them out of reach for some homeowners or small businesses.
    • Training: Operating a laser weeding system requires some training. This may not be an option for people who do not have experience with this type of technology.
    • Weather conditions: Laser weeding systems may not be able to operate in certain weather conditions, such as heavy rain or fog.

    Overall, laser weeding is a promising new technology for weed control. It is more precise, effective, and environmentally friendly than traditional methods. However, it is still a relatively new technology, and there are some limitations to its use.

    S: Do you believe the cost of laser weeding will come down?

    Bard: Yes, I believe the cost of laser weeding will come down in the future. As the technology matures and more companies start to develop laser weeding systems, the cost of these systems is likely to decrease. In addition, as more farmers and other businesses start to use laser weeding systems, the demand for these systems is likely to increase, which could also lead to lower prices.

    According to a recent article in Farm Equipment magazine: https://www.farm-equipment.com/blogs/6-opinions-columns/post/20156-laser-weeding-reduces-weed-management-costs, the cost of laser weeding systems is currently around $100,000. However, the article predicts that the cost of these systems could come down to as low as $50,000 within the next few years.

    The article also cites a study by the University of California, Davis, which found that laser weeding can save farmers up to 80% on weed control costs. This means that even if the cost of laser weeding systems does not come down significantly, farmers could still save money by using this technology.

    Overall, I believe that laser weeding is a promising new technology for weed control. The cost of laser weeding systems is likely to come down in the future, and the technology is becoming more widely adopted by farmers and other businesses. This suggests that laser weeding is a viable option for weed control that could save businesses money and reduce their environmental impact.

    S: Is laser weeding a product of AI?

    Bard: Yes, laser weeding is a product of AI. The AI technology used in laser weeding is called computer vision. Computer vision is a field of artificial intelligence that deals with the extraction of meaningful information from digital images or videos. In the case of laser weeding, computer vision is used to identify weeds from crops. This is done by analyzing the images of the plants using algorithms that have been trained on a large dataset of images of weeds and crops.

    Once the weeds have been identified, the laser weeding system can then target and kill them using a high-powered laser. The laser beam is focused on the weed’s leaves, and the heat from the laser causes the leaves to vaporize, killing the weed.

    The use of AI in laser weeding makes it a more precise and efficient way to control weeds than traditional methods. It is also more environmentally friendly, as it does not require the use of herbicides.

    Here are some of the benefits of using AI in laser weeding:

    • Precision: AI-powered laser weeding systems can target weeds very precisely, leaving surrounding plants unharmed. This is important in areas where crops or other plants are growing.
    • Efficiency: AI-powered laser weeding systems can kill weeds much faster than traditional methods. This can save farmers time and money.
    • Environmentally friendly: AI-powered laser weeding systems do not use herbicides. This makes them a more sustainable option for weed control.

    Overall, AI is a key technology that makes laser weeding a viable option for weed control. It is more precise, efficient, and environmentally friendly than traditional methods. As AI technology continues to develop, laser weeding is likely to become even more widely used in the future.

    S: How can AI driven laser weeding benefit a golf course?

    Bard: There are many benefits to using a laser weeding system at a golf course. Here are a few of the most important ones:

    • Precision: Laser weeding systems can target weeds very precisely, leaving surrounding plants unharmed. This is important in areas where the grass is closely cropped, such as on a golf course.
    • Effectiveness: Laser weeding systems are very effective at killing weeds. The heat from the laser vaporizes the water in the weed’s leaves, killing the plant instantly. This is much more effective than herbicides, which can take several days or even weeks to kill the weed.
    • Environmentally friendly: Laser weeding systems do not release any harmful chemicals into the environment. This makes them a more sustainable option for weed control than herbicides.
    • Safety: Laser weeding systems are safe to use around people and animals. The laser beam is focused on the weed’s leaves, and the heat from the laser does not travel far enough to harm anything else.
    • Cost-effectiveness: The cost of laser weeding systems has been decreasing in recent years. As the technology becomes more widespread, the cost is likely to continue to decrease. This makes laser weeding a more affordable option for golf courses.

    Overall, laser weeding systems offer a number of advantages over traditional methods of weed control. They are more precise, effective, environmentally friendly, safe, and cost-effective. As the technology continues to develop, laser weeding is likely to become even more widely used in golf courses and other settings.

    Here are some additional benefits of using a laser weeding system at a golf course:

    • Improved turf quality: Laser weeding can help to improve the quality of the turf on a golf course by removing weeds that can compete with the grass for water, nutrients, and sunlight. This can lead to a more lush and verdant playing surface.
    • Reduced maintenance costs: Laser weeding can help to reduce the need for manual weed removal, which can save golf courses time and money.
    • Increased customer satisfaction: Golfers appreciate playing on courses that are free of weeds, and laser weeding can help to create a more aesthetically pleasing and enjoyable playing experience.

    S: It sounds like an AI powered laser weeding system married with an automated lawnmowing system will dramatically change the job of a greenskeeper at a golf course.

    Bard: Yes, AI driven laser weeding and automated lawn mowers are likely to dramatically change the job of greenskeepers at a golf course. In the past, greenskeepers were responsible for manually weeding and mowing the golf course. This was a labor-intensive and time-consuming task.

    However, AI driven laser weeding and self-driving lawn mowers can automate these tasks. This means that greenskeepers will no longer need to spend as much time weeding and mowing the golf course. They will be able to focus on other tasks, such as repairing greens and bunkers, or managing irrigation systems.

    In addition, AI driven laser weeding and self-driving lawn mowers can be more precise and efficient than manual methods. This means that they can produce a better quality playing surface, and they can do so with less environmental impact.

    Overall, AI driven laser weeding and self-driving lawn mowers are likely to make the job of greenskeepers more efficient, less labor-intensive, and more environmentally friendly. This could lead to job losses in the short term, but it could also create new opportunities for greenskeepers in the long term.

    Here are some of the ways in which the job of greenskeepers may change in the future:

    • Greenkeepers will need to be more skilled in operating and maintaining AI-powered equipment. This will require them to have a strong understanding of computer science and engineering principles.
    • Greenkeepers will need to be more familiar with data analysis and interpretation. This will allow them to use data from AI-powered equipment to make better decisions about how to manage the golf course.
    • Greenkeepers will need to be more creative in their problem-solving skills. This will be necessary as they adapt to the changing landscape of golf course management.

    Overall, the job of greenskeepers is likely to become more technologically advanced in the future. This will require them to have a different set of skills and knowledge than they do today. However, it will also create new opportunities for them to use their skills and knowledge to make a positive impact on the environment and the game of golf.

    S: What is your best guess as to how far out we are from having a majority of golf courses adopt AI driven laser weeding systems?

    Bard:  It is difficult to say exactly how far away in time we are from having most golf courses implement AI driven laser weeding. However, I believe that it is likely to happen within the next 10-15 years.

    There are a number of factors that will influence the pace of adoption of this technology. One factor is the cost of the technology. As the cost of AI-powered equipment decreases, it will become more affordable for golf courses to implement.

    Another factor is the availability of the technology. As more companies develop and market AI-powered equipment for golf courses, it will become more widely available.

    Finally, the demand for this technology will also influence the pace of adoption. As golfers become more aware of the benefits of AI-powered equipment, they will be more likely to demand that their favorite golf courses adopt it.

    Overall, I believe that AI driven laser weeding is likely to become widespread in the golf industry within the next 10-15 years. The technology has the potential to make golf courses more efficient, less labor-intensive, and more environmentally friendly. As the cost of AI laser weeding technology decreases and the demand increases, I believe that we will see more and more golf courses adopt it.

    S: For all the Marvel fans out there, think of it like this: Imagine the movie Captain America and the Winter Soldier. The mower/laser-weeder would be like a Helicarrier. Instead of targeting certain people and sparing others, as in the movie, the AI in our case would be targeting and eliminating weeds while sparing crops. 🤔

    June 7, 2023

    Stu Healey, President

    Handicomp, Inc.

  • Lessons for the Jetson’s!

    Lessons for the Jetson’s!

    S: The potential impact of AI on an industry raises important questions about how it will affect individuals who rely on that industry for employment. Building upon AI’s previous answers, it becomes evident that PGA Professionals, particularly those who specialize in providing golf lessons, should pay attention to the advancements. However, it’s not just the current professionals who should be concerned; the younger generation considering teaching as a career may also wonder if there will be opportunities for them in the future.

    As AI continues to evolve and offer virtual coaching and training programs, it could potentially alter the landscape of golf instruction. Automated systems equipped with computer vision and machine learning capabilities can analyze a player’s swing and provide personalized feedback, potentially reducing the demand for traditional in-person instruction. This shift may raise concerns among PGA Professionals who rely heavily on teaching as their primary source of income.

    For aspiring young individuals contemplating teaching as a career, the question of whether there will be room for them in the future is valid. They might wonder if AI will replace the need for human instructors altogether, making their chosen path less viable.

    S: How can AI assist golfers with their playing performance?

    ChatGPT: Artificial Intelligence (AI) can assist golfers with their playing performance in several ways:

    1. Swing Analysis: AI can provide detailed swing analysis using video and sensor data. This can include information about the speed of the swing, the angle of the club, and how the golfer’s body is moving. This data can be used to provide insights and advice on how to improve a golfer’s swing and technique.
    2. Equipment Recommendations: AI can suggest the right clubs and balls based on a player’s swing, skills, and playing style. It can analyze past performance data and current trends to provide personalized suggestions.
    3. Training Programs: AI can create personalized training programs for golfers, helping them focus on specific areas that need improvement. This can include providing drills and exercises, monitoring progress, and adjusting the program based on the golfer’s performance.
    4. Game Strategy: AI can help golfers develop game strategies based on an analysis of past performance, conditions of the golf course, and strengths and weaknesses of the player. This can include deciding which club to use, aiming and power advice, and planning the course route.
    5. Mental Coaching: AI can also help with the psychological aspects of the game, such as focus and decision-making. This could include mindfulness exercises, focus techniques, and tips on handling pressure.
    6. Virtual Reality (VR): AI, combined with VR, can simulate real golfing experiences for practice and training. This can provide a realistic environment for golfers to practice without physically being on a golf course.
    7. Predictive Analytics: Using machine learning algorithms, AI can predict future performance based on patterns in past data. This can help golfers and their coaches to make strategic decisions.
    8. Injury Prevention: By analyzing a golfer’s movement and technique, AI can identify potential risks of injury. It can recommend modifications to swing mechanics or suggest specific conditioning exercises to help prevent injury.

    AI is transforming the way golfers train, play, and improve their game, providing them with personalized, data-driven insights and recommendations.

    S: It sounds like AI will be able to give golfers lessons on how to improve their game. Is this correct?

    ChatGPT: Yes, you’re correct. With advanced technologies, AI can serve as an interactive coach, giving golfers feedback and suggestions on how to improve their game. Here are some of the ways it can do this:

    1. Swing Analysis: By using video technology and motion sensors, AI can analyze a golfer’s swing in great detail. It can provide instant feedback on the speed, angle, and efficiency of the swing, and give specific recommendations on what needs to be adjusted for better performance.
    2. Personalized Lessons: Based on the data collected, AI can tailor lessons to a golfer’s specific needs, focusing on areas that need improvement. This can be anything from suggesting new techniques, offering practice drills, or helping with strategy for different courses.
    3. Progress Tracking: AI can track a golfer’s progress over time, providing insights on whether adjustments and practice are leading to improvement. It can also use this data to adjust the training program to keep challenging the golfer and promote continued progress.
    4. Virtual Reality Practice: With AI and Virtual Reality (VR), golfers can practice in a variety of simulated environments, facing different challenges. AI can provide feedback and lessons within this virtual space, providing a safe and controlled environment to try out new techniques or strategies.
    5. Predictive Analysis: AI can predict future performance trends based on past data, which can guide the direction of lessons and suggest areas to focus on.

    In essence, AI can provide interactive, personalized, and dynamic lessons to golfers, helping them to continuously improve their skills and performance.

    S: Thinking about this, can you envision a driving range being transformed into a golf learning center where hitting bays are fitted with everything you mentioned and golfers could go there to get lessons, 24 hours a day, 7 days a week?

    ChatGPT: Absolutely, that’s an innovative and very feasible idea. Here’s how such a futuristic, AI-powered golf learning center might look like:

    1. Automated Bays: Each hitting bay could be equipped with high-speed cameras, radar, and sensors to capture swing data such as speed, launch angle, spin rate, and direction. AI would analyze this data in real-time and provide instant feedback.
    2. Virtual Reality: The bays could include VR headsets that allow golfers to practice on a variety of simulated courses, with different challenges and conditions. AI could offer guidance and strategies during these virtual rounds.
    3. AI Coaching: Screens in the bays could display the AI’s analysis of the golfer’s performance, offering tips for improvement. The AI system could also suggest personalized drills and exercises.
    4. 24/7 Availability: With automated systems and AI, the golf learning center could be open 24/7, allowing golfers to practice and learn at any time that suits them.
    5. Fitness and Injury Prevention: AI could monitor the physical strain of golfers and suggest specific exercises or rest periods to prevent injuries. It could even coordinate with wearable devices to monitor heart rate, muscle fatigue, etc.
    6. Progress Tracking: The AI could keep track of a golfer’s performance over time, adjusting its coaching and suggestions as the golfer improves. Golfers could access this progress report anytime, anywhere, to stay motivated and informed about their development.
    7. Social Aspects: The center could have a social aspect, too, with leaderboards displaying progress, competitions, and achievements. It could create a community where golfers learn from and challenge each other.
    8. Remote Coaching: For human touch, professional coaches could access the golfer’s data and offer remote coaching, complementing the AI. This could be done via video calls, messaging, etc.

    With these features, a driving range could be transformed into a highly advanced, AI-driven golf learning center, offering golfers of all skill levels a chance to learn and improve their game in a dynamic, personalized, and convenient way.

    S: Because this is an early blog post I will ask the same questions of Bard and get its take, thereby providing two AI perspectives on the same theme.

    S: How can AI assist golfers with their playing performance?

    Bard: Artificial intelligence (AI) is rapidly changing the way we play golf. Here are some of the ways AI is being used to assist golfers with their playing performance:

    • Analyze swing mechanics: AI-powered golf apps and devices can analyze your swing mechanics in real time and provide feedback on your technique. This can help you identify areas where you need to improve and make adjustments to your swing.
    • Provide club recommendations: AI can also be used to recommend the best club for a particular shot. This is done by analyzing factors such as the distance to the hole, the wind conditions, and your swing speed.
    • Track performance: AI can track your performance over time, providing you with data on your shots, drives, and putts. This data can be used to identify areas where you need to improve and track your progress over time.
    • Generate personalized training plans: AI can also be used to generate personalized training plans based on your individual strengths and weaknesses. This can help you focus on the areas of your game that need the most improvement.
    • Create virtual courses: AI can be used to create virtual courses that you can practice on from the comfort of your home. This is a great way to improve your game without having to travel to a golf course.

    Overall, AI is a powerful tool that can help golfers of all skill levels improve their game. As AI technology continues to develop, we can expect to see even more innovative ways for AI to be used in golf.

    S: It sounds like AI will be able to give golfers lessons on how to improve their game. Is this correct?

    Bard: Yes, that is correct. AI is already being used to give golfers lessons on how to improve their game.

    In the future, AI is likely to become even more sophisticated in its ability to give golf lessons. AI systems will be able to analyze a golfer’s swing in real time and provide feedback on their technique. They will also be able to track a golfer’s performance over time and identify areas where they need to improve. Based on this data, AI systems will be able to generate personalized training plans that are tailored to each golfer’s individual needs.

    As AI technology continues to develop, it is likely that AI-powered golf lessons will become increasingly popular. These lessons will be more affordable and convenient than traditional golf lessons, and they will be able to provide golfers with more personalized and effective instruction.

    S: Thinking about this, can you envision a driving range being transformed into a golf learning center where hitting bays are fitted with everything you mentioned and golfers could go there to get lessons, 24 hours a day, 7 days a week?

    Bard: Yes, I can definitely envision a driving range being transformed into a golf learning center. In fact, I think it is a very likely possibility in the future. With the increasing popularity of AI-powered golf lessons, driving ranges will need to find new ways to stay competitive. One way to do this is to offer AI-powered golf lessons at their facilities.

    A golf learning center would have all of the features that you mentioned, such as hitting bays fitted with sensors and cameras that can track a golfer’s swing and provide feedback. The center would also have AI-powered caddies that can recommend clubs and strategies for each shot. In addition, the center would have a variety of other training tools and analytics features that golfers could use to improve their game.

    The center would be open 24 hours a day, 7 days a week, so golfers could come in and get lessons whenever they want. This would be a great option for golfers who are busy during the day and can only practice at night. It would also be a great option for golfers who want to practice on their own but want some guidance from an AI-powered caddie.

    I think a golf learning center would be a very popular and successful venture. It would provide golfers with a convenient and affordable way to improve their game. It would also be a great way for golfers to learn about the latest AI-powered golf technology.

    S: How much of this do you believe? Will it happen, in what form, and how fast? With respect to lessons, how will affordability and diminishing supply (scarcity of trained professionals) factor in? I encourage you to continue the subject with an AI chatbot or real people and make your own determinations.

    June 30, 2023

    Stu Healey, President

    Handicomp, Inc.

  • Teeing off with A.I.

    Teeing off with A.I.

    S: For my first post, I think I’ll start on the green and take a two foot gimmie; there’s no point risking a bad shot on the first hole. I’ll begin by engaging with ChatGPT and posing three straightforward questions about golf. These initial inquiries will act as stepping stones, leading us to a better understanding of the profound impact that AI can have on the business of golf.

    S: Explain the impact you feel AI will have on the business of golf.

    ChatGPT: The impact of AI on the business of golf is poised to be significant and transformative. AI technologies have the potential to revolutionize various aspects of the industry, ranging from enhancing player experience to optimizing operational efficiency. Here are a few key areas where AI can make a substantial impact:

    1. Player Performance and Training: AI-powered analysis and tracking systems can provide in-depth insights into players’ performance, including swing analysis, shot accuracy, and course management. By leveraging machine learning algorithms, AI can identify patterns, offer personalized recommendations, and facilitate data-driven coaching to help golfers improve their skills and enhance their overall performance.
    2. Course Management and Maintenance: AI can assist golf course managers in optimizing resource allocation, turf management, and maintenance schedules. With the help of sensor networks and AI algorithms, course conditions can be monitored in real-time, enabling proactive decision-making regarding irrigation, pest control, and course design modifications. This can lead to more efficient operations, cost savings, and improved playing conditions.
    3. Data Analytics and Fan Engagement: AI-powered data analytics can extract valuable insights from vast amounts of data collected during tournaments, including player statistics, audience preferences, and social media interactions. These insights can help golf organizations better understand their fan base, tailor marketing strategies, and provide personalized experiences to enhance fan engagement.
    4. Virtual Reality and Simulations: AI-driven virtual reality (VR) and augmented reality (AR) technologies can create immersive golf experiences for both players and fans. VR simulations can replicate famous golf courses, allowing players to practice and experience renowned courses virtually. Additionally, AR can provide spectators with real-time player stats, course information, and interactive content, enhancing their viewing experience.
    5. Smart Equipment and Club Fitting: AI can contribute to the development of smart golf equipment and club fitting processes. By analyzing data from sensors embedded in clubs and balls, AI algorithms can provide golfers with precise feedback on their swing mechanics and suggest equipment modifications to optimize performance. AI-powered club fitting systems can help players select the most suitable clubs based on their swing characteristics and playing style.

    Overall, AI has the potential to revolutionize the business of golf by enhancing player experiences, optimizing operations, enabling data-driven decision-making, and fostering deeper engagement with fans.

    S: Define, compare and contrast match play and stroke play competition.

    ChatGPT: Match play and stroke play are two different formats of competition in golf. Here’s a definition of each, along with a comparison and contrast between the two:

    1. Match Play: In match play, two golfers or teams compete against each other hole by hole. The objective is to win individual holes rather than focusing on the total number of strokes for the entire round. The player or team that wins the most holes at the end of the match is declared the winner. Each hole is treated as a separate contest, and the player or team with the lowest score on a hole wins that hole. If the scores are tied on a hole, it is considered “halved.” Matches can end before all 18 holes are played if one player or team secures an insurmountable lead.
    2. Stroke Play: Stroke play, also known as medal play, is the most common format in golf. In stroke play, each golfer or team plays the entire round (usually 18 holes) and records the total number of strokes taken. The objective is to complete the round using the fewest number of strokes possible. The player or team with the lowest total score at the end of the round is declared the winner. Stroke play is typically used in professional tournaments and for handicapping purposes.

    Comparison:

    • Objective: In match play, the objective is to win individual holes, while in stroke play, the objective is to achieve the lowest total score for the entire round.
    • Scoring: In match play, only the winner of each hole is relevant, while in stroke play, all strokes are counted towards the total score.
    • Duration: Match play matches can end before all 18 holes are played if one player or team secures a winning lead, whereas stroke play always encompasses the entire round.
    • Focus: Match play encourages a more strategic and aggressive style of play, as players can take risks to win individual holes. Stroke play emphasizes consistency and minimizing mistakes over the entire round.

    Contrast:

    • Determining the Winner: In match play, the winner is determined by the number of holes won. In stroke play, the winner is determined by the total number of strokes taken.
    • Effect of Others’ Performance: In match play, a player’s performance is directly influenced by their opponent’s performance on each hole. In stroke play, a player’s performance is not dependent on others and is solely based on their own scores.
    • Comebacks: In match play, a player or team can stage a comeback even if they are losing by a significant margin, as each hole represents a fresh opportunity to win. In stroke play, a significant deficit is harder to overcome since it requires consistently outperforming opponents over multiple holes.

    In summary, match play focuses on winning individual holes, while stroke play focuses on achieving the lowest overall score. Match play allows for strategic and aggressive play, while stroke play emphasizes consistency and minimizing mistakes over the entire round.

    S: Why do you fix a ball mark on a green and how do you do it?

    ChatGPT: A ball mark is a depression or indentation on a green that is caused by a golf ball landing on the putting surface. It is important to fix ball marks on greens to maintain the smoothness and health of the putting surface. Here’s why and how you should fix a ball mark:

    1. Why fix a ball mark: When a golf ball hits the green at a high velocity, it can leave a mark that disrupts the grass and creates an indentation. If left unrepaired, these ball marks can impede the growth and recovery of the turf, affecting the overall quality of the green. Additionally, an unfixed ball mark can alter the roll of a putt, causing the ball to bounce or veer off course. By promptly fixing ball marks, golfers contribute to the preservation and optimal playing conditions of the green.
    2. How to fix a ball mark: Repairing a ball mark is a simple process that can be done with a few easy steps: a. Approach the ball mark from the sides, rather than inserting the repair tool into the center of the depression. b. Insert the repair tool (such as a divot tool or a tee) at an angle, sloping it toward the center of the mark. c. Gently push the edges of the ball mark toward the center, leveling the grass without lifting or prying. d. Lightly tamp down the repaired area with the sole of your putter or your foot to ensure it is smooth and level with the surrounding turf. e. Avoid tearing the grass or creating additional damage while repairing the ball mark.

    It’s worth noting that when repairing a ball mark, it’s best to avoid lifting the soil from the center of the mark, as this can potentially damage the roots beneath the surface. Properly repairing ball marks not only benefits the golf course and other players but also demonstrates good etiquette and respect for the game.

    S: These three answers were generated in a matter of seconds and they are thorough, demonstrating the potential of AI to provide well-researched and well-written responses, surpassing those of many industry experts. It makes it easy to envision the immense value that such a powerful resource will bring to the business of golf.

    Without further ado, let’s dive in and see where this leads…

    June 25, 2023

    Stu Healey, President

    Handicomp, Inc.