Recently, I purchased the new FlightScope Mevo Gen 2 launch monitor with the hope that not only would it make my garden practise sessions more fun, but that I could collect and analyse data about my golf swing that would hopefully allow me to become a better golfer. In theory, with the ability to measure 18 data parameters, the Gen 2 really should be able to help me become a better golfer; however, this is dependent on me being able to analyse and make sense of the data, and then utilise this to improve my golf swing.
Whilst I currently understand what most of the data parameters are, I haven’t fully gotten up to speed with them all yet, or worked out which numbers are good, which are bad, and what I should be targeting in order to improve. After all, I have only just recently unboxed, set up and tested my FlightScope Mevo Gen 2 for the very first time.
With generative AI tools now being so prevalent in our everyday lives, this got me thinking. Would it be possible to feed some of my FlightScope data into ChatGPT, and get it to not only analyse it, but to compare my data with other golf groups, highlight what I’m doing well and provide tips for improvement? Well, to test this out, I exported the data from my FlightScope dashboard, booted up ChatGPT, fed in the following prompt and sat back, allowing it to do the rest.
If you are a golf professional, have knowledge of the golf swing or golf swing data, I’d love to hear your thoughts on how well you think ChatGPT has done analysing my swing data and providing recommendations for improvement. Please do let me know in the comments area below!
The prompt and my data
“I used my FlightScope Mevo Gen 2 in my outdoor garden practise area (hitting net) to gather some data about how well I hit golf shots with my 6 and 8 irons. Can you analyse the data below, and tell me what I am doing well, and not so well, and what I can focus on to improve my ball striking? I’d like you also to compare my swing data with that of PGA Tour, LPGA Tour and amateur golf data. I am a 7 handicap golfer.”
The output from ChatGPT
Here’s the output from ChatGPT related to my above prompt and data.
1. Data summary - my averages
First of all, ChatGPT provided a summary of my averages for seven key metrics vs those of a PGA Tour, LPGA Tour and 7-10 handicap golfer, as well as providing some observations for both my 6 iron and 8 iron shots.
6 Iron (7 shots)
| Metric | Your Avg | PGA Tour | LPGA Tour | 7–10 Hcp Avg |
|---|---|---|---|---|
| Ball Speed (mph) | 110.4 | 130-135 | ~115-120 | ~115 |
| Club Speed (mph) | 85.6 | 92-95 | 78-80 | 84-88 |
| Smash Factor | 1.29 | 1.38 | 1.33 | 1.30–1.32 |
| Carry Distance (yds) | 152.4 | 180-195 | 150-160 | 160-170 |
| Spin Rate (rpm) | 5397 | 5500–6500 | ~6000 | 5000–6500 |
| Launch (V°) | 16.5° | 14–17° | 17–19° | 16–19° |
| AOA (°) | -3.5° | ~-4° | ~-3° | -3 to -5° |
Below are ChatGPT’s observations based on the above 6 iron data.
Club speed is solid, but a touch low for a 7-hcp aiming for elite consistency.
Ball speed is a bit low, likely due to slightly off-centre contact or efficiency.
Smash factor (1.29) is okay, but below elite (1.33–1.38).
Spin is within range, but varies—some lower than ideal.
Launch and AOA look appropriate – your 6i swings down with a consistent negative AOA, which is good.
8 Iron (20 shots)
| Metric | Your Avg | PGA Tour | LPGA Tour | 7–10 Hcp Avg |
|---|---|---|---|---|
| Ball Speed (mph) | 100.0 | 115-120 | ~105-110 | ~100-105 |
| Club Speed (mph) | 82.0 | 87-91 | 74-78 | 80-85 |
| Smash Factor | 1.22 | 1.33 | 1.30 | 1.25–1.30 |
| Carry Distance (yds) | 131.7 | 160-170 | 135-145 | 135–145 |
| Spin Rate (rpm) | 6018 | 7500–8500 | 7000–8000 | 6000–8000 |
| Launch (V°) | 20.9° | 16–20° | 19–22° | 18–22° |
| AOA (°) | -4.3° | ~-4° | ~-3.5° | -3 to -5° |
Below are ChatGPT’s observations based on the above 8 iron data.
Ball speed is decent, but smash factor is low (1.22) – suggesting inconsistent face contact.
Spin rate is on the lower end for an 8-iron, meaning approach shots may roll out more.
Carry distance is slightly short for a 7-hcp, and there’s high variance (std dev ~15 yds).
Launch and AOA are good, you’re presenting the club well.
2. What I'm doing well
Based on my data, ChatGPT has suggested that I do the following well:
- Consistent attack angle – your AOA is reliably shallow but descending (especially for irons), which is solid.
- Launch angles are appropriate – you’re not ballooning or delofting excessively.
- Club speed is respectable – especially for your handicap, particularly with the 6 iron.
- Spin axis is reasonably neutral – good sign of face/path control, though there’s some tendency to pull.
3. Areas for improvement
Of course, as you’d expect, with those numbers (and being an amateur golfer), there’s always room for improvement, and according to ChatGPT, this is what I could do better.
Smash Factor (Efficiency)
- 6 iron: 1.29 average → decent but could be higher (ideal: 1.33–1.38)
8 iron: 1.22 average → needs improvement
2. Dispersion (Distance + Direction)
- 8-iron has high variability – std dev of 14.8 yds in carry is significant.
- Several shots are pulls or fades, some with large spin axis variance (up to ±24°).
- Directional consistency: More left misses (Pull/Pull-Draw), showing a clubface that’s closing relative to path.
3. Strike Quality
- Low smash with the 8i and shot types like “push/slice” and “pull/draw” suggest an inconsistent face-to-path relationship.
- One shot had 72.6 mph ball speed → likely a mishit or very poor contact (anomaly, but worth noting).
4. Comparison to PGA Tour benchmark data
Below is a simplified breakdown of my 6 and 8 iron shot for carry, ball speed, spin and smash factor metrics vs PGA Tour averages.
| Metric | PGA Tour (6i) | Me (6i) | PGA Tour (8i) | Me (8i) |
|---|---|---|---|---|
| Carry (yds) | 185–195 | 152 | 155–165 | 132 |
| Ball Speed (mph) | 130–135 | 110 | 115–120 | 100 |
| Spin (rpm) | 6000 | 5400 | 8000 | 6000 |
| Smash Factor | 1.38 | 1.29 | 1.33 | 1.22 |
According to this data, I am 15–20% behind Tour-level metrics in ball speed and carry, but they don’t call them professionals for nothing.
5. Actionable recommendations
Having analysed and compared my data with that of the professionals and other amateurs of a similar handicap, here’s what ChatGPT suggested I work on:
A. Improve Face Contact
- Use foot spray or impact stickers to locate where you’re striking on the face.
- Focus on center-face contact – even small toe/heel misses dramatically lower smash.
- Drill: “Gate Drill” (place two tees just wider than the ball) to promote centered hits.
B. Improve Distance Control
- Practice half swings and 3/4 swings to develop feel and tempo.
- Play a “ladder drill”: hit 5 shots each trying to land at 120/130/140/150 yards and track your dispersion.
C. Fix Pull Miss Tendency
- Your spin axis is often left (especially with 8i).
- Your face is too closed relative to path, possibly due to early release or overactive hands.
- Drill: “Hold the Face” – try to hit 10 balls with a slightly open face and hold the finish.
D. Improve Smash Factor (Efficiency)
- Focus on tempo, balance, and width in your backswing.
- Use Trackman-style “ladder” games to prioritise quality over quantity.
- Watch swing footage – look for body/arm sequencing that may be off (i.e., arms racing ahead of the body).
Summary of ChatGPTs analysis
Below is a simplified summary of the above analysis from ChatGPT:
| Category | Verdict |
|---|---|
| Ball Striking | Solid, but needs fine-tuning |
| Consistency | Direction decent, distance erratic |
| Face Control | Needs work – pulls dominate |
| Contact Quality | Smash factor can improve |
| AOA & Launch | Well controlled |
| Spin Rates | 6i okay, 8i a bit low |
| Carry Distances | Short for your handicap |
Final thoughts
So there you have it, a full analysis and breakdown of my FlightScope launch monitor data in seconds from ChatGPT. As with all generative AI output, it’s important to carefully assess how accurate and truthful the output is. Without linked sources, it’s difficult to work out whether or not those PGA Tour/LPGA Tour/Amateur metrics that my data was compared against are actually reliable. That said, I do think it’s really useful to know roughly how I compare on metrics such as carry, spin, smash factor and dispersion, and the actionable recommendations certainly provide food for thought.
As mentioned above, I’d love to know your thoughts on this analysis and these recommendations based on your knowledge of the golf swing, performance data or role as a golf coach, so be sure to let me know in the comments section below!
