Reading Your Data — The Scratch Project

The Stats Framework

On-course stat tracking converts subjective "I think I need to work on X" into objective "the data shows I lose 1.2 strokes per round on approaches from 150–175 yards." The difference between those two statements is the difference between purposeful practice and comfortable practice.

📊 Data-Driven Improvement

Why Traditional Stats Miss the Point

Fairways Hit and GIR Are the Wrong Metrics

Traditional golf statistics — fairways hit, greens in regulation, putts per round — are flawed as improvement guides. They conflate quality and context. Strokes Gained solves both problems by measuring performance relative to expectation — every shot compared to the Tour average for that exact situation.

Why Traditional Stats Mislead

Putts per round: 28 putts could mean excellent putting
OR missing 8 greens by 1 foot (easy chips, short putts).
Same number — completely different meaning.

GIR: 10 greens hit from average of 185 yards
OR 10 greens hit from average of 142 yards.
Same GIR — completely different ball-striking quality.

The Five Strokes Gained Categories

The Complete Picture of Your Game

Category	Covers	10 HCP Typical
SG: Off the Tee (OTT)	All tee shots on par 4s and 5s	−0.8 to −1.2
SG: Approach (APP)	All approach shots to the green	−1.2 to −1.8
SG: Around the Green (ARG)	Chips, pitches, bunker under 30 yds	−0.6 to −1.0
SG: Putting (PUTT)	All putts on the green	−0.4 to −0.8
SG: Total	Sum of all four categories	−3.0 to −4.5

⭐

The scratch standard: A scratch golfer averages approximately 0.00 across all SG categories vs. Tour average. The SG breakdown tells you exactly where those 3–4 lost strokes occur — and therefore where practice time produces the highest return.

Strokes Gained — Deep Dive

Each SG category measures a distinct part of the game and requires a different interpretation approach. Understanding what the numbers mean — and what they don't — prevents misdiagnosis and misallocated practice time.

🔬 SG Mechanics

SG: Approach — The Most Impactful Category

Where Most of the Game Is Won or Lost

1
What it measures: The expected strokes to hole out from your approach position compared to where you finish. If you are 150 yards out (expected 2.9 strokes to hole) and finish 25 feet from the flag (expected 2.1 strokes) — you gained 0.8 SG on the approach.
2
Distance bands matter: Break SG: APP by distance band — 100–125, 125–150, 150–175, 175–200, 200+. A player who loses 0.3 SG from 150–175 yards but gains 0.1 SG from 125–150 has a very specific practice target. The overall number hides this.
3
Direction of miss: If 68% of short-side misses are left, that tendency is systematic — adjust aim or check shot shape consistency.

SG: Putting — The Most Misread Category

Make Percentage by Distance

Distance	Tour Make %	Scratch Make %	10 HCP Make %
3 feet	99%	97%	92%
5 feet	88%	80%	68%
8 feet	65%	52%	38%
10 feet	52%	40%	28%
15 feet	32%	22%	14%
20 feet	20%	13%	8%

💡

Critical cross-reference: Poor SG: PUTT can indicate approach shot problems, not putting problems. A player consistently leaving approaches at 45 feet will have worse SG: PUTT than one leaving them at 18 feet — even with identical putting technique. Always cross-reference with SG: APP before concluding you have a putting problem.

SG: Off the Tee

Distance vs. Accuracy Trade-off

1
Distance vs. accuracy trade-off: SG: OTT captures both. A short accurate drive and a long slightly offline drive can produce the same SG value if expected strokes from each position are equal.
2
Penalty frequency first: OB, water, and unplayable lies are the most damaging tee shot outcomes. One penalty shot per round costs more SG than any other single tee shot metric. Address penalties before addressing distance.
3
Average approach distance bridge: If adding 20 yards of driving distance reduces average approach from 168 to 148 yards, the GIR gain from that distance increase is quantifiable — and is often the strongest argument for speed training.

SG: Around the Green

The Most Undervalued Category at 10 HCP

Scrambling % — Make Par After Missing Green

Tour average

58–62%

Scratch amateur

46–52%

5 HCP

36–40%

10 HCP

24–28%

Arccos & Shot Scope

Both platforms automatically track every shot using GPS sensors. Both produce SG data but differ in interface, subscription model, and depth of specific analytics. Arccos now offers three hardware options including Air (sensorless) and Gen 4 sensors.

📡 Platform Guide

Arccos — Gen 4 Sensors & Air

Three Hardware Options, Same Analytics

1
Arccos Air (sensorless — recommended if already using): Tracks shots using only the Link Pro device in your pocket — no sensors on clubs required. GPS-based shot detection powered by a firmware update to the existing Link Pro. If you already have a Link Pro, the update is free. Less precise than sensor-based tracking on short shots and putting, but excellent for full-swing data and SG: OTT and SG: APP.
2
Gen 4 Smart Sensors (launched early 2025): 16 sensors (14 + 2 spares), improved connectivity, refreshed 2D/3D course mapping with pinch-to-zoom, and a new AI Rangefinder. The Smart Club Distances feature has been significantly improved — your actual carry per club from real tracked rounds, updated continuously. Most accurate option for all SG categories including putting.
3
Strokes Gained dashboard: The home screen shows SG breakdown across all five categories with trend lines. Navigate to Analytics → Strokes Gained → Rolling Average. The 10-round rolling average is the only number that matters for practice decisions.
4
Approach analysis by distance: Under Analytics → Approach, filter by distance band. Identify your worst-performing 25-yard window. This data point should determine the next 4 weeks of approach practice.
5
Caddie AI: Following Caddie recommendations has been shown in Arccos internal data to improve approach proximity vs. manual club selection for many players. Use it for 10 rounds to evaluate its impact on your own game before deciding whether to rely on it. Note: AI Caddie must be disabled for competition — check your club's local rules before the round.

Shot Scope V5 Pro

Key Features and Dashboard Navigation

1
Performance dashboard: Shot Scope compares your stats to your handicap group rather than Tour average — arguably more useful for practice prioritisation than Tour benchmarking. The V5 Pro (current model, released 2024) adds a larger display and enhanced shot detection accuracy. The companion app has expanded its SG analytics significantly since 2024, now offering full five-category SG breakdowns directly on the platform.
2
Proximity to hole by distance: Navigate to Approach → Proximity → by Distance. Your average distance from the flag by 10-yard distance band — the clearest single view of approach shot performance. Shot Scope's handicap-group comparison means you see where you underperform vs. similar-handicap players, not just Tour.
3
Miss pattern mapping: Shot Scope plots every approach miss on a green graphic. Over 20+ rounds, this reveals a clear directional bias. If 65% of misses are left, that is your systematic miss — adjust your aim point (see Guide 20 Approach Miss Direction).
4
Phone-free advantage: Shot Scope tracks automatically via the wrist device without a phone on the course — a meaningful benefit for those who prefer a clean, undistracted round. Data syncs to the app post-round. The wrist GPS also doubles as a rangefinder with hazard distances on approach shots.

Golfmetrics

Manual-Entry SG — The Precision Tool

1
What makes Golfmetrics different: Unlike Arccos and Shot Scope (GPS auto-tracking), Golfmetrics is manual-entry. You input each shot's lie category, distance, and outcome. This requires discipline but produces more accurate data — GPS tracking misses nuances like unplayable lies, gimme putts, and penalty drops that Golfmetrics captures precisely.
2
The SG workflow: Navigate to Stats → Strokes Gained. Golfmetrics uses a comprehensive shot-value database to calculate SG for every lie category at every distance. The sub-category depth — SG: Approach broken down by lie (fairway, rough, bunker, recovery) and distance band — is more granular than Arccos or Shot Scope.
3
Best for: Players who prefer accuracy over convenience. The data quality advantage compounds over time. Widely used by serious UK county-level amateurs. Annual subscription approximately £50.
4
Key report — GIR by lie: Golfmetrics shows GIR percentage broken down by lie type (fairway, rough depth, specific areas). This reveals whether approach problems are distance-based, lie-based, or directional — a distinction GPS platforms cannot make cleanly.

Hole19, 18Birdies & Hybrid Platforms

GPS-First with Partial SG

1
Hole19 Premium (~£30/yr): GPS rangefinder with optional stat tracking. The premium tier adds proximity-to-hole analytics and a simplified SG calculator. Best suited to players transitioning from no tracking to active stat use — lower commitment than Arccos/Shot Scope.
2
18Birdies Pro (Free/£30/yr): Similar GPS/stats hybrid with a well-designed interface. Partial SG data on the premium tier. Useful as supplementary tracking when Arccos sensors aren't practical (practice rounds, links trips).
3
Platform combination strategy: The highest-data approach uses two platforms in parallel — Arccos for automatic round tracking combined with Golfmetrics for quarterly deep-dives. Shot Scope is the best single-platform option for those who want wrist-based tracking without a smartphone during the round.

Platform Comparison

Which Platform for Which Player

Platform	Method	SG Depth	Cost	Best For
Arccos Caddie	Auto (grip sensors)	Full — 5 categories	~£120/yr	Convenience + AI caddie
Shot Scope	Auto (wrist device)	Full + handicap compare	~£150 device	Phone-free tracking
Golfmetrics	Manual entry	Most granular	~£50/yr	Accuracy over convenience
Hole19 Premium	GPS + manual	Partial	~£30/yr	Entry-level tracking
18Birdies Pro	GPS + manual	Partial	Free/£30/yr	Supplementary tracking

Strokes Gained Without a Tracking Device

Every recommendation in this system assumes SG data — but the methodology does not require Arccos, Shot Scope, or any paid tracker. A pen, a simple scorecard template, and 10 minutes per round produces genuinely useful SG estimates. This tab is your complete starting point if you have no tracking device, or simply prefer manual recording.

📝 The Five-Number Method

What to Record — Five Numbers Per Hole

The Minimum Viable Dataset

1
Tee shot result (par 4s/5s only): Fairway hit (F), missed left (L), missed right (R), or penalty (P). One letter, no detail needed.
2
Approach proximity: After your approach shot to the green (the shot that's meant to find the green), estimate distance to the hole in paces (1 pace ≈ 1 yard). "12 paces" is good enough — you don't need a laser.
3
Greens in regulation: Y or N. Did you reach the green in the "regulation" number of shots (2 for par 4, 1 for par 3, 3 for par 5)?
4
Putts taken: The number of putts on that hole. This single number, tracked over 20 rounds, tells you more about your putting than almost any other metric.
5
Up-and-down (if applicable): If you missed the green, did you get up and down (chip/pitch + 1 putt or fewer)? Y or N.

💡

Where to write it: Most scorecards have a blank column or back page. A 5-character code per hole (e.g. "F-12-Y-2-—") takes under 10 seconds to record after each hole and does not slow play.

Converting Manual Data to SG Categories

Approximate Mapping — Good Enough to Act On

SG Category	What to Track Manually	How to Interpret
SG: Off the Tee	Fairways hit % + penalty count on par 4/5 tee shots	Under 50% fairways with 1+ penalty/round = OTT is a leak. Over 60% with 0 penalties = OTT is fine, look elsewhere.
SG: Approach	Average proximity (paces) on approach shots, split into bands: under 100yd, 100–150yd, 150–175yd, over 175yd	If your 100–175yd average proximity is consistently 30+ paces, this matches the confirmed primary leak zone (Guide 37, Guide 51) — prioritise accordingly.
SG: Around the Green	Up-and-down % from missed greens	Under 40% up-and-down = short game leak. Over 55% = short game is a strength.
SG: Putting	Putts per round; 3-putt count	Over 32 putts/round or 2+ three-putts/round = putting leak. Under 30 putts/round with 0–1 three-putts = putting is fine.
Double bogeys	Count holes scored 2+ over par	2+ double bogeys per round is the single biggest manual signal — see Guide 20 (Course Management) for the elimination framework regardless of which category causes them.

The Spreadsheet Option

Free Manual SG Tracking — Google Sheets

If you want closer-to-true SG numbers without a paid tracker, a free Google Sheet with the five inputs above plus a lookup table of PGA Tour average "expected strokes to hole out" by distance and lie (publicly available from Mark Broadie's published research and multiple golf analytics blogs) lets you calculate genuine SG values manually.

▸
The calculation: SG for a shot = (Expected strokes from your starting position) − (Expected strokes from your ending position) − 1. For example, an approach from 150 yards in the fairway has an expected value of roughly 2.8 strokes. If your shot finishes 10 feet from the hole (expected value ≈ 1.5), your SG for that shot = 2.8 − 1.5 − 1 = +0.3.
▸
Realistic expectations: This takes longer than wearing Arccos sensors — roughly 15–20 minutes of data entry per round. For players who enjoy the analytical process, it's genuinely viable. For players who find it tedious, the five-number method above gives 80% of the practical value for 10% of the effort.
▸
When to upgrade: If after 10–15 rounds of manual tracking you're finding real value in the data, Arccos Air (Guide EP8) removes the recording burden entirely and gives you automatic SG by category, shot-by-shot. The manual method is an excellent way to confirm the system is worth the investment before buying hardware.

⚠️

Don't let perfect be the enemy of useful: Manually-tracked data is noisier than sensor data — a single round tells you very little. The five-number method becomes useful after 10 rounds and genuinely informative after 20, exactly like Arccos. The advantage of starting now with manual tracking is that you begin building your 20-round sample immediately, at zero cost, while you decide whether to invest in hardware.

Prioritising Improvements

Your SG data reveals multiple weaknesses simultaneously. The skill is identifying which weakness to address first — the one that produces the largest expected scoring improvement per hour of practice invested.

🎯 Priority Framework

The ROI Prioritisation Matrix

Strokes Per Hour of Practice — Which Category Pays Most

Category	SG Loss	Practice Hours to +0.5 SG	Priority
SG: Approach (150–175 yds)	−0.8/rnd	20–40 hrs	1st — highest ROI
SG: Around-Green scrambling	−0.6/rnd	15–30 hrs	2nd — highly trainable
SG: Off the Tee (penalty rate)	−0.4/rnd	10–20 hrs	3rd — strategic fix first
SG: Putting (5–10 ft)	−0.3/rnd	20–40 hrs	4th — smaller marginal gain

⭐

The 10 HCP to scratch truth: Across 200,000+ tracked rounds, SG: Approach accounts for 40% of the scoring gap between 10 HCP and scratch. Approach before putting — always. The instinct to practise putting is strong; the data consistently shows approach work pays more.

When to Deviate From Data Priority

Conditions Where the Matrix Does Not Apply

1
Technical change in progress: If you are currently rebuilding a swing element (e.g. wrist mechanics), that work takes priority regardless of what the SG data says. The technical fix is the root cause; the SG loss is the symptom. Fix the cause.
2
Small sample size: If your data is based on fewer than 15 rounds, do not make major practice plan changes. See the Sample Size tab for minimum sample thresholds.
3
Competition-specific weakness: If you have an important competition on a specific type of course (links, parkland, hilly) in 4 weeks, practise the skills that course demands — even if they are not your statistically weakest category.

Data to Practice Plan

Translating SG data into a practice plan requires a clear bridge between what the numbers show and what specific drill or session addresses it. This tab provides that bridge.

📋 Translation Framework

SG Data → Specific Practice Action

The Four-Step Translation

1
Identify the category: Which of the four SG categories shows the largest negative relative to target? Check your 10-round rolling average, not a single round.
2
Break down to sub-skill: Within SG: Approach, is the loss concentrated at 150–175 yards, or 125–150? Within SG: Putting, is it lag putting or short putts? The sub-skill is the drill target.
3
Diagnose the cause: Is the loss a technical issue (use Mevo and HackMotion), a strategic issue (use miss pattern data), or a practice-to-course transfer issue (use the Practice Structure Science guide)?
4
Set a measurable target: "Improve SG: Approach from 150–175 yards by 0.3 over the next 6 weeks" is measurable. "Work on my irons" is not. Every practice block should have a specific SG sub-category target with a timeframe.

SG Data to Drill Reference

Which Guide and Drill to Use for Each SG Weakness

SG Weakness	Likely Cause	Guide Reference	Specific Drill / Protocol
SG: APP 150–175 yds	Ball speed, attack angle, or miss direction	Guide 03 + Mevo guide	Attack angle protocol; miss direction aim points
SG: APP proximity — all distances	Dynamic loft inconsistency	Guide 03 Wrist Mech.	Lead wrist flexion drills; HackMotion impact position
SG: ARG up-and-down rate	Landing zone accuracy	Guide 02 Adv. Wedge	Spin mapping protocol; landing zone targeting drill
SG: ARG bunker save rate	Entry point, bounce utilisation	Guide 02 Bunker tab	Sand entry drill; bounce-first impact protocol
SG: PUTT — 5–10 feet	Start line accuracy	Guide 01 Direction tab	Alignment stick drill; chalk line gate drill
SG: PUTT — lag putting	Pace control from distance	Guide 01 Pace tab	Clock drill; target-focus long putt protocol
SG: OTT — penalty rate	Tee strategy, miss direction	Guide 20 Tee Strategy	Miss direction planning; tee box positioning
SG: OTT — distance loss	Speed, GRF, smash factor	Guide 25 + Guide 06 GRF	Rypstick speed protocol; GRF Phase 1–3 drills

Sample Size & False Patterns

The greatest risk in data-driven improvement is making significant practice changes based on patterns that do not yet exist — small samples amplify noise into apparent signals. Understanding minimum sample requirements prevents wasted practice time chasing ghosts.

⚠️ Sample Size Rules

Minimum Rounds for Reliable Conclusions

When You Can and Cannot Trust the Data

Conclusion Type	Minimum Rounds	Confidence Level	What to Do With Less Data
Identify dominant SG weakness	10–15	Moderate (70%+)	Treat as a working hypothesis — do not restructure full practice
Specific distance band weakness	20–25	Good (80%+)	Note the pattern; wait for confirmation in next 5 rounds
Technique change is working	15–20	Moderate	Use Mevo data as early confirmation — SG follows technique with a lag
Confirm practice plan is working	25–30	Good (80%+)	3-round baseline + 25 rounds post-change minimum
Seasonal handicap trend	40+	High (90%+)	Use HCP trend + SG combination, not SG alone

Common False Pattern Traps

What Looks Like Signal But Is Noise

1
"My putting has got worse" after 3 rounds: Three rounds of poor putting could be random variance. The standard deviation of SG: PUTT across rounds is approximately ±1.0 — meaning a normally distributed putting performance can look like +1.0 in round 1 and −1.2 in round 2 with no real change in skill. Never change your putting approach based on 3 rounds.
2
Course difficulty masking SG categories: Playing a hard course will produce worse absolute SG numbers but is not evidence of skill decline. Compare SG across rounds on similar-difficulty courses, or use handicap-adjusted SG (Shot Scope provides this).
3
Weather effects on SG: OTT: Wet conditions reduce driving distance and increase dispersion. A run of wet-weather rounds will produce artificially low SG: OTT that corrects automatically in dry conditions.

Weekly Multi-Tool Synthesis

Your programme uses five data sources simultaneously: Arccos/Shot Scope (on-course SG), Mevo (ball flight and club data), HackMotion (wrist mechanics), video analysis (movement pattern), and HRV/readiness (training state). Each guide covers its tool in isolation. This section provides the unified weekly review workflow that synthesises all five into a single, coherent practice priority each week.

🔄 The Five-Tool Ecosystem

How the Five Tools Relate to Each Other

The Diagnostic Chain — Input to Output

The Diagnostic Hierarchy

HRV (readiness) → determines training intensity available
Arccos / Shot Scope → identifies WHERE strokes are lost on course
Mevo → identifies WHY (ball flight cause: face, path, attack angle)
HackMotion → identifies the ROOT CAUSE (wrist mechanics driving the Mevo numbers)
Video Analysis → CONFIRMS the physical movement pattern behind the numbers

Always diagnose top-down: SG category → Mevo data → HackMotion → Video.
Reverse-engineering (video first) is slower and less precise.

Tool Priority by Question Type

Which Tool to Consult First

Question	First Tool	Confirming Tool	Root Cause Tool
"Where am I losing strokes?"	Arccos/Shot Scope SG	Proximity by distance	Miss pattern plot
"Why is my approach proximity poor?"	Mevo: face angle, F2P, attack angle	HackMotion: impact wrist	Video: impact sequence
"Why is my ball curving?"	Mevo: spin axis, F2P	HackMotion: lead wrist flexion	Video: release pattern
"Am I ready to train hard today?"	HRV reading	Resting heart rate	Sleep quality (Oura/Whoop)
"Is my technique change working?"	HackMotion: position comparison	Mevo: spin axis before/after	Arccos: SG change over 10+ rounds
"What is my practice priority this week?"	Arccos 10-round rolling SG	Mevo session data	HackMotion trend data

🗓️ The 30-Minute Weekly Review Protocol

Sunday Evening Review — Complete Step-by-Step

30 Minutes That Set the Week's Practice Priority

1
Step 1 — SG Review (5 minutes): Open Arccos or Shot Scope. Check the 10-round rolling SG across all four categories. Note which category shows the largest gap from your target. Note whether it is improving, stable, or worsening compared to last week. Write down the weakest category and the sub-skill within it (distance band, shot type).
2
Step 2 — Mevo Data Review (8 minutes): Open your Mevo session data from the past week's range sessions. Check the specific metrics that correspond to your SG weakness:
• SG: APP weak → check attack angle, face angle, F2P consistency, smash factor
• SG: OTT weak → check club speed trend, spin axis, smash factor
• SG: ARG weak → check wedge spin rates, attack angle on short shots
• SG: PUTT weak → Mevo does not measure putting — skip to HackMotion
Note whether Mevo confirms the SG weakness (e.g. high spin axis = confirming face control issue) or contradicts it (e.g. Mevo looks good but SG: APP still weak → strategic/course-management cause, not technical).
3
Step 3 — HackMotion Review (7 minutes): Open HackMotion session data. Check the wrist position benchmarks for your primary Mevo finding:
• High spin axis + open face angle → check lead wrist extension at top and impact
• Low smash factor + early release → check radial deviation at top (lag loading)
• High shot-to-shot variance → check address position consistency (P1 repeatability)
Compare this week's readings to your benchmark session. Note if the metric is moving in the right direction, has plateaued, or has regressed.
4
Step 4 — HRV Trend Review (3 minutes): Open your HRV app. Check your 7-day average vs. your 30-day baseline. If HRV is trending down across the week, your training load may be too high — reduce volume next week. If HRV is above baseline, you are well recovered — push intensity next week on speed and strength sessions.
5
Step 5 — Weekly Priority Decision (5 minutes): Based on steps 1–4, write down one primary practice focus for the week. Use the format:
"Priority: [specific skill] using [specific drill] because [SG data says X] confirmed by [Mevo/HackMotion says Y]."
Example: "Priority: Lead wrist flexion at impact using HackMotion biofeedback because SG: APP is −0.9/round with high spin axis (avg ±14°) confirmed by HackMotion showing +8° lead wrist extension at P7."
6
Step 6 — Update Progress Journal (2 minutes): Log the priority and supporting data in Guide 17 (Progress Journal). Note Mevo benchmarks and HackMotion positions from this week. This creates the longitudinal record that reveals real progress vs. noise over months.

🔍 Resolving Contradictory Data

When Arccos and Mevo Disagree

The Most Common Data Conflicts and How to Resolve Them

Conflict	SG Data	Mevo Data	Most Likely Explanation	Resolution
Good technique, poor SG: APP	SG: APP −1.0+	Face angle, F2P — normal range	Strategic error: wrong club, poor aim points, under-clubbing	Review approach strategy in Guide 20; check Arccos average carry vs. perceived carry
Good SG: APP, poor SG: PUTT	SG: PUTT −0.8	Approach metrics normal	Real putting issue OR leaving approaches too far from flag	Check average approach proximity in Arccos. If >25 ft average, it is an approach problem — not putting
Improving HackMotion, no SG gain	SG flat	Spin axis improving	SG data has a lag — needs 10–15 rounds to show technique improvement	Trust HackMotion data short-term; wait 15 rounds for SG confirmation before concluding the change is not working
Good Mevo in sessions, poor on-course	SG: APP poor	Range data — good	Practice structure issue: blocked range practice not transferring	Switch to interleaved/simulation practice immediately (Guide 05 Practice Science)

📊 Progress Tracking Dashboard — Monthly Review

The Monthly Performance Review

Metrics to Track and Compare Month-to-Month

Once per month — ideally on the same weekend each month — run a 60-minute comprehensive performance review using the following metric set. Record all results in the Progress Journal (Guide 17).

Metric	Tool	Record	Target Direction
SG: Total (10-round rolling)	Arccos/Shot Scope	Absolute value + trend	Increasing (less negative)
SG: APP (10-round rolling)	Arccos/Shot Scope	By distance band	Improving in weakest band
Driver club speed (benchmark test)	Mevo — 10 shots, middle 6 avg	mph to 1 decimal	Increasing (speed protocol working)
Driver smash factor	Mevo — same session	To 2 decimal places	Above 1.46 consistently
7-iron spin axis avg	Mevo — 8 shots, middle 6	± degrees	Reducing toward ±5°
Lead wrist at top (HackMotion)	HackMotion P4	Degrees flexion/extension	Moving toward −5° to −15° (flex)
Lead wrist at impact (HackMotion)	HackMotion P7	Degrees flexion/extension	Moving toward −8° to −18° (flex)
HRV 30-day average	HRV app / Oura / Whoop	rMSSD value	Stable or increasing (recovery improving)
Average approach proximity	Arccos/Shot Scope	Feet, by distance band	Reducing (closer to flag)
Up-and-down rate	Arccos/Shot Scope	Percentage	Increasing toward 35%+

⭐

The longitudinal value: A single month of data tells you very little. Twelve months of consistent monthly data tells you everything — which training blocks produced speed gains, which technique changes improved spin axis, which practice structure changes improved SG: APP transfer, and whether HRV-guided training produced better adaptation than the prior fixed-schedule approach. The monthly review is the compound interest mechanism of the entire programme. Skipping it is the equivalent of investing without ever checking returns.

Multi-Season Trend Analysis

For players with 8+ quarters of SG data, multi-season analysis is the most valuable analytical work available. Most serious amateurs have the data and never use it at this level. The compound record of quarterly SG deltas is your career's most important performance document.

📈 The Three Multi-Season Questions

What 8+ Quarters of Data Reveals

Long-Term Pattern Recognition

1
Which category plateaued first? Most players see ARG and Putting plateau before APP. A category flat for 3+ consecutive quarters despite targeted work needs a coaching intervention, not more of the same practice.
2
Which training blocks produced the largest SG gains? Cross-reference your Progress Journal (Guide 17) with quarterly SG deltas. The activities that moved the needle most are your highest-return activities — repeat them.
3
Are your seasonal cycles working against you? Many players show consistent SG variance by season. Knowing your pattern allows you to plan training that counters natural drift.

📊 Quarterly SG Tracking Template

Copy to Your Progress Journal

8-Quarter Rolling SG Log

Quarter	SG: OTT	SG: APP	SG: ARG	SG: Putt	Total	Primary Training Focus
Q1	—	—	—	—	—	Baseline
Q2
Q3
Q4
Q5
Q6
Q7
Q8

The "Primary Training Focus" column links what you practised to what the SG data shows. With it, you have a personal evidence base for what actually works.

🎓 Bringing Data to Your Coach

The Pre-Lesson SG Brief Format

Four Steps That Double Lesson Productivity

1
Lead with the SG category: "My SG: APP from 125–175 yards is −0.4 vs. scratch baseline. I need −0.1 to reach +1." The coach identifies the technical cause — that is their job.
2
Show the proximity scatter: Share your Arccos proximity report for the specific distance band so the coach can see exactly where the ball lands relative to your aim point.
3
Ask the diagnostic question: "Is this a ball-striking problem, a distance control problem, or a target selection problem?" These have completely different technical interventions.
4
Close the loop: After the lesson, note in your quarterly log what the coach identified and the expected SG impact. Review at the next quarterly audit.

Stats Interpretation

The Stats Framework

Fairways Hit and GIR Are the Wrong Metrics

The Complete Picture of Your Game

Strokes Gained — Deep Dive

Where Most of the Game Is Won or Lost

Make Percentage by Distance

Distance vs. Accuracy Trade-off

The Most Undervalued Category at 10 HCP

Arccos & Shot Scope

Three Hardware Options, Same Analytics

Key Features and Dashboard Navigation

Manual-Entry SG — The Precision Tool

GPS-First with Partial SG

Which Platform for Which Player

Strokes Gained Without a Tracking Device

The Minimum Viable Dataset

Approximate Mapping — Good Enough to Act On

Free Manual SG Tracking — Google Sheets

Prioritising Improvements

Strokes Per Hour of Practice — Which Category Pays Most

Conditions Where the Matrix Does Not Apply

Data to Practice Plan

The Four-Step Translation

Which Guide and Drill to Use for Each SG Weakness

Sample Size & False Patterns

When You Can and Cannot Trust the Data

What Looks Like Signal But Is Noise

Weekly Multi-Tool Synthesis

The Diagnostic Chain — Input to Output

Which Tool to Consult First

30 Minutes That Set the Week's Practice Priority

The Most Common Data Conflicts and How to Resolve Them

Metrics to Track and Compare Month-to-Month

Multi-Season Trend Analysis

Long-Term Pattern Recognition

8-Quarter Rolling SG Log

Four Steps That Double Lesson Productivity