MY SYSTEM · STEP 2 – ANALYSES
How to analyze
Having data is half the battle. Here I show how 5,000 strokes turn into reliable answers — with σ-consistency, Strokes Gained, and median instead of gut feeling.
Three principles to guide any senior golf analysis
Collecting data is easy. Understanding data is the art — and for senior golfers, it's a different discipline than for tour pros. We have less swing speed, more dispersion, and our daily form fluctuates more. Anyone who works with averages here will make the wrong decisions.
For over three years, I've distilled three principles from 4,063 range shots and 50 Excel columns that guide every one of my analyses—from a small range block to an 18-hole evaluation.
Dispersion over mean. Median instead of best. Strokes gained over score. Once these three sentences are in place, the analysis is half done.
Dispersion before mean
An 8-iron with a median of 130 yards and a standard deviation of 6 yards is better than one with a median of 138 yards and a standard deviation of 14 yards. Consistency beats distance — almost always. In senior golf, where the shot lands matters, not how far it would go with a perfect strike. could.
Median instead of best
With „my best drives go 220m,” I misplay a hole. With „my median driver goes 175m,” I play realistically. Senior golfers have more bad shots than perfect ones — the statistics must reflect that, not ego.
Strokes Gained instead of Score
„Gross 51 on 9 holes” says little. „SG -2.23 vs. Scratch, PW as biggest loser with Σ -2.90" says everything. Mark Broadie's method separates luck from skill - and makes every round comparable to any other.
What I really measure per club
Length dispersion
Standard deviation of carry distance. My I8 has σ 7.53 m — best value in the bag between 80 and 120 m. Low = club self-plans.
Page scattering
Standard deviation of the lateral deviation. Says more about water hazards than any distance statistic. During the driver breakthrough on June 9: σB halved from 23 m to 8.9 m.
Median Carry
The median is more robust against outliers than the average. My driver median: 175 m (best 220 m, average is misleading). Plan with the median, not with the best result.
Strokes Gained
Mark Broadie's Gold Standard: How many strokes do I gain or lose per stroke vs. scratch baseline. Best diagnostic measure — Wendlohe C 12.06.: SG −2.23, PW Σ −2.90 as the biggest score killer.
Scrambling-Quote
How often do I save par when I miss the green in regulation? That reveals the strength of my short game. Senior Tour pros average 55 %; I’m aiming for 40 %—my Achilles’ heel in 2026.
3-Putt Rate
What percentage of greens do I leave after three or more putts? The most honest lag-putting stat. My Wendlohe pattern: 3-putts pile up on first putts 4–8 m — this led to the P5 test.
In Five Steps from Raw Data to Training Hypothesis
I do that after every range session and after every round—routine, not a project.
Pull raw data into the master
R10-CSV or Bebrassie-PDF go into the Master Excel. 50 columns, one row per shot - Date, Club, Distance, Side, Spin, Surface, Drill, Note. A central table for everything is the prerequisite for any comparability.
Calculate KPIs per bat
Pivot table with the six KPIs from the block above — n, σL, σB, Median, Strokes Gained, Scatter Ratio. Excel formulas do that. As soon as I add new strokes, all KPIs update automatically.
Compare with target values
Comparison tab in the master Excel with traffic light logic: red for deviation from target, green for hit. Target values from two sources – Tour reference (TrackMan 2024) and realistic HCP brackets for players 60 and over. Without a benchmark, no number is meaningful.
Prioritize weaknesses by score impact
Not all weaknesses are equally important. A driver problem costs 1.5 strokes per round, a 3-putt percentage costs 4 strokes. Score-Impact in Strokes per 9 Holes is my sorting criterion. What costs the most comes first.
Derive training hypothesis
From the diagnosis, it becomes precise one Hypothesis for weekly plan: „If I train PW distance control with Drill W1, σL will decrease from 14m to under 10m in 4 weeks.” Measurable, datable, testable. This moves us to Step 3 — Training after analysis.
Runde Wendlohe Course C, June 12, 2026
This is how an analysis really went – from the brassie export to the week's training focus.
Raw data Bebrassie-Export 9-hole round, 51 gross strokes (+15). First reaction: „Well, it was windy.” Wrong reaction. The right reaction was: look at the data.
SG vs. Scratch: −2.23 strokes
FiR (Fairway in Regulation): 57 % (25 % the previous day)
GiR (Green in Regulation): 11 %
Scrambling: 0 % — one missed green approach lost
Bat Breakdown: The par-3s were step-by-step the biggest score killers with a cumulative -2.90 strokes over the round. Worse than the driver, worse than any putt. Three approaches from 80-100m ended up 12-18m short or long — which is geometrically unavoidable with a stroke length of 14m.
PW σL Soll: ≤ 10 m · IST: 14 m → ROT
Driver SD: ≤ 15 m · IST: 8.9 m → GREEN
Target 3-Putt Rate: ≤ 15 % · Actual: 33 % → ROT
Score-Impact Prioritization: Weakness in putting costs 2.9 strokes per 9 holes, 3-putts cost 1.8 strokes. The driver is in the green zone — no training focus needed. So the order was clear: first wedges, then lag putts.
Training Hypothesis W25: If I practice 30 putts per session, 3 times a week, from 80 meters with distance control (target: 8-meter circle) and practice 2 sets of lag putts from 4–8 meters, I can reduce my PW σL to under 11 meters in 3 weeks and my 3-putt rate to under 25 %. Measurement: Pre/post-test in W25 and W28.
Three Excel files that carry everything
Centralized Excel with all range types. 12 core columns, pivot-ready, automatic KPI calculation. Template: Download Center on „How I Measure”.
Five Tabs: Tour Reference (TrackMan 2024), Target-Mathias (Season + Long-term), Actual-Mathias, Comparison (Traffic Light), Methodology. The Comparison Machine.
Dashboard with trend icons (—/-/+/+++), driver hierarchy, score impact ranking. „Data Rules” tab defines mandatory sources per KPI.
Three Excel files, three thousand rows of formulas. But: they pay for themselves from day one.
Six categories × three to five KPIs
σL · σB · Median-Carry · FiR-Quote · Smash Factor
Shot spin · Life expectancy · Approach distance · Spin values
Distance Control (8m Circle Quote) · σL · Loft Recommendation · Spin Consistency
3-Putt Rate · Lag Putt Distance Remaining · Hole-Out Rate · Putts per Hole
Scrambling Quote · Sand Save Quote · Up-and-Down Distance
Penalty Count · Tea Club Choice · Lay-Up Discipline · Risk Score
From analysis comes training
When the weaknesses are prioritized, the real work begins. Step 3 shows how hypotheses turn into a weekly plan.
German 
English 