In three lines - The FINNS AI coach diagnoses eight areas — pace, heart rate, efficiency, stroke, frequency, volume, lessons, and personal traits — and prescribes concrete Try-This drills with distance, sets, and rest intervals included. - Heart rate zone distribution (Z1–Z5) and recovery heart rate trends give you a measurable picture of the intensity you are actually swimming at, not just the intensity you think you're hitting. - Switching the view to weekly, monthly, yearly, or all-time reveals long-term patterns that disappear inside individual sessions.


1. The Frustration of Solo Swimming — No One to Tell You What Needs Work

After enough laps on your own, a familiar thought surfaces.

"I did 1,500m today. Was that actually good?"
"Heart rate was high but pace didn't improve. What's going on?"
"I had my stroke corrected a while ago — is my SWOLF actually getting better, or not?"

In a coached environment these questions get answered right away. In a solo free-swim lane, you can make dozens of round trips without ever getting close to an answer. The numbers are there. What's missing is the context that connects them — what they mean, and what you should change.

That is the exact problem the FINNS AI coach is built to address. It reads your data and points to a direction: this area is the weak link right now, here is where to start.


2. The Eight-Area Diagnosis — What the Coach Actually Reads

Analysis tab weekly view — swim personality card and AI coach card
Analysis tab weekly view — swim personality card and AI coach card

The AI coach diagnoses your current state across eight areas.

  1. Pace — per-stroke, per-interval 100m-normalized pace and its variability
  2. Heart rate — Z1–Z5 zone distribution, peak HR during the session, recovery HR speed
  3. Efficiency — SWOLF score, distance traveled per stroke
  4. Stroke — per-stroke proportion and dominant stroke pattern
  5. Frequency — weekly session count and interval regularity
  6. Volume — weekly and monthly cumulative distance, average distance per session
  7. Lessons — coached vs. free-swim ratio, structure pattern inside lesson sessions
  8. Personal traits — time-of-day pattern, swim personality type, long-term trajectory

For each of these eight areas the app reads where you currently stand, then focuses its Try-This drill on whichever area has the most room to move.

On the Analysis tab's weekly view, a swim personality card (for example: Endurance, with a SWOLF value) appears at the top, followed immediately by the AI coach card. That card surfaces specific feedback — something like breathing-and-recovery training, with a reference to how quickly your heart rate drops in the first one to three minutes post-swim. Below it, a metrics table shows this week's distance, calories, workout time, average pace, and lap count, each accompanied by a percentage change versus the prior week (▲ or ▼).

For a deeper look at how swim personality types are classified, see Post 05 — AI Coach and Swim Personality Types. This post stays focused on how the eight-area diagnosis turns into drill prescriptions.


3. Reading Change Through Week-over-Week and Month-over-Month Deltas

Analysis dashboard — distance trend bars, weekly/monthly goal completion rate, SWOLF trend line, stroke distribution by day
Analysis dashboard — distance trend bars, weekly/monthly goal completion rate, SWOLF trend line, stroke distribution by day

A single session's numbers tell you how much you did today. They do not show change. When the AI coach runs its eight-area diagnosis, it is the trend and the delta — not the raw value alone — that carries the most weight.

The analysis dashboard puts this picture on one screen.

The week-over-week percentage change you check here is the raw material for the AI coach's diagnosis. If this week's volume is down 22% from last week and SWOLF is up two points simultaneously, the app interprets that combination and works it into the next coaching note.


4. Heart Rate as an Intensity Gauge — Z1–Z5 and Recovery Heart Rate

Heart rate zone distribution Z1–Z5, peak HR trend, recovery HR trend
Heart rate zone distribution Z1–Z5, peak HR trend, recovery HR trend

Among the eight diagnostic areas, heart rate is the most direct window into intensity.

Zone Distribution (Z1–Z5)

The chart shows what percentage of a session — or a selected period in total — was spent in each zone from Z1 through Z5. That alone tells you, at a glance, which intensity band you are actually training in.

Solo swimmers often fall into a rhythm that "feels the same" lap after lap. Looking at the zone breakdown, it is not unusual to discover "I was stuck in Z3 the whole time" or "I intended Z2 recovery but the data says Z4."

Peak HR Trend

The trend of peak heart rate across weeks or months is trackable here. If your peak HR during the same interval set is gradually declining, cardiovascular adaptation is happening.

Recovery Heart Rate Trend — 1, 2, and 3 Minutes Post-Swim

Recovery HR measures how quickly your heart rate falls after the workout ends. The trend tracks your actual HR at the one-, two-, and three-minute marks across sessions.

As fitness improves, heart rate drops faster after sessions of the same intensity. When condition is poor or overtraining is creeping in, the recovery slows. When the AI coach mentions "heart rate recovery difference in the 1–3 minute window" in a weekly note, this is the specific metric it is referring to.


5. Try-This Drill Prescriptions — Distance, Sets, and Rest Included

Once the eight-area diagnosis is complete, the AI coach pairs a "focus on this area" recommendation with a concrete drill — the Try-This.

Why the Drills Are Specific

"Your pace needs work" and "8×100m, each set at threshold pace, 20 seconds rest between sets" are fundamentally different pieces of information. The first is a direction. The second is something you can walk into the pool and execute tomorrow.

FINNS Try-This drills are delivered with distance, set count, target intensity (for example: threshold pace or sustained Z4), and rest intervals. Some examples of the form they take:

These prescriptions draw on swimming training methodology from domains like USA Swimming — the kind of coach-level session design that most amateur swimmers would not otherwise encounter. The key is that the suggestions are matched to your data context, not generic templates handed to everyone.

What Determines Which Drill You Receive

Which Try-This appears depends directly on the eight-area diagnosis results.

Because the drill is tied to a diagnosed area, it is easier to understand why that particular drill was suggested — and to notice whether it is working.


6. Viewing the Longer Arc — Weekly, Monthly, Yearly, All-Time

Analysis tab long-period view — monthly/yearly personality and AI coach note, metrics and pace trend
Analysis tab long-period view — monthly/yearly personality and AI coach note, metrics and pace trend

Short-term data shapes what you do in the next session. But "how have I actually changed over the past three months" requires a wider window.

On the Analysis tab, switching the period to monthly or yearly redraws the same screen against that time span. The personality card (for example: Endurance Builder) and AI coach note regenerate from the data across that period, and the metrics and pace trend below update to match.

Things worth paying attention to in the long-term view:

For the full breakdown of how swim personality types are classified and what each type means in practice, see Post 05 — AI Coach and Swim Personality Types.


7. Closing — Closing the Loop Between Data and Action

Swim apps are generating more data than ever. What to actually do with it is a separate question.

The eight-area diagnosis and Try-This drills are the FINNS AI coach's attempt to close the loop between the number on the screen and the action in the water. A slow recovery HR diagnosis leads directly to what to swim next session. Rising SWOLF leads directly to which drill can address it.

For most of your solo swimming, there is no coach in the lane. Eight-area diagnosis and Try-This are an attempt to fill that gap with data context.

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