Marathon Photography Workflow 2025: From RAW to Organized Galleries

The Complete Marathon Photography Timeline

Let's map out the entire process from pre-race to final delivery.

Race Day: 5 AM - 12 PM (7 hours shooting)

5:00 AM: Arrive at start line

• Scout locations (start corral, mile markers, finish line)
• Test camera settings (dawn light)
• Connect with race organizers

6:30 AM: Elite/wave 1 start

• Shoot start line (200-300 photos)
• Capture elite runners (clean bibs, full-frame)

7:00 AM - 11:00 AM: Course coverage

• Position 1: Mile 5 (400 photos)
• Position 2: Mile 13 halfway point (600 photos)
• Position 3: Mile 20 "the wall" (500 photos)

11:00 AM - 12:00 PM: Finish line

• Peak finish time (1,800 photos)
• Podium + awards ceremony (200 photos)

Total: 3,500 photos across 7 hours

Post-Race: 12 PM - 6 PM (Workflow time)

This is where the magic happens. Here's how to go from 3,500 RAW files to organized, delivered galleries in 6 hours.

Professional marathon photography workflow: shooting to delivery

Pre-Race Preparation (Friday, 2 days before)

Get organized before race day. This 30-minute setup saves 2+ hours later.

1. Get Participant List (10 minutes)

Contact race organizer:

• Email: "Hi, I'm shooting the marathon Sunday. Can you send the participant list?"
• Usually receive: Excel/CSV with 800-2,000 runners
• Includes: Bib number, name, age category, team

If messy data: Use AI to create clean CSV in 5 minutes

Save as: 2025-12-15_City_Marathon_Participants.csv

2. Create Lightroom Catalog (5 minutes)

File → New Catalog:

• Name: "2025-12-15_City_Marathon"
• Location: External SSD for speed
• Create collections:
  • "1_Start_Line"
  • "2_Mile_5"
  • "3_Mile_13_Halfway"
  • "4_Mile_20_Wall"
  • "5_Finish_Line"
  • "6_Awards_Podium"

3. Check Gear (15 minutes)

Camera settings for marathon:

• Mode: Shutter priority (1/500s minimum for running)
• ISO: Auto (1600-6400 ceiling)
• AF: Continuous, wide area
• Drive: High-speed continuous (10-12 fps)

Gear checklist:

• ☐ 2 camera bodies (backup essential)
• ☐ 70-200mm f/2.8 (finish line)
• ☐ 24-70mm f/2.8 (wide shots, start)
• ☐ 4× 64GB memory cards (backup)
• ☐ 2× spare batteries per body
• ☐ Monopod (long lenses, 4+ hour shoots)

Race Day: Shooting Strategy

Goal: Capture every runner at least once with clear bib number visible.

Position Strategy

Position 1: Start Line (6:30-7:00 AM)

• Lens: 24-70mm
• Target: Clean frontal shots, corral energy
• AI benefit: Fresh, excited runners = clear bibs
• Photos: 200-300

Position 2: Mile 5 (7:30-8:30 AM)

• Lens: 70-200mm
• Target: Still fresh, good form, clear bibs
• Location: Find straight section (no turns = better angles)
• Photos: 400-500

Position 3: Mile 13 Halfway (9:00-10:00 AM)

• Lens: 70-200mm
• Target: Peak action, mix of fast and slow runners
• Location: Spectator-friendly zone (energy background)
• Photos: 600-800

Position 4: Mile 20 "The Wall" (10:30-11:00 AM)

• Lens: 70-200mm
• Target: Determination shots, emotion, grit
• Note: Bibs may be obscured (sweat, gear), shoot multiple angles
• Photos: 400-500

Position 5: Finish Line (11:00 AM-1:00 PM)

• Lens: 70-200mm f/2.8
• Target: Peak finish traffic, emotion, celebration
• Setup: Fixed position, continuous shooting
• AI gold mine: Runners face camera, clear bibs
• Photos: 1,500-2,000

Total photos: 3,100-4,100 across 5 positions

Pro Tips for AI-Friendly Shooting

AI detection works best when you:

1. Shoot frontal angles (not back/side when possible)
2. Capture full torso (entire bib visible)
3. Avoid extreme motion blur on bib area (1/500s minimum shutter)
4. Include finish line heavily (runners face camera = 95%+ detection rate)

You don't need perfect bibs in every shot. AI just needs 1-2 clear images per runner to identify them across all photos.

Post-Race Workflow: 12 PM - 6 PM

Race done. Time to deliver. Here's the 6-hour professional workflow.

Step 1: Import RAW to Lightroom (30 minutes)

12:00 PM - Back home/studio

Lightroom import:

1. Insert memory cards (all 4 cards)

2. File → Import Photos

3. Import settings:

   • Copy (don't move)
   • Destination: /External_SSD/2025-12-15_City_Marathon/RAW/
   • Build previews: "Minimal" (faster)
   • Apply preset: "Camera Calibration + Copyright"

4. Add to collections by shooting location:

   • DNG_0001-0300 → "1_Start_Line"
   • DNG_0301-0800 → "2_Mile_5"
   • DNG_0801-1600 → "3_Mile_13_Halfway"
   • ... etc.

Result: 3,500 RAW files imported, organized by location

Time: 25-30 minutes (depending on card speed)

RAW files imported and organized by shooting location

Step 2: Quick Cull Bad Shots (20 minutes)

12:30 PM - Remove obvious failures before AI processing

Survey view quick pass:

• Delete: Out of focus (eye AF failed)
• Delete: Severe overexposure (blown highlights)
• Delete: Accidental ground/sky shots
• Keep: Borderline shots (AI might find good bibs)

Filter criteria:

• Focus quality: Keep 90%+ photos
• Exposure: Keep if recoverable in RAW
• Framing: Keep unless completely unusable

Result: 3,200 photos remain (removed 300 duds)

Why cull?

• Faster AI processing
• Cleaner final galleries
• Less storage waste

Time: 15-20 minutes (quick pass only, not star-rating yet)

Step 3: Export JPG Previews for AI Detection (15 minutes)

12:50 PM - Prepare files for RaceTagger

Lightroom export:

1. Select all 3,200 photos
2. File → Export
3. Export to: /External_SSD/2025-12-15_City_Marathon/AI_Processing/
4. Settings:
   • Format: JPEG, Quality 80, sRGB
   • Resize: Long edge 2048px (faster AI, good accuracy)
   • Metadata: Copyright only
   • Sharpening: Standard, screen

Click Export → Walk away 10-12 minutes

Why 2048px?

• AI bib detection accuracy: 95% (same as full-res)
• Processing speed: 3-4× faster
• Disk space: 80% smaller

Exporting 2048px JPGs for fast AI bib detection

Step 4: AI Bib Detection in RaceTagger (45 minutes)

1:05 PM - Let AI do the heavy lifting

RaceTagger workflow:

1. Launch RaceTagger

2. Create project: "City Marathon 2025-12-15"

3. Import photos: Select /AI_Processing/ folder (3,200 JPGs)

4. Import participant CSV:

   • File → Import Participant List
   • Select 2025-12-15_City_Marathon_Participants.csv
   • 1,247 runners loaded

5. Start AI detection: Click "Detect Bib Numbers"

   • Processing time: 35-40 minutes for 3,200 photos
   • Walk away! AI works automatically
   • Make lunch, answer emails, stretch after 7-hour shoot

What AI does:

• Scans every photo for bib numbers
• Detects numbers even with:
  • Partial occlusion (arms, gear, other runners)
  • Side angles
  • Varying distances
  • Motion blur (within reason)
  • Shadows, bright sun

Expected accuracy:

• Finish line (frontal): 96-98%
• Mid-race (varied angles): 88-92%
• Start line (crowd): 85-90%
• Overall average: 90-93%

Step 5: Review Uncertain Detections (20 minutes)

1:50 PM - Human review for edge cases

RaceTagger review mode:

1. Filter: "AI Confidence < 90%"

   • Shows ~250-400 photos (8-12% of total)
   • AI flagged these as uncertain

2. Quick verification:

   • Bib number correct? → Confirm ✓
   • Bib number wrong? → Type correct number
   • No visible bib? → Tag as "Spectator" or "Unidentified"
   • Multiple runners? → Tag as "Group Shot"

Speed: 3-5 seconds per uncertain photo

Common edge cases:

• Bib obscured by timing chip, belt, gear
• Side/back angle (number not visible)
• Extreme distance (small bib in frame)
• Multiple runners overlapping

Result: 3,200 photos tagged with 90-95% automation, verified by human

Time: 18-22 minutes

Quick review of uncertain AI detections - confirm or correct

Step 6: Auto-Match Participants (Instant)

2:10 PM - The magic moment

RaceTagger auto-matching:

Detected bib #523 → Participant CSV lookup → Match found:

• Name: Jessica Martinez
• Bib: 523
• Age category: Female 30-34
• Team: Boston Athletic Club
• Email: jmartinez@email.com (for notifications)

Applied to all 28 photos of Jessica across 5 shooting locations.

This happens in under 2 minutes for all 3,200 photos.

Before AI: Type "Jessica Martinez" manually into 28 photos After AI: Automatically matched, zero typing

Multiply by 1,247 runners: Hours saved.

Step 7: Export Metadata (XMP Sidecars) (5 minutes)

2:12 PM - Sync tags back to Lightroom

RaceTagger export:

1. File → Export Metadata
2. Format: XMP Sidecar files
3. Location: /AI_Processing/ (same as JPGs)
4. Click Export

Result: .xmp files created next to each JPG

/AI_Processing/
  ├── DNG_0001.jpg
  ├── DNG_0001.xmp  ← Metadata
  ├── DNG_0002.jpg
  ├── DNG_0002.xmp

Copy XMP files to RAW folder:

1. Copy all .xmp files
2. Paste into /RAW/ folder
3. Rename to match RAW extensions:
   • DNG_0001.xmp → DNG_0001.NEF.xmp (Nikon)
   • Or DNG_0001.CR3.xmp (Canon)

Back in Lightroom:

• Metadata → Read Metadata from Files
• All tags now synced to RAW catalog

Time: 4-6 minutes

Step 8: Edit in Lightroom (2-3 hours)

2:17 PM - Professional editing begins

Now you can filter and edit by participant:

Example workflow for Jessica Martinez:

1. Filter: Keyword "Jessica Martinez" → See her 28 photos

2. Star-rate selects: 5★ for best 3-4 shots

3. Batch edit:

   • Select all 28 photos
   • Apply preset: "Marathon Warm Natural"
   • Adjust: Exposure +0.3, Highlights -15, Shadows +20
   • Sync settings to all

4. Individual edits on 5★ photos:

   • Crop to rule of thirds
   • Straighten horizon
   • Spot removal (dirt, sensor spots)
   • Vignette for focus

Repeat for key participants (top finishers, client VIPs)

Batch edit remaining photos:

• Select by location collection
• Apply location-specific presets:
  • "Mile 5 Morning Light"
  • "Finish Line Dynamic"

Time: 2-3 hours for 3,200 photos

• 5★ selects: 45-60 min (300-400 photos)
• Batch edits: 90-120 min (2,800 photos)

Filtering by participant keywords - all photos pre-tagged by AI

Step 9: Export Final Galleries (30 minutes)

4:30 PM - Prepare for delivery

Lightroom export settings:

1. Select all edited photos (3,200)

2. File → Export

3. Export location:

   /Finals/2025-12-15_City_Marathon_Finals/
   

4. File settings:

   • Format: JPEG
   • Quality: 90 (high quality for printing)
   • Color space: sRGB
   • Resize: Long edge 4000px (full-res for clients)

5. Metadata:

   • ☑ Include all metadata (keywords, participant info)
   • ☑ Copyright watermark (text overlay, bottom right)

6. Output sharpening: High, glossy paper

Export time: 25-30 minutes for 3,200 high-res JPGs

Result: Final galleries with embedded metadata:

• Participant names
• Bib numbers
• Categories
• Teams
• Copyright info

Step 10: Upload to SmugMug (30 minutes)

5:00 PM - Client delivery platform

SmugMug gallery setup:

1. Create gallery: "City Marathon 2025 - December 15"

2. Upload finals: /Finals/ folder (3,200 photos)

3. SmugMug auto-organizes by metadata:

   • Searchable by participant name
   • Filterable by bib number
   • Grouped by category (Male 30-34, Female 40-44, etc.)

4. Gallery settings:

   • Privacy: Unlisted (link-only access)
   • Downloads: Enabled for purchased photos
   • Pricing: Set print/digital prices

5. Send participant notifications:

   • SmugMug bulk email tool
   • Template: "Your marathon photos are ready! Search by name or bib #[LINK]"
   • 1,247 emails sent automatically

Upload time: 25-30 minutes (depending on internet speed)

Pro tip: Upload starts at 5 PM. Go make dinner. Check at 5:30 PM. Done.

Final SmugMug gallery - searchable by participant name and bib

Complete Workflow: Time Breakdown

Gallery live by 5:45 PM Sunday. Marathon was Sunday morning. Client ecstatic.

What If You Did This Manually?

Traditional workflow without AI:

AI workflow: 5 hours 45 minutes Manual workflow: 11 hours 30 minutes Time saved: 5 hours 45 minutes (50% faster)

If you're billing time:

• 5.75 hours @ $75/hour = $431.25 saved
• Or reinvest that time in shooting another event

Advanced Tips for Marathon Shooters

For Ultra-Fast Turnaround (Same-Day Delivery)

Goal: Gallery live by 6 PM race day (faster than competitors)

Optimizations:

1. Bring laptop to race: Import + AI detection during finish line shooting
2. Pre-load CSV: Have participant list ready Friday
3. Skip full edit: Batch preset only, minimal individual edits
4. Upload from venue: Mobile hotspot or coffee shop WiFi

Fastest possible: 3-4 hours post-race

For Multi-Day Events (Boston Marathon, New York Marathon)

Strategy:

• Day 1 (Saturday): Elite race + expo (1,000 photos)
• Day 2 (Sunday): Main marathon (3,500 photos)

Process Saturday photos Saturday night:

• Deliver elite/VIP galleries immediately
• Build momentum, social media buzz

Process Sunday photos Sunday evening:

• Main participant galleries live by Monday 8 AM

For High-Volume Shooters (10,000+ photos)

Challenge: Marathon + half-marathon same day

Solution:

1. Dual-process: Run AI detection on both events simultaneously
2. Outsource editing: Hire editor for batch color grading
3. You focus on: Review, quality control, client communication

Common Marathon Photography Questions

Q: What if runner has no bib visible in any photo? A: Tag as "Unidentified" collection. Some runners cover bibs, wear jackets. Can't tag everyone.

Q: Should I shoot finish line only (guaranteed clear bibs)? A: No. Variety sells. Course coverage shows journey. Finish + 2-3 course positions = best value.

Q: How to handle rain/mud obscuring bibs? A: AI still detects 70-80% (impressive). Manual review takes longer but still faster than full manual tagging.

Q: Can I deliver galleries before editing? A: Yes! Some photographers offer "same-day proofs" (AI-tagged, basic export) then "edited finals" 48 hours later.

Q: What's the minimum photos per runner for good coverage? A: Industry standard: 3-5 photos per participant. One clear bib shot + variety.

Pricing Your Marathon Photography

What to charge based on effort:

Package example (City Marathon, 1,200 runners):

• Client (race organizer): $2,500 flat fee
• Participant sales: $15/digital, $25/print (avg $18/runner)
  • 30% conversion rate: 360 sales × $18 = $6,480
• Total revenue: $8,980

Your costs:

• Shooting: 7 hours @ $75/hr = $525
• Editing: 5.75 hours @ $75/hr = $431
• Software (RaceTagger + Lightroom): $35/month
• SmugMug: $300/year ($25/month)
• Total costs: $1,016

Profit: $7,964 per marathon

If you shoot 12 marathons/year: $95,568 revenue

Bottom Line

Marathon photography is demanding:

• 5 AM wakeup
• 7 hours of shooting
• 26.2 miles of coverage
• 3,500 photos to organize and deliver

Without AI: 11+ hours of post-processing. Gallery delivered Wednesday.

With AI workflow: 5.75 hours post-processing. Gallery delivered Sunday evening.

The difference? You get your Monday back. You can shoot more events. You deliver faster than competitors.

Marathon photography should be about capturing 26.2 miles of human determination - not spending 11 hours typing bib numbers into keywords.

Shooting your next marathon? Start your RaceTagger free trial and deliver galleries the same day.