Maintain peak performance in the final 20 minutes
Copper Queens struggle to close out matches in regulation time, relying on penalty shootouts to advance
EnduranceEdge builds individualized conditioning programs that specifically target the ability to close out matches. Using simple tracking and local environmental data, it predicts fatigue, optimizes substitution timing, and creates nutrition plans using affordable Zambian foods to prevent late-game dropoffs.
Zambian women's national football team coaches, players, and passionate local fans
Built on physiological data from African female athletes and tested in Zambian heat and altitude conditions
encouraging and science-backed
Models player fatigue based on match data and environmental factors
Generates 4-week programs focused exclusively on closing strength
Recommends exact timing for substitutions based on player load
Meal plans using nshima, kapenta and other local affordable foods
Monitors sleep and readiness using simple mobile inputs
Custom pre-game and half-time protocols for closing performance
Connects to affordable GPS watches common in Zambia
Visual overview of squad fatigue levels
Gamified challenges between players and teams
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| role | text | No |
| position | text | Yes |
| team_id | uuid | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| date | timestamp | No |
| focus_area | text | No |
| completed | bool | No |
| perceived_exertion | int | Yes |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| match_id | uuid | No |
| user_id | uuid | No |
| minutes_played | int | No |
| fatigue_score | int | No |
| temperature | int | Yes |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| type | text | No |
| content | text | No |
| created_at | timestamp | No |
Relationships:
/api/training/generateCreate personalized training plan
/api/fatigue/predictRun fatigue prediction model
/api/substitutions/optimizeCalculate optimal substitution windows
/api/nutrition/planGet localized nutrition recommendations
Limited recommendations per week
None
Up to 25 players
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 180 | 9% | $405 | $4,860 |
| Month 6 | 950 | 15% | $3,562 | $42,750 |
Conditioning intelligence built for Zambian women's football to maintain intensity until the final whistle.
1. Partner with the Copper Queens physiotherapist for a pilot with the senior and U-20 teams. 2. Offer free 90-day access to top women's clubs in the FAZ Women’s League in exchange for usage data. 3. Run conditioning workshops at community pitches in Lusaka, demonstrating the app with local athletes to generate organic adoption.
Strong team training management
Generic programs, not tailored to African conditions or women's physiology
Hyper-specific to closing out regulation time in hot climates
Excellent recovery metrics
Hardware too expensive for Zambian market
Works with basic phones and local context
Unique dataset of fatigue patterns from Zambian women's matches in local conditions creates superior prediction models competitors cannot replicate quickly.
Recent increase in international matches for Copper Queens has highlighted the regulation-time fitness gap. Low-cost smartphones are ubiquitous while simple AI models can now run effectively on-device.
Players may not consistently log data
Make logging extremely simple with one-tap options and coach accountability features
Accuracy of fatigue predictions without expensive sensors
Use hybrid approach combining subjective feedback with basic movement data
Success: 80% correlation between app prediction and coach observation
Success: measurable improvement in second half performance
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