# Testing Your Apify Actor
## 🧪 Quick Test Guide
Your Actor is deployed! Let's verify it works correctly.
---
## Method 1: Web Console Test (Easiest)
### Step 1: Open Actor Console
```
https://console.apify.com/actors/OdaJN92JUkidz02uv
```
### Step 2: Click "Try it" or "Start"
### Step 3: Use This Input
```json
{
"mode": "batch",
"tool": "get_player_projections",
"arguments": {
"sport": "NBA",
"slate": "main"
}
}
```
### Step 4: Click "Start"
### Step 5: Wait for Results
- Status should change to "RUNNING" → "SUCCEEDED"
- Time: 10-30 seconds
- Check the "Dataset" tab for results
### Expected Output
```json
{
"sport": "NBA",
"slate": "main",
"date": "2025-11-23...",
"projections": [
{
"playerName": "Player Name",
"team": "TEAM",
"position": "PG",
"salary": 9500,
"projectedPoints": 45.2,
"floor": 36.2,
"ceiling": 54.2,
"value": 4.76,
"ownership": 15.3,
"confidence": 0.9
}
// ... more players
]
}
```
---
## Method 2: Command Line Test
### Using the Test Script
```bash
cd /home/roizen/projects/sportintel-mcp
./test-actor.sh
```
This will:
1. Test player projections
2. Test live odds
3. Show results in terminal
---
## Method 3: Apify CLI Test
### Single Test
```bash
apify call OdaJN92JUkidz02uv --input '{
"mode": "batch",
"tool": "get_player_projections",
"arguments": {"sport": "NBA"}
}' --wait-for-finish
```
### View Last Run
```bash
apify runs ls --actor OdaJN92JUkidz02uv
```
---
## 🎯 Test All 4 Tools
### Test 1: Player Projections ✅
```json
{
"mode": "batch",
"tool": "get_player_projections",
"arguments": {
"sport": "NBA",
"slate": "main",
"minSalary": 5000,
"maxSalary": 12000
}
}
```
**Expected**: 100+ players with salaries $5K-$12K
### Test 2: Lineup Optimizer ✅
```json
{
"mode": "batch",
"tool": "optimize_lineup",
"arguments": {
"sport": "NBA",
"projections": [],
"strategy": "tournament",
"lineupCount": 5
}
}
```
**Note**: You'll need to provide projections from Test 1
**Expected**: 5 optimized lineups
### Test 3: Live Odds ✅
```json
{
"mode": "batch",
"tool": "get_live_odds",
"arguments": {
"sport": "NBA",
"markets": ["spreads", "totals"]
}
}
```
**Expected**: Current NBA game odds from multiple books
**Note**: Requires ODDS_API_KEY environment variable
### Test 4: Explain Recommendation ✅
```json
{
"mode": "batch",
"tool": "explain_recommendation",
"arguments": {
"playerName": "LeBron James",
"method": "shap"
}
}
```
**Expected**: SHAP explanation for the player
---
## ✅ Success Criteria
Your Actor is working if:
- [ ] Status shows "SUCCEEDED" (not FAILED)
- [ ] Run completes in <60 seconds
- [ ] Dataset contains data (not empty)
- [ ] No error messages in logs
- [ ] Player count > 50 (for NBA projections)
- [ ] Salaries are realistic ($3K-$12K range)
---
## ❌ Troubleshooting
### Issue: Actor FAILED
**Check:**
1. View logs in "Log" tab
2. Look for error messages
3. Common issues:
- API rate limits (wait 1 minute)
- No games today (try different date)
- Missing environment variables
### Issue: Empty Dataset
**Causes:**
- No NBA games scheduled today
- API returned no data
- Filters too restrictive (minSalary too high)
**Solution:**
- Remove salary filters
- Check if there are games today
- Try different date parameter
### Issue: Mock Salaries Returned
**Explanation:**
- If real APIs fail, system falls back to mock data
- Mock salaries are estimates, not real
**How to Tell:**
- Only 10-20 players instead of 200+
- Same salaries every time
- Players like "LeBron James" = $9500 always
**Fix:**
- Set `ROTOGRINDERS_API_KEY` environment variable
- Or wait for DraftKings API (no key needed)
---
## 📊 Performance Benchmarks
### Normal Performance
| Metric | Expected | Actual |
|--------|----------|--------|
| Cold start | 5-10 sec | ? |
| Run time (projections) | 10-30 sec | ? |
| Players returned | 150-250 | ? |
| Memory usage | <512 MB | ? |
| Success rate | >95% | ? |
### Fill in "Actual" after testing!
---
## 🎬 Record Your Test
**For Apify Store submission**, you'll want:
1. **Screenshot of Input**
- Show the configuration form
- Highlight the 4 tools
2. **Screenshot of Running**
- Show status = "RUNNING"
- Show progress
3. **Screenshot of Results**
- Show Dataset with players
- Highlight key fields
4. **Screenshot of Success**
- Show status = "SUCCEEDED"
- Show run duration
---
## 📝 Test Report Template
After testing, fill this out:
```
Test Date: _______________
Tester: _______________
Test 1: Player Projections
- Status: SUCCEEDED / FAILED
- Duration: ___ seconds
- Players returned: ___
- Issues: _______________
Test 2: Lineup Optimizer
- Status: SUCCEEDED / FAILED
- Duration: ___ seconds
- Lineups generated: ___
- Issues: _______________
Test 3: Live Odds
- Status: SUCCEEDED / FAILED
- Duration: ___ seconds
- Games found: ___
- Issues: _______________
Test 4: Explain Recommendation
- Status: SUCCEEDED / FAILED
- Duration: ___ seconds
- Explanation quality: ___
- Issues: _______________
Overall Assessment: PASS / FAIL
Ready for Store: YES / NO
Notes:
_______________
_______________
```
---
## 🚀 Next Steps After Testing
If all tests pass:
1. ✅ Mark "Test Actor" as complete
2. ✅ Create visual assets (screenshots from tests!)
3. ✅ Submit to Apify Store
4. ✅ Configure pricing
5. ✅ Monitor first users
If tests fail:
1. ❌ Review logs
2. ❌ Fix issues
3. ❌ Re-deploy (`apify push`)
4. ❌ Test again
---
## 📞 Need Help?
**Can't get it to work?**
1. Check logs in Apify Console
2. Review `APIFY_DEPLOYED.md` for config
3. Ask in Apify Discord
4. Open GitHub issue
**Actor works but want to improve?**
1. Review `PHASE2_COMPLETED.md` for enhancements
2. See `APIFY_STORE_SUBMISSION.md` for next steps
3. Check todo list for remaining features
---
**Ready to test?** → https://console.apify.com/actors/OdaJN92JUkidz02uv
**Good luck!** 🎉
