Backtest Results - Sunday, March 1, 2026
SPREAD PICKS SCORECARD
| Pick |
Result |
Outcome |
| IND +1.5 |
Grizzlies 125 - Pacers 106 |
Failed to cover by 17.5 |
| TBD |
Could not match team: TBD |
NO_RESULT |
| TBD |
Could not match team: TBD |
NO_RESULT |
Spread Record: 0-1 (-1.1u)
OVER/UNDER PICKS SCORECARD
| Pick |
Result |
Outcome |
| MEM @ IND UNDER 237.5 |
Grizzlies 125 - Pacers 106 (Total: 231) |
Under by 6.5 |
| TBD UNDER 0 |
Game result not found |
NO_RESULT |
| TBD UNDER 0 |
Game result not found |
NO_RESULT |
O/U Record: 1-0 (+1.0u)
PARLAY RESULT
| Leg |
Pick |
Outcome |
| 1 |
Indiana Pacers +1.5 |
UNMATCHED |
| 2 |
MEM @ IND UNDER 237.5 |
WIN |
Parlay Result: LOSS (-0.5u)
DAILY SUMMARY
| Category |
Record |
Units |
| Spreads |
0-1 |
-1.1 |
| Over/Under |
1-0 |
+1.0 |
| Parlay |
LOSS |
-0.5 |
| Daily Total |
|
-0.6 |
QUALITATIVE ANALYSIS
WHAT WORKED
- UNDER 237.5 in MEM @ IND hit cleanly - Model correctly identified that heavy injuries to both teams would slow pace and reduce scoring efficiency
- Injury impact assessment was directionally correct - Both teams were severely depleted, leading to lower-quality offensive execution as predicted
WHAT MISSED
- Massive spread miscalculation on IND +1.5 - Model predicted Pacers favored by 7+ points, but Memphis won by 19. This suggests the injury adjustment methodology is fundamentally flawed
- Overcompensated for Indiana's injuries - Despite losing Siakam and Haliburton, the Pacers were still competitive recently. Model failed to account for roster depth and coaching adjustments
MODEL CALIBRATION NOTES
- Insufficient sample to assess confidence calibration - Only one complete game analyzed with actual spread/total bets
- Injury adjustment cap appears too conservative - Memphis missing 4 rotation players should have been weighted more heavily than the 7-point maximum
METHODOLOGY ADJUSTMENTS TO CONSIDER
- Revise injury impact calculations - Current system treats all Tier 1 injuries equally at +5 points, but context matters (team depth, recent performance without player, position replaceability)
- Implement injury interaction effects - When multiple key players are out, the impact isn't additive - it compounds exponentially. Current 1.15x multiplier for two Tier 1 players is insufficient
The core issue: Model correctly identified injury-heavy games would be lower-scoring but completely botched the relative strength assessment between two depleted rosters.
CUMULATIVE SEASON RECORD
| Category |
Record |
Win % |
Units |
| ATS |
41-38 |
51.9% |
-1.4 |
| O/U |
43-42 |
50.6% |
|
| Parlays |
6-26 |
|
|
| Season Total |
|
|
-1.4u |
View original analysis