Another poor performance by the model this past week. Based primarily on team and player past performance numbers, the model couldn’t project the radical and strange drop-offs in production we’ve seen from some teams (like Boston), nor the inexplicable production increases in other teams. Poor coaching, especially in rotation adjustments and 4th quarter time mismanagement, along with telling inexperience, also accounts for some of it. Late sitting (or returning) of key players (especially by Cleveland) and game-changing injuries have also played a part. Excuses. Excuses. Excuses.
The bottom line, simply stated, is that mere numbers (which is all the model has to work with) haven’t been reliable as accurate projectors of performance thus far in these playoffs. That said, numbers have a way of righting themselves; and hopefully will. GLTA
FWIW – The model’s projected total scores are hitting Over/Under plays at a 58.5% rate. Although the model’s not designed for this, I’ve been using it, going 8-3. and won $ doing so, and putting me a smidgin ahead for the past week.
The bottom line, simply stated, is that mere numbers (which is all the model has to work with) haven’t been reliable as accurate projectors of performance thus far in these playoffs. That said, numbers have a way of righting themselves; and hopefully will. GLTA
FWIW – The model’s projected total scores are hitting Over/Under plays at a 58.5% rate. Although the model’s not designed for this, I’ve been using it, going 8-3. and won $ doing so, and putting me a smidgin ahead for the past week.
