dfsforge / NBA forecasts / Jaxson Hayes rebounds

Jaxson Hayes: reboundsFITTED MODEL

C · LAL · NBA · baseline 4.1/game (2026, 81 games)
3.5
Median
0.7-8.4
80% range
1.8-5.9
50% range
9.9
Ceiling (p95)

Outcome distribution

0.73.58.4
Shaded: the 80% range. Dashed lines: p10 / median / p90.

Chance of reaching

reboundsProbability
2.0+72%
4.0+43%
6.0+24%
8.0+12%
Model receipt: on the held-out season, across 4136 C rebounds games, our 80% range covered 81.7% of actual outcomes (target 80%).
Baseline is the 2026 per-game average; the distribution shape is learned per position and per production level from historical game logs. When the weekly slate model is live the baseline switches to the weekly line.
More: Jaxson Hayes player page · all NBA forecasts
Forecasts are probability distributions from dfsforge's variance model, fitted on historical game logs and validated on a held-out season - the coverage number printed above is that holdout result, not a training-set fit. Research output, not advice. Open the app · Accuracy receipts