The Donaghy Effect

NBA/WNBA Player Props & Game Analytics

AI-powered betting analytics giving probabilities for player props, team ATS, and O/U to indicate where +EV opportunities are. Our models use historical data vs historical lines and consider referee-specific context (coming soon) to help you find edges. Unlike others we don't do simple hit rates.

Player Prop Analysis

Pascal Siakam

Pascal Siakam

Hawks Hawks @ Pacers Pacers
2025-10-31 23:00:00

Available Props

Game Range

vs Line
+0.0
Average
20.8
Line
26.5
Over/Under
-118/-108
EV
U -2.9%

Expected Value Summary

Prop O/U 5G 10G 20G H2H
Points 26.5 U 13.2% U 2.9% O 4.9% O 12.9%
Rebounds 8.5 O 20.4% O 4.3% U 5.2% U 0.6%
Assists 5.5 O 2.5% O 15.8% O 21.0% U 0.5%
3-Pointers 2.5 O 74.2% O 38.1% O 45.8% O 48.9%
Steals 1.5 O 35.1% O 45.5% O 43.0% O 50.5%
Blocks 0.5 O 26.4% O 64.2% O 21.4% U 4.9%
Double Double +118 Y 7.3% Y 16.7% Y 30.9% N/A
Triple Double +1360 Y 5.6% Y 6.7% Y 6.8% N/A

■ Green indicates positive expected value  |  ■ Red indicates negative expected value

Game Lines Analysis

Hawks Hawks @ Pacers Pacers
2025-10-31 23:00:00

Line Type

Game Range

Scoring
IND: -10.9
ATL: -2.1
Allowing
IND: +0.9
ATL: +2.9
O/U
232.5
Model
228.2
EV
U +14.0%

Analysis Breakdown

  • Home team averaging -10.9 points vs expected in this period
  • Away team averaging -2.1 points vs expected in this period
  • Away defense allowing +2.9 points vs expected
  • Combined O/U record: 7-13 in this period
  • Games averaging -4.6 points vs O/U line
  • Model predicts 228.2 total (line: 232.5)

About The Donaghy Effect

Our models use historical data with referee-specific context to generate probability distributions for each prop. Rather than relying on simple averages or hit rates like other sites, we account for variance in player and team performance, matchup dynamics, and officiating crew tendencies. This approach helps identify when bookmaker lines diverge from actual player and team performance patterns, highlighting where edges and positive expected values are available.

Tools & Features

  • NBA Player Props Tool — Probability distributions, hit-rates, and fair lines for points, rebounds, assists, threes, and more. Compare your projections against book odds.
  • NBA Matchups (ATS & O/U) — Spread and total projections with uncertainty bands. See how referee assignments impact game pace and scoring.
  • +EV Props Finder — Automatically ranks positive expected value opportunities. Filter by confidence level and bet size to match your risk tolerance.
  • +EV Matchups — Daily edges on spreads and totals ranked by expected value. Referee-adjusted predictions for game totals.

Whether you're analyzing player props, looking for ATS value, or hunting for profitable totals, our platform provides the data-driven insights you need. Sign up for free access and start finding edges today.

FAQ: NBA Betting Analytics

How do you calculate expected value (+EV)?

We convert book odds to implied probabilities, compare to our model probability, and compute EV = (probability × win_payout) - ((1-probability) × stake). Positive EV indicates the bet is mathematically profitable long-term.

Do you cover ATS and totals?

Yes. Our matchup pages show ATS (against the spread) and O/U (over/under) probabilities with distribution curves, team context, and referee impact analysis.

How accurate are your player prop predictions?

We use historical data with referee context to model probability distributions. Our approach accounts for variance in player performance and situational factors like matchups and officiating crew tendencies.

What makes referee analysis important for betting?

Different referees have measurably different tendencies in calling fouls, which affects pace of play, free throws, and game totals. Our models incorporate referee assignments into predictions.

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