The Donaghy Effect
NBA Betting Analytics: Player Props, ATS, O/U, and $Line with Referee Impact
Predictive modeling that finds true betting edges. We don't rely on simple hit rates like other sites—our advanced analytics generate probability distributions that account for game context, referee tendencies, and performance variance. By analyzing what Vegas actually priced into historical lines, we identify when today's markets present exploitable expected value opportunities.
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How Our Analysis Works
We evaluate player props using two complementary methods designed to reveal true performance patterns and identify mispriced betting lines.
vs Historical Line
We compare a player's past results to the actual Vegas line set for each specific game. Because those historical lines already accounted for opponent strength, injuries, pace, and matchup context, this analysis provides a context-adjusted view of how the player performed relative to market expectations. This helps bettors understand whether a player consistently exceeds or falls short of the line once matchup factors are properly priced in.
vs Current Line
We also model the player's recent production directly against today's betting line. This isolates current trends in form, usage, minutes, and role—independent of opponent adjustments—making it easier to see whether the player's recent performance supports value on the current market number.
By combining both perspectives, our system highlights when today's line may be mispriced, whether value exists on the over or under, and how historical expectations align with real-time player trends. This dual-layer analysis gives bettors a more accurate, data-driven view of expected value than simple hit rates or raw averages.
Immanuel Quickley
Raptors @ Knicks
*Stats and charts do not include overtime games because they inflate statistics and predictions
Expected Value Summary
vs Historical Lines
■ Green indicates positive expected value | ■ Red indicates negative expected value
vs Current Line
Against the Spread (ATS)
ATS Betting Edge: Our model evaluates the statistical likelihood of each team covering the spread based on their previous performance against historical Vegas lines. But we don't stop there—we also factor in the assigned referees for each game and how their tendencies impact the prediction. Certain officials consistently call tighter games with more fouls, keeping contests closer than talent suggests and helping underdogs cover. Others allow physical play that lets superior teams dominate, favoring favorites to cover. By combining team performance data with referee impact analysis, we identify when today's lines fail to account for officiating crew assignments, revealing situations where the betting market has mispriced the true probability of covering the spread.
Rockets
@
Jazz
ATS Game Analysis
Coming Soon
ATS performance chart will be available in the next update
Referee Impact on ATS
Assigned officials for this game and their ATS tendencies
Coming Soon
Referee impact visualization will be available in the next update
ATS Summary
Coming Soon
Team ATS records (5G, 10G, 20G, H2H), model prediction, and EV analysis will be available in the next update
Over/Under
Referee Impact on Over/Under
Historical performance against over/under lines (excluding overtime games)
Understanding O/U Data: This visualization ranks NBA teams and referees by their historical impact on game totals. A positive value means games tend to go over the Vegas line, while negative values indicate under trends.
O/U Game Analysis
Game Total Analysis: These charts display how Jazz and Rockets have performed in recent games relative to Vegas expectations. The bar charts show scoring and defensive trends, while the probability distribution indicates likely total ranges. Our model projects 235.8 points compared to the 232.5 line.
Analysis Breakdown
- Home team averaging -4.8 points vs expected in this period
- Away team averaging +5.8 points vs expected in this period
- Home defense allowing +13.6 points vs expected
- Away defense allowing -10.8 points vs expected
- Combined O/U record: 11-8 in this period
- Model predicts 235.8 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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