Why Plus-Minus Is Broken: The Real Metric That Predicts NBA Success

The Myth of Simple Plus-Minus

Let’s be real: if your favorite player has a +12 in a game, does that mean they’re a superstar? Probably not. That number’s been cooked by teammates, opponents, and even the coach’s lineup shuffle. In my years analyzing NBA data at a sports tech startup, I’ve seen too many good players get buried under flawed metrics.

Plus-minus looks simple—how many points your team outscored opponents when they were on the floor—but here’s the twist: it rewards luck as much as skill. If your point guard is playing with Steph Curry and Klay Thompson? You’ll look better than you are. If you’re stuck with bench players? You’ll suffer—even if you’re doing everything right.

Enter BPM: The Truth Serum for Player Value

That’s where BPM comes in—Box Plus/Minus. This isn’t just another stat; it’s a regression model built from 30+ years of NBA data that strips away noise.

BPM measures how much each player contributes per 100 possessions relative to the league average. A +5.0 means you’re helping your team win 5 more points every 100 plays than an average player would. A +10? That’s elite—think Jordan-level impact.

It doesn’t care if you played with Harden or D’Angelo Russell. It doesn’t care about pace or team strength—it normalizes everything.

How Does It Actually Work?

Think of it like this: every action has value.

• 1 assist ≈ +0.5 net points (because someone else scores)
• 1 offensive rebound ≈ +0.4 (you keep possession)
• 1 turnover ≈ -0.7 (you handed them free offense)

These weights aren’t guesses—they come from actual historical patterns that show what wins games.

Then we adjust for context:

• Fast-paced teams like Golden State get scaled down because they play more possessions.
• Players on bad teams get boosted slightly—because it takes more effort to win when no one else can score.

This is why guys like Jalen Brunson or Chris Paul often have higher BPMs than expected—they don’t need star power to carry their teams; they just do it consistently.

Why This Matters Beyond Stats

I grew up watching kids in Chicago playgrounds work harder than anyone in practice—but never get scouted because their high school didn’t have an elite program. Sounds familiar? The same thing happens in basketball analytics: systems favor those with flashy numbers on inflated rosters. But BPM? It levels the field. It gives credit where it’s due—even to role players who clean up the glass or lock down guards without stealing headlines.

And here’s my hot take: If we want real equity in talent evaluation—the kind that helps overlooked athletes rise—we need to stop trusting raw plus-minus and start trusting models like BPM.

Final Word: Metrics Should Serve People, Not Just Numbers

You don’t need a PhD to understand this stuff—you just need to ask one question:

“Is this measuring what actually matters—or just what looks good on paper?”

So next time someone says ‘he had +22 today,’ hit pause and ask: ‘What was his BPM?’ The answer might surprise you—and maybe finally give justice to the unsung heroes of basketball.