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Last season (2025-26)

What changed?

Players whose game really moved: more minutes, a bigger role, a new shot diet. Each change comes with the likely reason and how much of it should hold.

The 2026-27 season does not have enough games yet, so this shows 2025-26: each player's last 25 games (or his games since a role change or a trade) against the rest of his season. Once players have about 20 games this season, the page switches to this season by itself.

Biggest real changes

279 of 393 players flagged

Showing 9 changes, biggest first (size after the "is it real?" pull). Clear filters

Collin Murray-BoylesF · TORProbably real
3-point rate-14 pts

34 games since Dec 20 vs the 23 games before

Murray-Boyles's 3-point rate is down 14 points over his 34 games since Dec 20 (10% vs 24%). The likely reason: Jakob Poeltl (26 MPG before) played only 26 of 54 games. Probably real: about 65% should hold.

  • Teammate outJakob Poeltl (26 MPG before) played only 26 of 54 games
Gradey DickG · TORProbably real
3-point rate-14 pts

18 games since Mar 3 vs the 58 games before

Dick's 3-point rate is down 14 points over his 18 games since Mar 3 (38% vs 51%). No clear cause shows up in our data; it could be an injury, a coaching choice or the schedule. Probably real: about 60% should hold.

Gradey DickG · TORProbably real
Minutes-7.4

18 games since Mar 3 vs the 58 games before

Dick's playing time is down 7.4 minutes a game over his 18 games since Mar 3 (8.4 vs 15.8). No clear cause shows up in our data; it could be an injury, a coaching choice or the schedule. Probably real: about 70% should hold.

Collin Murray-BoylesF · TORProbably real
Above-the-break 3 share-13 pts

34 games since Dec 20 vs the 23 games before

Murray-Boyles's above-the-break 3 share is down 13 points over his 34 games since Dec 20 (6% vs 19%). The likely reason: Jakob Poeltl (26 MPG before) played only 26 of 54 games. Probably real: about 65% should hold.

  • Teammate outJakob Poeltl (26 MPG before) played only 26 of 54 games
Immanuel QuickleyG · TORPartly real
Points-7.7

8 games since Mar 13 vs the 62 games before

Quickley's scoring is down 7.7 points a game over his 8 games since Mar 13 (9.6 vs 17.3). Much of it is playing time: his minutes went from 32.6 to 27.0 a game. Also shot volume: his shots per 36 minutes (counting free throw trips) went from 16.3 to 13.4. Partly real: about half should hold.

  • MinutesHis minutes went from 32.6 to 27.0 a game (about 39% of the change)
  • Shot volumeHis shots per 36 minutes (counting free throw trips) went from 16.3 to 13.4 (about 33% of the change)
  • EfficiencyHis TS% went from 58.6% to 47.7% (about 28% of the change)
Jamal SheadG · TORProbably real
3-point rate-9 pts

Last 25 games of the season vs the 57 games before

Shead's 3-point rate is down 9 points over his last 25 games of the season (46% vs 54%). No clear cause shows up in our data; it could be an injury, a coaching choice or the schedule. Probably real: about 70% should hold.

Scottie BarnesG-F · TORProbably real
Rebounds-2.9

Last 25 games of the season vs the 55 games before

Barnes's rebounding is down 2.9 rebounds a game over his last 25 games of the season (5.5 vs 8.4). Most of it is per-minute production: his rebounds per 36 minutes went from 8.8 to 6.2. Also playing time: his minutes went from 34.4 to 31.6 a game. Probably real: about 65% should hold.

  • Per-minute rateHis rebounds per 36 minutes went from 8.8 to 6.2 (about 77% of the change)
  • MinutesHis minutes went from 34.4 to 31.6 a game (about 23% of the change)
Gradey DickG · TORPartly real
Corner-3 share-11 pts

18 games since Mar 3 vs the 58 games before

Dick's corner-3 share is down 11 points over his 18 games since Mar 3 (10% vs 21%). No clear cause shows up in our data; it could be an injury, a coaching choice or the schedule. Partly real: about half should hold.

Immanuel QuickleyG · TORPartly real
Minutes-5.6

8 games since Mar 13 vs the 62 games before

Quickley's playing time is down 5.6 minutes a game over his 8 games since Mar 13 (27.0 vs 32.6). No clear cause shows up in our data; it could be an injury, a coaching choice or the schedule. Partly real: about half should hold.

How this works

Windows

Every night we split each player's regular season (8+ games on each side) in one of three ways, in this order: the day he joined a new team; the game after which his minutes and usage shifted the most (a simple two-part split); or, if neither moved much, his last 10 games. Until the new season has enough games (about 20 each for most players) we use last season and its last 25 games, which catches the roles that changed at the trade deadline.

Is it big?

A change counts as big when it reaches:

  • Points: 4 points a game
  • Minutes: 5 minutes a game
  • Usage: 4 points
  • TS%: 4 points
  • 3P%: 5 points
  • 3-point rate: 8 points
  • Rim share: 8 points
  • Midrange share: 8 points
  • Corner-3 share: 8 points
  • Above-the-break 3 share: 8 points
  • Assists: 2 assists a game
  • Rebounds: 2.5 rebounds a game

Players need 15+ minutes a game on one side. Shooting needs 40+ threes or 60+ shots on each side.

Is it real?

Both windows are pulled toward the player's whole season by a fixed amount of weight M, the sample size where a stat is half skill and half luck: (window x n + season x M) / (n + M). A change is shown only if the pulled gap keeps at least half of the raw gap: Probably real keeps 60% or more, Partly real keeps 50 to 59%, anything less is Mostly noise and stays off the feed.

M values: 3P% 501 threes, TS% 218 shots and points 9.7 games, from Is it real?; minutes 9.4, usage 17, assists 18.9, rebounds 18.1, 3-point rate 13.9, rim share 18.2, midrange 16.8, corner 3 21.6 and above the break 15.4 games, measured on 1,766 pairs of back-to-back 10-game stretches in 2025-26. That is why 3P% changes almost never make it: threes are mostly luck until a player has taken hundreds.

Causes

Rules, each with a number. Points split exactly into minutes, shot volume and efficiency. Assists and rebounds split into minutes and per-minute rate. TS% and 3P% split into shot diet (league FG% from the spots he shot from) and shot-making (the rest). Context: a new team, a move into or out of the starting five (starting lineups from our stint data), key teammates (25+ minutes before) who missed most of the window, a new rotation player (20+ minutes), and opponents' defensive rating. We keep causes that explain 15%+ of the change and show the top three.

What we measured

Backtest on 2025-26: we ran this as if the season stopped on 3 dates and checked each flag against the rest of the season. Probably real changes kept 71% of their size on average (we predicted 66%) and 88% kept going the same way (301 flags). Partly real kept 60% (predicted 55%). Mostly noise kept 39% (predicted 33%), so the pull is a little cautious, which is the safe side.

Latest run: 393 players checked, 447 probably real and 180 partly real changes, and 273 big swings left out as mostly noise.

What it cannot see

Injuries a player played through, coaching decisions, matchups and schemes, and anything off the box score. Missing teammates are read from who played, not the injury report. Causes are rough splits, not proof; when nothing in our data fits we say so.