Minnesota Timberwolves at Milwaukee Bucks, NBA forecast
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Win probability
Starts from the pregame forecast, then moves with every score and the time left. Above the line favors MIL; hover for each play.
Game center
From the ESPN box score.
Top performers
Timberwolves- Julius RandlePoints29
- Donte DiVincenzoAssists7
- Julius RandleRebounds8
Bucks- Giannis AntetokounmpoPoints25
- Kevin Porter Jr.Assists8
- Giannis AntetokounmpoRebounds8
Last plays
- Q40.0End of Game139–106
- Q40.0End of the 4th Quarter139–106
- Q40.1Timberwolves offensive team rebound139–106
- Q40.5Rob Dillingham misses two point shot139–106
- Q411.5Amir Coffey makes 25-foot three point jumper (Andre Jackson Jr. assists)139–106
- Q426.9Leonard Miller lost ball turnover (Cole Anthony steals)139–103
- Q437.6Amir Coffey makes free throw 1 of 1139–103
- Q437.6Rob Dillingham shooting foul139–102
- Q437.6Amir Coffey makes layup (Pete Nance assists)139–102
- Q446.1Leonard Miller makes 1-foot running dunk (Joe Ingles assists)139–100
Turning points
The 5 plays that swung the win chance most, each judged at its own moment: the chance with the score just before it against just after.
- Q111:44Julius Randle makes 26-foot three point jumper (Naz Reid assists)MIN 3 – 0 MIL · MIN 46% → 52% +6MIN 46% → 52%+6 pts
- Q18:37Donte DiVincenzo makes 25-foot three pointer (Julius Randle assists)MIN 8 – 2 MIL · MIN 52% → 59% +6MIN 52% → 59%+6 pts
- Q16:44Julius Randle makes 27-foot three point jumper (Jaden McDaniels assists)MIN 15 – 6 MIL · MIN 59% → 65% +6MIN 59% → 65%+6 pts
- Q15:34Ryan Rollins makes 23-foot three point jumper (AJ Green assists)MIN 18 – 11 MIL · MIL 32% → 39% +6MIL 32% → 39%+6 pts
- Q13:21Bones Hyland makes 22-foot three point jumper (Jaden McDaniels assists)MIN 25 – 15 MIL · MIN 62% → 68% +6MIN 62% → 68%+6 pts
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Bucks 54%
Forecast Elo ratings alone
How often that comes true: NBA favorites the forecast gave 50–55% have won 49.4% of 342 graded games.
- Market
- MIL -1.5
- ML MIN +110 / MIL -130
- Pre-line forecast
- MIL 48%
- Elo + market-implied
- Elo ratings
- MIN -0.5
- MIL 48%
- Ratings vs. market
- −6.2 pts
- MIL: Elo 48.0%, market 54.3%
- Fair odds
- MIL -119
- MIN +119 · the forecast as odds, no margin
- Pregame projection
- MIN 114.0 – 115.5 MIL
- Posted spread, posted total 229.5
How the number is built
Elo inputs in rating points (higher favors that team; 25–28 Elo is about a point of spread in football and basketball), then how the pieces combine.
| Factor | MIN | MIL | Why |
|---|---|---|---|
| Team rating | 1604 | 1473 | Elo entering the game; 1500 is league average |
| Home field | — | +36 | Worth 36 Elo in the NBA |
| Lineups | −67 | +26 | MIN: Missing Rudy Gobert −28 · otherwise weaker than recent lineups · MIL: Stronger than its recent lineups (from the box score) |
| Travel | — | −12 | MIL crossed 1 time zone heading east to this game: 12 Elo per zone for body-clock lag |
| Elo ratings | MIN +14 Elo | MIN 52.0% | |
| Market-implied ratings | MIN 51.7% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | MIN 51.7% | 10% Elo, 90% market-implied (log-odds blend) | |
| Forecast | MIL 54.3% | Follows the market (vig removed): in testing, adding the ratings made it less accurate | |
Tale of the tape
This season coming into the game, regular season, each number with its league rank (the longer the bar, the higher). Home and road: the host's record at home against the visitor's on the road. Opponent Elo: how strong the teams each has played are, 1st the toughest. Offense and defense are points per 100 possessions, which sets aside how fast a team plays.
| MIN | Stat | MIL |
|---|---|---|
| 3rd of 30119.9 | Points scored | 112.925th of 30 |
| 11th of 30114.8 | Points allowed | 115.114th of 30 |
| 6th of 30+5.1 | Margin | −2.221st of 30 |
| 6th of 30116.0 | Offense rating | 112.419th of 30 |
| 9th of 30111.1 | Defense rating | 114.619th of 30 |
| 12th of 30102.5 | Pace | 99.926th of 30 |
| 5th of 306–4 | Last 10 | 6–45th of 30 |
| 8th of 3011–8 | Road vs home | 9–920th of 30 |
| 20th of 301491 | Opponent Elo | 148428th of 30 |
| 5th of 301604 | Elo rating | 147319th of 30 |
Who's playing
Who sat out, from the box score, and what each absence cost against the lineups the team had been playing.
Timberwolves
−67 Elo- Rudy Gobert suspended by league−28 Elo
Bucks
+26 EloFull strength: nobody who matters sat out.
Rating history
Each team's Elo over the last two seasons. Hover or drag to compare on any date.
Recent form
Last five results, and whether the forecast hit.
Against the line
How each team has done against the closing spread and total, coming into this game.
| This season |  MIN |  MIL |
|---|---|---|
| Against the spread | 17–23 | 18–21 |
| Last 10 | 5–5 | 5–5 |
| Favorite | 14–19 | 7–11 |
| Underdog | 3–4 | 11–10 |
| Overs–unders | 19–21 | 16–23 |
| Overs–unders, last 10 | 6–4 | 4–6 |
Against each game's closing line. Books set every line knowing these records: across 3,901 past games, the team with the better record against the spread so far that season covered 51.2%, short of the 52.4% a standard −110 bet needs, and over/under streaks held 48.0% of the time. They describe the past.
Head to head
MIN 2–3 MIL in their last 5 meetings; the forecast called 2 of 5.