Harvard Crimson vs Brown Bears prediction
Chance to win · 58% and 23% in regulation
All predictions
9 picks graded · Average confidence 62%Full game
- 1X2WonHarvardodds down 1.54Confidence 53%
- Best tip of the game: Over/UnderWonU6.5odds down 1.38Confidence 64%
- HandicapLostBrown +2.51.44Confidence 61%
- Winner (incl. OT)WonHarvardodds up 1.27Confidence 57%
- Double chanceWonHarvard or drawodds down 1.18Confidence 65%
- Draw no betWonHarvardodds down 1.23Confidence 59%
- Both teams to score (GG/NG)WonYes1.12Confidence 81%
1st period
- 1st period 1X2WonHarvard2.01Confidence 51%
- 1st period Over/UnderLostU2.5Confidence 69%
How to read the picks
Confidence is the model’s own score for a pick, out of 100. It is not a probability, but picks with higher confidence have won more often. The score details show the model’s probability instead — they are not picks.
Why some of these picks carry a lower confidence: form from only 1 games.
Predicted final score
What the picks are derived from. Not a bet.Score details
- Correct scoreLost3–1After 60 min4–14%chance
- 1st period correct scoreLost1–01st period3–020%chance
- Highest scoring periodLost3rd periodMost goals1st · 3 goals30%chance
Score breakdown
- After 60 minutes 3-1
- By period 1-0, 1-0, 1-1
- Likeliest 3-1 (4%), 4-2 (4%), 3-2 (4%)
Season so far
This seasonHead-to-head
- Feb 13, 2026: Brown Bears 3, Harvard Crimson 2, after a shootout.
- Dec 6, 2025: Harvard Crimson 7, Brown Bears 3.
- Mar 1, 2025: Brown Bears 4, Harvard Crimson 3, after a shootout.
- Jan 10, 2025: Harvard Crimson 3, Brown Bears 1.
Last five games
- Loss, 2–4 at Massachusetts Minutemen, Oct 30. Odds: UMass 1.88, Harvard 3.15.
- Win, 2–1 against Massachusetts Minutemen, Oct 29. Odds: Harvard 2.08, UMass 2.65.
- Loss, 0–4 at Cornell Big Red, Mar 14.
- Win, 3–1 at Cornell Big Red, Mar 13.
- Win, 4–3 against St. Lawrence Saints, after overtime, Mar 6.
- Loss, 1–2 at Yale Bulldogs, Oct 30. Odds: Yale 2.12, Brown 2.65.
- Loss, 1–3 at Boston University Terriers, Oct 10.
- Loss, 0–9 at Union Dutchmen, Mar 7.
- Loss, 0–3 against Union Dutchmen, Feb 28.
- Loss, 1–3 against Rensselaer Engineers, Feb 27.
Each side’s last five, every competition — W a win, L a loss, OT a loss after overtime or a shootout. Beside each team, its goals and its 1X2 odds before puck drop; the odds that came in are lit (none after overtime: the draw).
Key insights
- 7-game losing streak for Brown Bears coming into this game.
- Head-to-head level at 2-2 after the last 4 meetings.
- 6.5 goals per meeting across the last 4 head-to-head games; the total is 5.5.
- 2nd vs 10th in the NCAA standings.
How the odds moved
| Market | Opening | Now | Move |
|---|---|---|---|
| 1X2: 1 (HAR) | 1.45 | 1.50 | Drifted |
| 1X2: X (draw) | 4.75 | 4.55 | Shortened |
| 1X2: 2 (BRO) | 5.04 | 4.75 | Shortened |
| Over/Under line | 5.5 | 5.5 | No change |
| Handicap HAR | −1.5 | −1.5 | No change |
Opening and current odds from the bookmakers we track; the handicap line is shown from the home team’s side.
NCAA standings
NCAA · ECAC
| # | Team | GP | W | L | OTL | Pts | P% | +/− |
|---|---|---|---|---|---|---|---|---|
| 1 | 29 | 24 | 0 | 0 | 116 | 2.000 | 0 | |
| 2 | 25 | 17 | 1 | 0 | 92 | 1.840 | 0 | |
| 3 | 25 | 16 | 1 | 1 | 92 | 1.840 | 0 | |
| 4 | 30 | 15 | 1 | 0 | 76 | 1.267 | 0 | |
| 5 | 30 | 13 | 2 | 1 | 86 | 1.433 | 0 | |
| 6 | 30 | 13 | 1 | 1 | 76 | 1.267 | 0 | |
| 7 | 30 | 13 | 3 | 1 | 82 | 1.367 | 0 | |
| 8 | 25 | 11 | 2 | 0 | 73 | 1.460 | 0 | |
| 9 | 30 | 12 | 2 | 0 | 74 | 1.233 | 0 | |
| 10 | 25 | 9 | 2 | 0 | 59 | 1.180 | 0 | |
| 11 | 25 | 5 | 1 | 1 | 43 | .860 | 0 | |
| 12 | 25 | 4 | 4 | 0 | 60 | 1.200 | 0 |
Pts points, on the league’s own system. The table follows the league’s own order. W/L/OTL wins, regulation losses, overtime and shootout losses · GP played · P% points share · +/− difference.
Harvard Crimson host Brown Bears in the NCAA on Friday, November 6, 2026. Who wins after 60 minutes, by how many goals, and how many goals in total — our 1X2, handicap and over/under picks come from one model, and every pick is marked won or lost for everyone to see. The model uses projected goals and shots, the starting goalies, recent form, the standings and the bookmakers’ current odds.