RIT Tigers vs Michigan State Spartans prediction
Chance to win · 25% and 55% in regulation
All predictions
9 picks graded · Average confidence 63%Full game
- 1X2WonMichigan State1.22Confidence 53%
- Best tip of the game: Over/UnderWonU6.51.67Confidence 68%
- HandicapLostRIT +2.52.07Confidence 57%
- Winner (incl. OT)WonMichigan State1.12Confidence 58%
- Double chanceWonMichigan State or draw1.06Confidence 65%
- Draw no betWonMichigan State1.08Confidence 60%
- Both teams to score (GG/NG)WonYesConfidence 82%
1st period
- 1st period 1X2WonMichigan State1.67Confidence 51%
- 1st period Over/UnderWonU2.5Confidence 72%
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 2 games; an edge above the model’s usual ceiling.
Predicted final score
What the picks are derived from. Not a bet.Score details
- Correct scoreLost1–3After 60 min1–54%chance
- 1st period correct scoreWon0–11st period0–120%chance
- Highest scoring periodWon3rd periodMost goals3rd · 3 goals31%chance
Score breakdown
- After 60 minutes 1-3
- By period 0-1, 0-1, 1-1
- Likeliest 1-3 (4%), 2-4 (4%), 2-3 (4%)
Season so far
This seasonLast five games
- Loss, 1–5 at Massachusetts Minutemen, Oct 10.
- Win, 3–2 at Massachusetts Minutemen, after a shootout, Oct 9. Odds: UMass 1.57, RIT 4.30.
- Win, 4–2 against Niagara Purple Eagles, Oct 3.
- Loss, 1–4 at Niagara Purple Eagles, Oct 2.
- Overtime loss, 4–5 at Holy Cross Crusaders, after overtime, Mar 8.
- Loss, 1–5 against Northern Michigan Wildcats, Oct 11.
- Win, 6–2 against Northern Michigan Wildcats, Oct 9. Odds: Michigan State 1.05, N. Michigan 27.00.
- Overtime loss, 3–4 against Wisconsin Badgers, after overtime, Mar 28.
- Win, 2–1 against Connecticut Huskies, Mar 26.
- Overtime loss, 2–3 against Ohio State Buckeyes, after overtime, Mar 14.
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).
How the odds moved
| Market | Opening | Now | Move |
|---|---|---|---|
| 1X2: 1 (TIG) | 8.50 | 8.50 | No change |
| 1X2: X (draw) | 6.50 | 6.50 | No change |
| 1X2: 2 (MSS) | 1.18 | 1.18 | No change |
| Over/Under line | 6.5 | 6.5 | No change |
| Handicap TIG | +2.5 | +2.5 | 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 · Atlantic Hockey
| # | Team | GP | W | L | OTL | Pts | P% | +/− |
|---|---|---|---|---|---|---|---|---|
| 1 | 30 | 19 | 3 | 1 | 96 | 1.600 | 0 | |
| 2 | 30 | 15 | 2 | 0 | 94 | 1.567 | 0 | |
| 3 | American International | 32 | 14 | 0 | 0 | 105 | 1.641 | 0 |
| 4 | 30 | 15 | 1 | 1 | 92 | 1.533 | 0 | |
| 5 | 29 | 12 | 0 | 0 | 75 | 1.293 | 0 | |
| 6 | 30 | 11 | 2 | 2 | 81 | 1.350 | 0 | |
| 7 | 30 | 11 | 1 | 2 | 71 | 1.183 | 0 | |
| 8 | 32 | 12 | 0 | 0 | 88 | 1.375 | 0 | |
| 9 | 29 | 9 | 1 | 0 | 69 | 1.190 | 0 | |
| 10 | Mercyhurst Lakers | 30 | 8 | 5 | 1 | 77 | 1.283 | 0 |
NCAA · Big Ten
| # | Team | GP | W | L | OTL | Pts | P% | +/− |
|---|---|---|---|---|---|---|---|---|
| 1 | 30 | 21 | 3 | 1 | 122 | 2.033 | 0 | |
| 2 | 30 | 20 | 2 | 0 | 123 | 2.050 | 0 | |
| 3 | 30 | 19 | 2 | 0 | 105 | 1.750 | 0 | |
| 4 | 29 | 16 | 0 | 0 | 93 | 1.603 | 0 | |
| 5 | 32 | 15 | 2 | 0 | 92 | 1.438 | 0 | |
| 6 | 30 | 12 | 0 | 1 | 68 | 1.133 | 0 | |
| 7 | 30 | 11 | 0 | 0 | 74 | 1.233 | 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.
RIT Tigers host Michigan State Spartans in the NCAA on Saturday, October 17, 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.