Notre Dame @ Purdue: Result, Lines & ATS Trends (Week 3, 2024)

Sat, Sep 14, 2024, 3:30 PM EDTWeek 3 · at Purdue

Weather at kickoff88°F11 mphgusts 21DryWeather watch ›

Notre Dame

1-1 · Power #4

▲ winner

Final

Purdue

1-0 · Power #117

final

Closing spread

ND -7.5

✓ ND W

Total

47.5

▲ Over · 73 pts

Model before kickoff

ND 28–20 PUR

✓ ND (73%) won

Closing line · ESPN BET

SourceESPN BET closing line

OpenND -10.5

CloseND -7.5

Total45.5 → 47.5

Books differ and lines move; check your sportsbook before betting.

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Market

Open → close

Spread

OpenND -10.5

3 → PUR

CloseND -7.5

3 pts toward Purdue

Total

Open45.5

▲ 2

Close47.5

Up 2 since the open

Line movement

Opening and closing line · tap a dot

Opened ND -10.5 · closed ND -7.5 · moved 3 toward PURmodel ND -12

model ND -12

Openline modelKickoff

Line context

Road favorites of 6.5–8.5 since 2023: won 74%, covered 59% (57 games)ⓘ

Closing line · ESPN BET

SourceESPN BET closing line

OpenND -10.5

CloseND -7.5

Total45.5 → 47.5

Books differ and lines move; check your sportsbook before betting.

Similar games

The recent games that looked most like this one before kickoff, and how they turned out

In the 1 games most like ND as a 7.5-point road favorite at PUR, the favorite won 1, covered 1, and 0 went over the total.

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This game: ND won 66–7; the favorite covered, as in 1 of the 1 similar games. 73 points went over 47.5, as in 0 of 1.

Favorite won

1 of 1100%

Normal range · usually 70%

Favorite covered

1 of 1100%

Normal range · usually 49%

Went over

0 of 10%

Normal range · usually 49%

Only 1 close matches, too few to read much into. Average result: favorite by 17 against an average line of 7; 45 points a game (usually 53.5). When games like this go over ›

All 1 games

Match	Game	Line	Final	Covered	O/U
Loose	CLEM @ SYR 2023 · Week 5 · loose · similar spread	-7	31–14	W	U53

History, not a prediction. Every FBS game from 2021 on is compared with this one as it looked before kickoff (team strength, the betting line, season form, situation, venue and rest), and only close matches are kept. How matches are found

ATS

Records before kickoff

	Season	Cover	Venue	Role
ND WL	1-1	50%	1-0	0-1
PUR W	1-0	100%	1-0	—

Venue/role: ND away, as favorite; PUR home, as underdog. Squares: last 5 games ATS (W covered, L didn’t), oldest first.

Totals

Over/under before kickoff

	O-U	Over %	SU
ND UU	0-2	0%	1-1
PUR U	0-1	0%	1-0

Went over in Q3. Of 192 earlier overs in games with totals 43.5–51.5, 31% had cashed by the end of Q3.

When games like this go over ›

Squares: last 5 games (O over, U under), oldest first. Hover for the score and line.

Last 10 games

Before kickoff, this and last season

	Straight up	Spread	Over / under
ND	7-3 70%	7-3 70%	6-3 67%
PUR	4-6 40%	4-6 40%	6-3 67%

Wins-losses (pushes and ties last). Spread and over / under skip games without a line.

Matchup stats

Season to date before kickoff · ranks among 137 FBS teams

Power rating this season

pts vs an average team · #rank · tap a dot

ND+18.9 →+14.6▼ 4.3#16

PUR+1.0 →+1.5▲ 0.5#63

Predashed line = average team · hover or tap a dotW2

Longer bar = better

PUR

#104

Offense

PUR better ▶

#59

Defense

PUR better ▶

0.0 #59

Turnovers

◀ ND better

−1.0 #112

63 plays #94

Pace

PUR faster ▶

66 plays #70

Unit by unitEach offense against the other's defense

When ND has the ball

Advantage: PUR defense

	ND off	PUR def	Edge
Points / game	18.5 #113	0.0 #2	PUR
Yards / play	5.14 #104	2.91 #5	PUR
PPA / play	+0.09 #86	−0.20 #16	PUR
Success rate	37% #111	24% #4	PUR

When PUR has the ball

Advantage: PUR offense

	PUR off	ND def	Edge
Points / game	49.0 #10	14.5 #44	PUR
Yards / play	8.83 #5	4.77 #60	PUR
PPA / play	+0.56 #4	−0.05 #46	PUR
Success rate	64% #2	40% #86	PUR

Bars show league standing (dashed mark = league middle); Offense and Defense use the average rank across the four stats below. In the tables, a highlighted value and the Edge column mark the side ranked better by at least 15% of the league; defense values are what that team allows. Yards and turnovers from ESPN box scores; PPA from CollegeFootballData (garbage time excluded). Descriptive only: the model already uses these.