🔮 Prediction for Indianapolis Colts vs Tennessee Titans – NFL (October 18)

Why this pick

The pick is J. Taylor Under 89.5 rushing yds. Over his last 9 games, Jonathan Taylor went over the line of 89.5 rushing yds in 3 of 9, averaging 72.78 per game. Applied to this pick, it would have landed in 6 of 9 (67%).

Across the sample his range runs from 26 to 98.

Jonathan Taylor's last 9 games

6 of 9 under 89.5

89.5

74vs Jacksonville Jaguars · 19-36 · 12/07

87vs Seattle Seahawks · 16-18 · 12/14

70vs Jacksonville Jaguars · 17-23 · 12/28

26vs Houston Texans · 30-38 · 01/04

98vs Baltimore Ravens · 23-41 · 09/13

92vs Kansas City Chiefs · 30-33 · 09/21

68vs Houston Texans · 19-17 · 09/27

95vs Washington Commanders · 30-13 · 10/04

45vs Pittsburgh Steelers · 22-34 · 10/11

Recent winning player props

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AI Pick for Indianapolis Colts vs Tennessee Titans – NFL

For this matchup the AI picked a prop: Jonathan Taylor, Under 89.5 rushing yards, at 1.91.

The final score changes nothing; all that counts is what Jonathan Taylor does.

First fact: the line of 89.5 sits 16.72 above what Jonathan Taylor produces on average, 72.78 rushing yards per game over the last 9.

The model doesn't settle for the bare average: it gives recent games more weight and arrives at a projection of 69, lower than the plain average because his most recent games came in below it, 20.5 below the line.

Real frequency is the most honest number: in 6 of the last 9 games, Jonathan Taylor finished on the pick's side.

For odds of 1.91 to pay off you need to hit about 4.7 out of every 9: the Jonathan Taylor record sits comfortably above that.

His last 4 games (45, 95, 68, 92, newest first) leave 2 of 4 on the pick's side: no sharp change from the full sample.

How stable is he? Game to game he strays about 24.22 from his average, and the line sits 0.7 of those deviations away: little room for surprises.

He plays at home today: in that setting, within the sample, he averages 78.67 over 3 games.

For the Under, every run counts against it, and one long one can be enough to lose it.

The model doesn't assume how the game will be played: it leans on what Jonathan Taylor has been producing on the ground.

The AI doesn't bet on hunches: it takes the real Jonathan Taylor series, checks it against what the market as a whole expects for this line, and only when the best available price sits above that estimate does it publish the pick.

What can go wrong: one isolated big play, or a game that forces his team to change plans — in the NFL, a lopsided score changes how much a team throws and how much it runs.

On price: the edge the AI flags is calculated at 1.91; below that it shrinks, above it grows.