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NFL Anytime TD Picks Thursday: Colston Loveland Offers Real Value - October 22, 2026

New England Patriots @ Chicago Bears

Thu 8:15 PM ET
Jon's best play · Anytime TD
39.8%our model
vs
37.0%market implied
+2.8ptsmodel edge
+170price at build

Our calibrated model gives Colston Loveland a 39.8% shot at the end zone, while the market is only pricing 37.0%. That gap is the play.

  • Jahdae WalkerCHI · WR13% model · 5% market+7.9pts+2001at build
  • Cole KmetCHI · TE19% model · 16% market+3.0pts+540at build
  • Colston LovelandJon's best playCHI · TE40% model · 37% market+2.8pts+170at build
  • Corey KinerNE · RB13% model · 11% market+1.9pts+800at build
  • Kyle WilliamsNE · WR14% model · 13% market+1.4pts+700at build
model TD% market implied

D'Andre Swift is the model's most likely scorer (48.4%) — but not a pick at today's price: the market is asking more than our number. Good pick, wrong price. Value opens at +107 or better.

Full model board · all 41 players (ranked by Model TD%)
#PlayerModel vs marketOdds
  • 1D'Andre Swiftmodel's #1CHI · RBoverpriced — value at +107 or better48% model · 62% market-161at build
  • 2Rhamondre StevensonNE · RBoverpriced — value at +135 or better43% model · 53% market-111at build
  • 3Colston LovelandJon's best playCHI · TE40% model · 37% market+170at build
  • 4A.J. BrownNE · WRoverpriced — value at +199 or better34% model · 43% market+134at build
  • 5Rome OdunzeCHI · WRoverpriced — value at +213 or better32% model · 37% market+174at build
  • 6Hunter HenryNE · TE28% model · 31% market+220at build
  • 7Luther Burden IIICHI · WR26% model · 35% market+184at build
  • 8TreVeyon HendersonNE · RB26% model · 25% market+300at build
  • 9Roschon JohnsonCHI · RB20% model · 33% market+200at build
  • 10DeMario DouglasNE · WR19% model · 24% market+310at build
  • 11Cole KmetCHI · TE19% model · 16% market+540at build
  • 12Kalif RaymondCHI · WR18% model · 21% market+370at build
  • 13Efton Chism IIINE · WR16% model · 18% market+460at build
  • 14Eli RaridonNE · TE16% model · 17% market+490at build
  • 15Caleb WilliamsCHI · QB16% model · 24% market+320at build
  • 16Drake MayeNE · QB16% model · 22% market+350at build
  • 17Romeo DoubsNE · WR16% model · 24% market+320stale
  • 18Kyle WilliamsNE · WR14% model · 13% market+700at build
  • 19Corey KinerNE · RB13% model · 11% market+800at build
  • 20Jahdae WalkerCHI · WR13% model · 5% market+2001at build
  • 21Sam RoushCHI · TE10% model · 8% market+1100at build
  • 22Zavier ScottCHI · RB10% model · 5% market+2001at build
  • 23Zavion ThomasCHI · WR8% model · 7% market+1399at build
  • 24Cameron LatuNE · TE6% model · 6% market+1601at build
  • 25Tanner ArkinNE · TElimited data5% model · 6% market+1500at build
  • 26Kevin ByardNE · FSlimited data1% model · 1% market+8909at build
  • 27Jaylon JohnsonCHI · CBlimited data1% model · 1% market+7419at build
  • 28Malik MuhammadCHI · CBlimited data1% model · 1% market+9424at build
  • 29Cam LewisCHI · CBlimited data1% model · 1% market+9900at build
  • 30Christian GonzalezNE · CBlimited data1% model · 1% market+10889at build
  • 31Kyler GordonCHI · CBlimited data1% model · 0% market+23710at build
  • 32Craig WoodsonNE · SAFlimited data1% model · 1% market+7419at build
  • 33Dillon ThienemanCHI · SAFlimited data1% model · 1% market+7900at build
  • 34Devin BushCHI · LBlimited data0% model · 1% market+6893at build
  • 35Christian EllissNE · LBlimited data0% model · 1% market+9424at build
  • 36D'Marco JacksonCHI · LBlimited data0% model · 1% market+9900at build
  • 37Robert SpillaneNE · LBlimited data0% model · 1% market+18768at build
  • 38Austin BookerCHI · DElimited data0% model · 0% market+49900at build
  • 39Kentavius StreetCHI · DElimited data0% model · 0% market+49900at build
  • 40Grady JarrettCHI · DTlimited data0% model · 0% market+30203at build
  • 41James LynchCHI · DTlimited data0% model · 0% market+30203at build
First TD scorer market (24)

Ranked by market price. Our model covers anytime TD only, so the model column shows each player's anytime TD probability for context.

Model edge is our calibrated anytime-TD probability minus the market-implied probability from the current price. A positive edge means our model rates the player higher than the market is pricing. Players without a positive edge are not plays at today's prices — however likely they are to score.

Limited data marks players with thin history (rookies, new roles); their probability is shrunk toward a position baseline and should be read cautiously.

Model TD% is a probability, not a prediction of certainty. Odds refresh from the live market about every 30 seconds; prices marked "at build" are the offers captured when the board was generated.

Model nfl_atd-v1r2-20260930

Analysis

Thursday, October 22, 2026. One game on the board. Forty-one players listed. The NFL is not giving us a full slate tonight, but you only need one good number to make Thursday night worth your time. New England Patriots vs Chicago Bears kicks off at Soldier Field, and after going through this board, there is one play I want to put my name on.

My Best Play: Colston Loveland, Chicago Bears TE, +170

My best play on this slate is Colston Loveland of the Chicago Bears. The model has him at 39.8% to score an anytime touchdown, a HIGH confidence tier. The market has him at +170, which implies 37.0%. The model clears the implied probability by nearly three points, and you are getting plus money on a HIGH-tier tight end. Tight ends who work in the red zone are among the most dangerous touchdown-scoring options in football. When the model is above the market number at plus odds with a HIGH tier attached, that is a play worth taking.

Let me be straight with you: 39.8% means this does not happen more often than it does. Even the strongest anytime touchdown plays miss most of the time. If you back Loveland at +170, you need to accept that he will not score on the majority of Thursdays you play this. That is the variance built into every touchdown prop. But when a HIGH-tier player is priced below the model's probability at plus money, that is the spot. That is my play on this slate.

The Board's Top Name and Why I Passed

The highest model probability on this entire board belongs to D'Andre Swift of the Chicago Bears. The model has Swift at 48.4% to score a touchdown, the top number on the slate and a HIGH-confidence tier. That is a serious number. Lead running backs are among the most consistent touchdown producers in the game, and 48.4% reflects that kind of role and opportunity.

So why did I pass? The market has Swift at -161, which implies a 61.7% chance of scoring. The model says 48.4%. That is a gap of more than 13 percentage points between what the model believes and what the book is charging. You are paying 61.7% probability for a player the model rates at 48.4%. That is a price problem, not a player problem. Swift may absolutely score on Thursday night. The model gives him the best chance of anyone on the slate. But when the market asks that kind of premium over the model number, the value has moved somewhere else. For me, it moved to Loveland at +170.

Context: The Rest of the Board

Rhamondre Stevenson of the New England Patriots is second on the board at 42.5% model probability, HIGH tier, and -111 market odds, implying 52.6%. The market is again running ahead of the model. A.J. Brown is fourth at 33.5% model, HIGH tier, with +134 market odds implying 42.7%. The market asks more than the model gives there too. Rome Odunze sits at 32.0% model, HIGH tier, at +174 with a 36.5% implied market probability, which is much closer to the model number. Hunter Henry is at 27.5% model, HIGH tier, at +220, implying 31.2%.

I am not recommending any of these players. They are context for where the board sits. My one play on this slate is Loveland. Every other entry in this section is information, not a pick.

Several players at the bottom of the board carry a LOW DATA designation. That includes Tanner Arkin (NE, TE) at 4.9%, Kevin Byard (NE, FS) at 1.3%, and the defensive backs and linemen listed toward the end of the table. LOW DATA means the model does not have enough individual information to anchor the number firmly, so it pulls the estimate toward a position baseline. Read those numbers as rough estimates, not strong convictions. They are on the board for completeness and transparency, not because the model has a firm read on them.

First Touchdown Market

The first-touchdown board is ranked by market price only. The model does not produce a first-TD probability. The anytime numbers are shown for context only. D'Andre Swift leads the first-TD market at +390, implying 20.4%. Rhamondre Stevenson follows at +580, implying 14.7%. A.J. Brown is at +820, implying 10.9%. Colston Loveland appears at +950 in the first-TD market, implying 9.5%.

I do not have a model-backed first-TD play on this slate. If you enjoy that market, the board is there to work through. Know going in that first-TD is a significantly higher-variance bet than anytime, and the model cannot tell you who scores first, only who is likely to score at some point during the game.

One game on Thursday night gives you a focused look at one matchup and one clear answer from the board. My best play is Colston Loveland at +170. The model has him at 39.8%, the tier is HIGH, and the price clears the market implied probability. That is the number, that is the play, and that is where I stand on this slate.

Anytime touchdown props are high-variance by nature. Even a strong model probability like 39.8% means the player does not score most of the time. Size your plays to what you are comfortable losing and never chase losses on a single night. All picks are for informational purposes only. Please gamble responsibly.

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