Machine learning model names four anytime TD scorers for NFL Divisional Round

The SportsLine Machine Learning Model has locked in its anytime touchdown scorer picks for the NFL Divisional Round, Cbssports reports, backing Courtland Sutton (+185), Christian McCaffrey (-130), Jayden Higgins (+320) and Kyren Williams (+120).

The model highlights Sutton's role as Denver's top target (74 receptions, 1,017 yards, seven receiving touchdowns) and projects him to score in 37% of simulations. It points to McCaffrey's recent usage — two receiving touchdowns in the Wild Card win, eight targets and 15 carries last week, and 17 regular-season touchdowns — and projects him to score in 62% of simulations. Houston rookie Jayden Higgins, who scored in each of the final two regular-season games and had three catches for 39 yards in the Wild Card Round, is projected to score in 33% of simulations amid Nico Collins' concussion. The model also notes Williams' role in the Rams' high-scoring offense (30.7 points per game), his 13 touchdowns this season (three receiving) and projects him to score in 52% of simulations.

SportsLine also offers projections for every player prop and has compiled its best bets for each Divisional Round game, with expert Brady Kannon's locked picks noted alongside the model; Kannon is listed as 28-11-2 (+1570) over his last 41 NFL ATS picks.

Key Topics

Sports, Courtland Sutton, Christian Mccaffrey, Jayden Higgins, Kyren Williams, Divisional Round