Sean Koerner

Sean Koerner

2329 Posts
Sean Koerner
2329 Posts
NFL, college football, college basketball, player projections. have created team/player projection models for essentially every sport at some point
Role
Director of Predictive Analytics
Experience
20 years
Location
Los Angeles
Total Bets
3.5K
Followers
313.5K

Summary

Sean runs the predictive analytics at Action Network. From the in-game win probabilities in the award-winning Action Network app, to the DFS models on FantasyLabs, to the fantasy football rankings across the network. He also churns out fantasy/betting content for the NFL and is co-host for the Fantasy Flex pod and the betting show Convince Me

Sean creates projects for nearly every sport, from the WNBA to MLB to college hoops and everything in between.

Experience & Accolades

Sean is one of the most decorated fantasy analysts in the industry, finishing first in the FantasyPros In-Season Accuracy standings in 2023 – which measures almost all fantasy football analysts on their in-season projections over the course of the season. You can read more about their methodology here. He also won the in-season ranking title in 2015, 2016 and 2017. This past season, he not only finished first overall, but was the No. 1 ranker out of 180+ entrants in running back, wide receiver and kicker rankings. He was top 10 in quarterbacks and tight ends, as well.

His 2023 performance was arguably the best in the contest’s history:

  • It was a record fourth No. 1 finish in the accuracy contest
  • He was the first expert in history to be No. 1 at multiple positions (RB + WR)
  • He was the expert to finish top 10 at every position

Sean started to become obsessed with sports betting & fantasy football ever since his father took him to Las Vegas for his annual fantasy football draft (at 8 years old). Sean started trying to project teams/players ever since and almost every action/decision he's made since has led him to where he is today. He began betting 20 years ago and began his sports betting/fantasy sports career as soon as he graduated from college in 2007. Prior to joining Action in 2018, he worked for MGM, RotoHog/FastPoint games, Bloomberg Sports, STATS.

Sean began his betting career in college by building sports betting models. He eventually turned into a bookie in college before moving to Vegas to work at Excalibur Sportsbook as a supervisor. He decided to move back to California to begin a career in fantasy sports/betting at RotoHog as a product manager. That was when he began entering his season-long fantasy projections into the FSTA contests and won the award for most accurate season-long NFL & MLB projections 2-3 times each.

He then moved to NY to work for Bloomberg Sports as a product manager and Head of Projections. They were eventually acquired by STATS where he maintained the same role as a product manager. That was when he began entering his weekly NFL rankings into the FantasyPros accuracy contest and won first place 3 years in a row from 2015-2017. He joined Action Network in 2018.

Education

Sean has a BA in Psychology from Long Beach State and took multiple advanced stats classes. He spent most of his time in the library reading stats/sports betting books creating prediction models and using them to bet on various sports (MLB, NFL, NBA, WNBA, etc.).

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Sean Koerner's Picks

Today
I mentioned this one on the Fantasy Flex Projections pod earlier this week. With Luther Burden III ruled out, Zaccheus gets a clear bump in usage. DJ Moore also benefits, but with both D’Andre Swift and Roschon Johnson ruled out, there’s a good chance Moore lines up in the backfield more often..which gives Zaccheus even more opportunity. This should be one of Caleb Williams’ cleanest pockets of the season, if not his career. The Bengals already rank bottom five in pressure rate, and Trey Hendrickson is doubtful. That’s significant because Zaccheus’ target rate jumps from 15% when Caleb is pressured to a team-high 31% when he has a clean pocket. Fewer scrambles also mean more pass attempts overall, which adds volume to the passing game. Zaccheus’ average target depth is just 5.7 yards downfield, a career low, but that short-area usage helps his reception market the most. He’s been a bit unlucky with only a 66% catch rate, and based on his target profile, I’d expect something closer to 71%. Factoring that in, I project him around 4.1 receptions with about a 60% chance to clear 3.5.
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Douglas is currently functioning as the Patriots’ No. 4 WR, and I expect him to run a route on only 30–35% of Drake Maye’s dropbacks while commanding targets on roughly 18% of his routes.. putting him near 2.2 expected targets this week. His catch profile is interesting: Douglas has a -15% catch rate over expected, suggesting positive regression is coming, but mainly on underneath targets rather than deep ones. He’s caught both of his deep targets (each on blown coverage), but his efficiency on short-to-intermediate throws should improve.. just not in a way that boosts his yardage ceiling. I’m projecting his yards per catch to settle around 11–13 yards going forward. With Rhamondre Stevenson out, TreVeyon Henderson should take on a heavier workload and draw more targets out of the backfield, while Hunter Henry is due for a bit of squeaky-wheel treatment. Add in a likely low play-volume environment against a run-heavy Falcons team, and this shapes up as a tougher spot for Douglas to clear this with his limited usage. I have his median around 16.5 yards, with roughly a 63% chance he stays under 23.5.
112
14
Ladd has been on a tear, averaging 7.3 receptions per game over his last three while leading the Chargers in targets in all three. But that stretch also came with 39.3 pass attempts per game from Justin Herbert, including a 55-attempt game against the Colts. This week sets up differently. The Chargers should be able to lean on Kimani Vidal and the run game as favorites, which likely means less passing volume overall. It’s also the first time in McConkey’s two-year career that the offense has a real target threat at TE in Oronde Gadsden II, and Quentin Johnston is due for a bounce-back after two quiet games. If the Chargers were projected to throw for 60 minutes, Ladd could absolutely clear this again, but this game script points toward fewer attempts and more balance. I’m projecting him closer to 5.1 receptions with about a 59% chance to stay under 5.5.
187
19
Gray has been a tackle machine this year, though he’s only cleared 8.5 in half his games. That’s mostly a reflection of his schedule..he’s faced several teams that rank below average in LB tackle opportunities. The only two times he’s faced teams in the top half of that metric were against Houston (17 tackles) and Arizona (12 tackles), and the Chargers fall right in that same range. With Jeffery Simmons out, there’s also a boost for Gray since Simmons’ absence should allow a few more runs to reach the second level, where Gray typically lines up directly behind him. That gives him a notable uptick in my tackle model. I’m projecting 10.1 tackles here with about a 65% chance to clear 8.5. I’ll also be sprinkling the 12+ tackles alt at +344 (fair price closer to +220), since he’s hit that mark in both of his other plus tackle matchups this season.
112
17
Proj closer to +220 🪜
25
15
Hutchinson has only cleared this number in 2 of 7 games this season, and that’s with a sack in 5 of them. I’m projecting him for 1.2 sacks here (right in line with his sack prop) yet still landing around 3.1 total tackles, giving roughly a 61% chance he stays under 3.5. There are multiple paths for him to finish under even if he records a sack or two. Detroit should dominate time of possession, limiting Minnesota’s total play volume. The Vikings are projected for 21.5 rush attempts, about 0.5 fewer than Detroit’s season average faced, which reduces Hutchinson’s run-game tackle chances. He’ll still have sack upside, but his tackle floor is lower in this game script.
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17
Brown has cleared this in just 3 of 8 games despite facing one of the easiest schedules for defensive tackles so far. The Packers rank bottom five in tackle opportunities allowed to DLs, which limits his upside in this spot. He’s also due for some sack regression.. I have him at 0.7 expected sacks compared to his 3 actual on the season, and Jordan Love is one of the toughest QBs to sack in the league. That expected dip in sack production offsets the slight boost he gets from the Packers’ higher projected rush volume. Overall, I’m projecting 3.1 tackles with roughly a 60% chance Brown stays under 3.5.
94
16
PIT +3.5-112
IND
IND Team Abbreviation@PIT Team Abbreviation
PIT
0.56u
11/02 6:00 PM
Sharp prop betting often ties back to projected game scripts. When I see value on a team ATS, I’ll usually look for correlated prop value within that same script..but in this case, the spread itself is where I’m showing the most value. I’m projecting this closer to Steelers +2.5, and while I checked for value in “Steelers covering” game script props, nothing stood out as much as simply backing the side. The Colts look like a legit Super Bowl contender, but this could also be the point where their market perception peaks (though I could be wrong and they’re just one of the best teams of the last decade, it’s certainly possible). Either way, getting Pittsburgh +3.5 at home (Colts winning by 3 exactly is the most likely outcome) is where I’m showing the most value in this matchup.
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The 3rd overall pick has been an elite pass rusher so far, tied for a league-high 19 quick pressures, the most predictive metric for future sacks. Yet he’s only credited with 0.5 sacks on the season. My expected sack model has him closer to 4.1 sacks, meaning he’s due for some serious positive regression. I’m projecting about a 51% chance he records a sack here. FanDuel counts a 0.5 sack as a win for this market, and while DraftKings lists him at Over 0.25 at +139, FanDuel’s +154 offers better value. DK also has 2+ sacks at +1080, which I project closer to +620, so that’s worth a small sprinkle as well. Mac Jones should drop back around 37 times, and he’s roughly league average in sack rate which makes this a solid spot for Carter’s first real breakout. The market is looking too much into his measly 0.5 sacks on the season, but the metrics say he’s on the verge of a multi-sack game.
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Projecting Carter closer to +620 to have 2+ sacks
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22
Lassiter has been a tackle machine this season, averaging 6.4 per game, but has only cleared this in 3 of 7 games. The main reason for that is his brutal schedule, where he’d be expected to have about 5 more tackles if he faced a league-average slate. This should be an eruption spot against a Broncos team that’s allowed the 3rd-most tackles to opposing CBs. The only above-average matchup he’s had all season was the Rams (6th-most tackle opps to CBs), and he finished with 9 tackles in that game. Lassiter also leads the Texans in solo tackles in both run defense and coverage, which is rare for a CB. He’s not going to be involved in sacks, and with Bo Nix being one of the toughest QBs to sack, his scrambles/completions (that normally would have been sacks against other teams) should only lead to more tackle opps for Lassiter specifically. The Broncos are also expected to provide more run and completion volume than Houston typically faces. Projecting him closer to 6.8 tackles, with about a 67% chance to clear 5.5.
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After being extremely pass heavy through the first two games, OC Chip Kelly made a noticeable shift toward the run, and since then, the Raiders have the 2nd-lowest PROE in the league. It’s clear they’re trying to mask just how bad Geno Smith has been and instead lean on 1st-round rookie RB Ashton Jeanty. I expect that approach to continue after the BYE, especially with Vegas only 3-point underdogs at home, a rare setup where they could actually play with a lead. Geno’s thrown 10 interceptions this season but has been a bit unlucky as I have him at 7.7 expected INTs based on his turnover worthy throw rate. Still bad, but not as disastrous as it looks on paper. That should help keep the Raiders in a balanced, run-heavy script rather than the panic-throw mode we’ve seen if he can avoid throwing a pick here. On the flip side, if he tosses another 1–2 picks, there’s a real chance Kenny Pickett replaces him. Coming off a BYE, that possibility adds sneaky downside to Geno’s passing volume similar to the in-game benchings we cashed in on the last two weeks with Justin Fields and Spencer Rattler. It’s worth noting Geno has one of the lowest throwaway rates in the league (just 2%), which means fewer “wasted” pass attempts that are always brutal when you have an under in this market. I’m projecting him closer to 30 pass attempts, with roughly a 60% chance to stay under 31.5.. and that’s without even baking in any extra value for the potential benching scenario.
201
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Pending
Futures
Matthew Stafford o22.5-114
2025 NFL Regular Season - Total Passing TDs
0.57u
Discussed this on The Favorites
70
24
Cooper Kupp u700.5-114
2025 NFL Regular Season - Total Receiving Yards
1.14u
86
25
Javonte Williams u525.5-115
2025 NFL Regular Season - Total Rushing Yards
1.15u
48
16
Jared Verse o7.5-135
2025 NFL Regular Season - Total Sacks
1.35u
49
16
Past Performance
Yesterday0-0-00%
0.00u
Last 7 Days11-8-058%
1.60u
Last 30 Days48-33-059%
8.24u
All Time1937-1562-3155%
225.72u
Top Leagues
NFL1111-883-1955%
129.47u
MLB298-247-454%
42.72u
NCAAB262-210-355%
28.85u
WNBA147-118-355%
19.47u
NCAAF36-23-259%
6.62u
UFL5-4-056%
0.60u
Golf0-3-00%
-0.60u
NBA78-71-052%
-1.01u
Betting Highlights
Favorite Bet of All-Time
Patrick Mahomes under 30.5 rushing yards for Super Bowl LIV. He had 44 yards going into the final drive. Kneeled down 3 times for -15 yards to drop down to 29 yards and hit the under
Most Heartbreaking Bet
Max bet Jimmy Graham under 23.5 rec yards in the WC playoff game against NO in 2020. He had 6 yards heading into the final drive with the Bears down 3-21. On the final play of the game, Mitch Trubisky finds Graham in the back of the end zone for an insane one handed grab for a 19-yard garbage time TD. Graham finished with 25 yards and I'm still tilted by this. Side note: Stuckey was on this prop with me.
Specialties
  • NFL
  • College football
  • College basketball
  • Player projections
  • Have created team/player projection models for essentially every sport at some point