NHL Simulations: 20,000 Runs, Player Props & DFS | November 4, 2026

We ran Wednesday’s four-game NHL slate 20,000 times per game using the projected roster cases described below. Florida won most often; Seattle produced the highest average score. The useful part is how the scoring is distributed, what a quoted prop asks of a player, and which DraftKings salaries leave room for the rest of a lineup.

This is the first NHL entry in our Simulations series, a companion to our November 4 NHL best plays and full sample lineup. The player results below include overtime and exclude shootouts.

Three player findings that change the conversation

Tage Thompson: strong DFS production, a tougher shots-over case

$8,100 | 13.21 average DraftKings points | 43.6% with 4+ shots

Thompson reached four shots on goal in 8,723 of 20,000 games and scored a goal in 41.7%. His simulated DraftKings range from the 10th to 90th percentile was 3.0 to 25.8 points. That spread matters: the expensive one-off carries a meaningful ceiling, but he is not a guaranteed floor.

Buffalo’s November 2 report listed 63 season shots, including 18 over his previous three games. The shooting volume supports the DFS interest. The published DraftKings 4+ shots price of +100 is a different decision: its 50% break-even rate is above the 43.6% simulated share. This run does not make the shots over a priority merely because Thompson is our premium one-off.

Noah Ostlund ($3,900) brings their combined cost to $12,000. Their reported first power-play connection gives that pairing a hockey reason to exist across two even-strength lines.

Mackie Samoskevich: a goal angle and an affordable scoring route

$3,900 | 8.61 average DraftKings points | 31.0% with a goal

Samoskevich scored in 6,207 of 20,000 runs. The published +290 anytime-goal price translates to a 25.6% break-even rate before fees, below his 31.0% simulated share. That makes him a price to investigate rather than an automatic bet; the model has not established a profitable prop record.

The DFS case does not depend on that price gap. Seattle’s projected lineup places him with Berkly Catton ($3,300) and Kaapo Kakko ($3,300). At $10,500, the trio is $9,500 cheaper than Florida’s featured forward line. The reported PP2 grouping adds a second shared scoring route, although that deployment context is not a separate chemistry adjustment in the model.

Seth Jones: a point-producing defenseman who fits the build

$5,400 | 10.40 average DraftKings points | 60.9% with a point

Jones recorded a goal or assist in 12,180 of 20,000 simulations. His reported PP1 role connects him with both Tkachuks, so he offers another way into Florida’s offense without buying a third expensive winger. This is a one-or-more-point result, not a two-point prop.

Jones plus Samoskevich costs $9,300, leaving $40,700 for seven DraftKings roster spots. That is the practical appeal: Florida power-play exposure, a Seattle value forward and enough remaining salary to choose a premium scorer or a more expensive goalie.

More player props from the full distribution

Panarin’s 38.4% goal share is almost level with the 38.5% required at +160. Jack Quinn’s 37.2% compares with 31.7% at +215, while Farabee’s 58.1% point share compares with 55.6% at −125. Those are distinct comparisons worth tracking, not a blanket list of bets. Quinn offers a Buffalo scoring alternative; Farabee gives the Calgary side of a game in which Seattle is only a modest simulation favorite.

Prices: DraftKings Network player-prop board, captured November 4 at 3:31:02 p.m. ET. The board did not supply the individual quote time. These are published snapshots, not verified live offers. Break-even rates exclude any applicable fees; no opposite-side price adjustment has been made.

Who won, and which final scores appeared most?

Buffalo–Ottawa was essentially a coin flip. Florida had the clearest win advantage, while Seattle averaged the most goals. A decimal average is not a predicted final score, so here are the three most frequent exact scorelines in each 20,000-game distribution:

• OTT at BUF: OTT 3–2 (7.0%), BUF 3–2 (6.9%), BUF 4–3 (6.3%).
• CHI at FLA: FLA 3–2 (7.8%), CHI 3–2 (6.9%), FLA 4–3 (6.6%).
• SJS at LAK: LAK 3–2 (7.7%), SJS 3–2 (7.4%), LAK 4–3 (6.5%).
• CGY at SEA: SEA 3–2 (7.4%), SEA 4–3 (6.7%), CGY 3–2 (6.4%).

Even the leading scoreline appeared in fewer than 8% of runs. Ottawa’s 3–2 result was the single most common Buffalo-game score, despite Buffalo winning slightly more often across all scores. That is why one chosen final score cannot stand in for the full distribution. These final-score counts combine regulation, overtime and shootout endings, including the shootout winner credit.

How the DFS pieces fit

Florida is the primary scoring stack. Brady Tkachuk, Sam Bennett and Matthew Tkachuk cost $20,000 and average 11.27, 8.13 and 10.47 DraftKings points, respectively. Both Tkachuks share PP1; Bennett is on PP2. The reason to include Bennett is the projected even-strength line and his $5,000 salary, not a claim that all three share the first power play.

Seattle supplies flexibility. Catton, Kakko and Samoskevich average 8.09, 6.59 and 8.61 points. Two of them can be enough if a full three-man secondary line leaves too much of the lineup dependent on one group. Their savings can fund Jones, Thompson or a goalie upgrade. Calgary’s Zayne Parekh ($3,400) and Morgan Frost ($3,800) are a $7,200 alternative through their reported PP1 roles.

San Jose is a different game story. Celebrini–Smith–Toffoli costs $19,300, with the reported even-strength and PP1 combination providing the roster logic. Toffoli’s $4,000 price is important: he supplies the affordable third piece alongside two expensive forwards. The Kings won 54.7% of runs, but that still leaves a substantial Sharks-winning portion of the distribution.

Panarin is the Kings one-off. His $7,200 salary and 11.10-point average offer another premium route. The November 3 practice report reunited him with Kempe and Laferriere. Prefer that newer reporting to an older first-line listing.

The averages help compare cost and output; they do not measure tournament ownership or lineup profitability. For the complete $49,300 roster construction and position checks, use our NHL main-slate best plays article.

Goalies and the lineup snapshot

At the 3:18 p.m. ET source check, Daily Faceoff’s November 4 board listed Samuel Ersson, Jacob Markstrom and Yaroslav Askarov as confirmed. Colten Ellis, Spencer Knight, Dustin Wolf, Joey Daccord and Darcy Kuemper were listed likely. Those labels are attributed to Daily Faceoff, not independent primary confirmation.

Markstrom ($8,500) fits a Florida-winning roster. Knight ($6,900) saves $1,600 but belongs to a lineup that tells a different story from a large Panthers scoring stack. The simulation does not estimate individual goalie skill, so its team win shares should not be read as a goalie-ranking system.

The Seattle case uses the later projected Mahura–Ottavainen defense pair, with Daccord in net; the team explicitly labels its lines unofficial. The first two games begin at 7:30 p.m. ET, and Calgary–Seattle and San Jose–Los Angeles begin at 10 p.m. ET.

The moneyline context, briefly

DraftKings’ published game previews, checked at 3:17 p.m. ET, listed Buffalo −130, Florida −258, Los Angeles −166 and Seattle −135. Seattle’s 57.3% simulated win share sits almost level with the 57.4% break-even rate at −135. We are not turning the other model/market differences into underdog recommendations. The stronger contribution from this first run is the player distribution and the salary decisions above.

Reading the model and the 3–2 example

These results come from the saved 20,000-game ensemble for each displayed roster case. Historical scoring and event rates inform a joint team/player model, with overtime, shootouts and DraftKings scoring accounted for. The results are conditional on those roster cases; they are not a probability-weighted mixture of every possible lineup.

This is an experimental model, with mixed historical validation rather than an established betting or DFS edge. It does not model current-line chemistry, player-specific ice-time changes, individual goalie skill or contest ownership. Reported line and power-play assignments provide hockey context for the analysis, not evidence that those effects have been calibrated into the simulations.

One illustrative saved game finished Florida 3–2 in regulation. It was selected from the most frequent score-and-ending combination, which appeared in 1,059 runs (5.3%); the broader Florida 3–2 final-score bucket across all endings appeared in 1,564 (7.8%). Its individual player totals are an example, not their average or a sequence of predicted goals.

Our starting construction: Florida scoring exposure, selective Seattle value, and Thompson or Panarin when the remaining salary fits. Samoskevich’s goal share, Thompson’s shot distribution and Jones’ point production are the findings to carry forward as this series develops.