DFS PGA: Victiv v Draftkings

Written By PlayPicks Staff on February 8, 2015 - Last Updated on June 20, 2018

Part 1 – Scoring Analysis


This article is going to analyse the scoring systems of the two daily fantasy industry leaders in the area of fantasy golf.  Both Victiv and Draftkings are arguably the two best sites for daily fantasy players to enter PGA contests and understanding the differences between how the two sites score their PGA contests is vital in ensuring we make sound choices and selections each week.  While certain choices will always be dictated by the pricing, understanding how scoring differs between sites should also help us in our selections.






Double-eagle: 20pts, Eagle: 8pts, Birdie: 3pts, Par: .5pts, Bogey: -.5pts, Double bogey or worse: -1pt


Bonus pts:


3 birdies in a row: 3pts, Bogey free round: 3pts, All 4 rounds under 70: 5pts, Hole-in-one: +10pts

Placements—range from 30pts for first (winner) to 1pt for 40-50th place finish

See here for full Draftkings scoring:




Double-Eagle: 15 points, Hole-In-One: 14 points, Eagle: 9 points, Birdie: 5 points, Par: 2 points, Bogey: -1 point, Double Bogey: -4 points, Triple Bogey: -7 points, Quadruple Bogey or Worse: -10 points


Full Victiv Scoring (and explanation) can be found here:


On first glance, one may look at Draftkings scoring method and believe that it is more of a performance based system simply because it awards progressive points for higher finishes and bonus points for particular good play.  However, when we start to look closer at the scoring systems and results we see that Victiv’s system is the one that actually bases its scoring entirely on performance—in relation to the rest of the field—while Draftkings scoring brings in other variables (some of which are completely unpredictable unfortunately).  Here’s an example to delineate how the two differ:


Looking at scoring from the Waste Management Open we compare three players and their respective performances and scores and from each site:


 Hideki Matsuyama:

187 (Victiv)— 46 PAR, 19 BIR, 1 EAG, 5 BOG,1 DBB

113.5 (Draftkings)—46 PAR, 19 BIR, 1 EAG, 5 BOG,1 DBB, 1 2nd, 2 BIR3+, 1 BOFR


Bubba Watson:

187 (Victiv)—51 PAR, 16 BIR, 1 EAG, 4 BOG

105.5 (Draftkings)—51 PAR, 16 BIR, 1 EAG, 4 BOG, 1 2nd, 1 BIR3+, 1 BOFR


Ryan Palmer:

187 (Victiv)—52 PAR, 16 BIR, 1 EAG, 2 BOG,1 DBB

109 (Draftkings)—52 PAR, 16 BIR, 1 EAG, 2 BOG,1 DBB, 1 2nd, 3 BOFR


As you can see while the scores between the players have an 8 point swing over at Draftkings, at Victiv the players—who all finished Tied for second at -14—achieved the exact same scores.  Victiv’s scoring model essentially works to ensure that a player will achieve a score relative to his finishing position (or score) and won’t vary based off of any other factors.  To put it simply, any players achieving the same final score in a golf tournament will end up with the same fantasy score on Victiv.  Above we can see how this principle applies.  When looking at the three players we can see that Matsuyama actually scored the most birdies of the three players, but he also scored the most bogies.  Hence, the positive scores a player gets from scoring a lot of birdies are offset on Victiv by the relative larger negative scores for bogies and worse.  On Victiv, it doesn’t matter how a player gets to his respective final finishing score for a golf tournament, all that matters is the actual final score itself as that alone is ultimately what will determine his score on Victiv.


For DFS players Victiv’s system is extremely friendly since it is basing its scoring off of tournament performance and no other in game factors.  As a DFS player, predicting a player’s overall performance is our most consistent and reliable predictor so a scoring system created on this basis alone makes it less variable and just generally more reliable.  At Victiv, if our golfer has a high finishing position we know we will be awarded the same as other players who finish at his position but also more than those who finish under him.



In comparison, Draftkings PGA scoring model brings some other less predictable variables into the equation.  These variables make the scores between the three equally placed players in our example, much different.  As we can see, Matsuyama scored 4.5pts higher than Palmer and 8pts higher than Watson on Draftkings, even though all three finished at 14 under par and tied for second.  This is mainly due to two factors.  First, Matsuyama achieved 3 bonus achievements worth 3pts each while Watson only achieved two.  However the other factor is that Draftkings scoring rewards players more for scoring birdies while punishing players less for scores of bogies or worse.  When comparing Palmer and Matsuyama we see that both players scored 9 bonus points but Matsuyama scored 4.5 points higher.  This is because Matsuyama ended up with 19 birdies to Palmer’s 16.  While Palmer outscored Matsuyama in Pars (26pts—23pts), Matsuyama ended up with a 9 point advantage over him in Birdies (57pts—48pts).  While this advantage was negated somewhat by Matsuyama having more bogies on his card (5 compared to Palmer’s 2) it still did not equal out the final scores and Matsuyama ended up outscoring Palmer by 4.5 pts.





While I am admittedly a bigger fan of Victiv’s less variable model for DFS purposes I do see some positives in Draftkings scoring model.  First, it creates some extra excitement since it gives the possibility for some large swings should a player vault numerous positions or score a bonus achievement.  Second, it’s scoring is still largely performance based, so even though there may be some weeks where our players fall victim to the fickleness of the bonus points being awarded, it still mainly holds that the higher position our player places and the more under par he is, the higher relative score he will achieve in relation to the rest of the field.  Third, while the number of birdies a player scores each week is relative hard to predict, some players do have a higher propensity for birdies.  Thus using players with higher propensity for eagles and birdies (even if they score more bogies) can in theory be used as a tiebreaker when deciding between players since Draftkings rewards the players more for birdies and eagles.


However, when we look at things from a strictly predictive perspective we can see the flaws in Draftkings model.  Awarding points for achievements that no Daily Fantasy player could possibly ever predict on a consistent basis takes away from the skill aspect of the game.  Predicting when hole-in-ones, birdie streaks, and bogey free rounds will occur are an impossible task and make the games less predictable and unfortunately, more like gambling.  Even though the bonuses make up a small amount of the scoring it still makes the game less predictable, and therefore less skill-based, never a good thing for all but the mostly recreational player.


Victiv’s model on the other hand is based entirely on player performance.  A player who ends his tournament in a certain place with a certain score will achieve the same number of points as his peers who also achieved the same score.  Since the top finishing position and top actual finishing score is what golf tournaments award prize money on—and what golfers aim to achieve each and every week—it seems logical that Daily Fantasy sites should base their scoring models around this and only this factor.


To sum up, we know a golfer’s goal each and every week is to post the lowest score possible (to par).  Since we know that we are able to use research to help us predict when a player might achieve a low score and good finishing position on a certain week.  However, there are certain variables within a round that a DFS player cannot, with any certainty, predict when they will occur.  While these factors may add somewhat to the thrill of a fantasy game, it also creates more variables and less skill-based scoring which is not necessarily good long-term for the industry or the more skilled DFS player.


I’ll be back in the near future with the second part of my article where I compare the rosters and pricing differences between the two sites.


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