## Why You Should Pivot to Underdog QBs in High Total Games for DFS

In the weekly Fantasy Trends, we leverage the Trends tool to find quarterbacks, wide receivers and running backs with notable data points for the upcoming DFS main slate. For more of our weekly football content, visit our NFL homepage.

In the final installment of this season’s series, I wanted to examine an assumption at the core of DFS analysis: Do higher Vegas totals promote improved quarterback performance?

I began my analysis by aggregating all opening totals in our database. That effort resulted in a 2,581-game sample size dating back to 2014. I assumed a normal distribution of Vegas totals, calculated mean and standard deviation for the data set, and produced z-scores for all opening totals in the distribution. Then I analyzed quarterback performance based on those resultant z-scores.

For your reference, below is the definition for a z-score, taken from www.investopedia.com.

A Z-score is a numerical measurement of a value’s relationship to the mean in a group of values. If a Z-score is 0, it represents the score as identical to the mean score. Z-scores may also be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean. Positive and negative scores also reveal the number of standard deviations that the score is either above or below the mean.

Standardizing Vegas totals in terms of z-scores allows us to objectively and statistically determine what a “high” Vegas total actually means — and how high a Vegas total must climb in order to deliver improved average performance for the quarterbacks in that game.

Our sample produced a mean opening total of 45.64 points and a standard deviation of 3.97 points. Based on the normal curve for sample distributions, 68% of NFL games since 2014 have featured Vegas totals ranging from 41.67 to 49.61 points.

### Results: QB Fantasy Performance Based on Opening Total

These results clearly show that high total games — those with a z-score of +1.00 or higher — correlate with enhanced quarterback performance. In games with totals above 53.5, the effect is even more pronounced; quarterbacks in those games produce an impressive Plus/Minus of +3.24.

However, those kinds of games are incredibly rare. In fact, there have been only 96 such games since 2014, which represents only 3.7% of our sample population. Moreover, games with a z-score of +1.0 or higher (50 or more points) constitute only 14.7% of our sample population.

The scarcity of these games compelled me to dig deeper. So, I proceeded to perform the same statistical treatment for implied team totals and implied opposing team totals.

### Results: QB Fantasy Performance Based on Implied Team Total

These results are perhaps more drastic than our previous data set. Quarterbacks with an implied team total of z=+2.00 or higher boast a Plus/Minus of +3.64, along with a dramatically-high ownership percentage of 14.2%. At the other end of our distribution, quarterbacks with implied team totals of 15.3 or lower (z=-2.00 or lower) have a Plus/Minus of -4.25 and consistency of just 20.5%

But I’d like to draw your attention to the z=0.00 to +1.00 range toward the middle of the distribution. Quarterbacks with implied team totals of 22.8 to 26.3 boast a respectable Plus/Minus of +1.01, but an average ownership percentage of just 5.3%.

That depressed ownership is one of the key results we’re looking for when attempting to identify value at any position. Quarterbacks in “smash spots” may boast elite Plus/Minus scores, but their ownership percentages are extremely high. Moreover, their average expected points are also high, indicating elevated DraftKings pricing. But, there exists a tier of quarterbacks slightly below these with deflated DraftKings pricing and ownership who still boast improved production. Those are the kinds of quarterbacks we’re searching for.

### Results: QB Fantasy Performance based on Implied Opposing Team Total

You might be wondering: “Why should we care about the implied point total for the opposing team?” But by using our Correlations tool, we can see that opposing quarterbacks have an r=0.59 correlation with quarterbacks in the same game.

Pearson’s correlation (r) measures the strength of relationship between two variables — in this case, the strength of relationship between one quarterback’s performance and the opposing quarterback’s performance. A strong correlation (the scientific standard for which is r=0.40, depending on the specific discipline) indicates a strong relationship between two variables.

In our case, that correlation suggests that if one quarterback is successful, the opposing quarterback’s performance also typically improves.

We’ve already established that quarterbacks in high total games — and with high implied team totals — boast elevated performance. So it follows that opposing quarterbacks in those games also should boast improved production.

While our data set is rife with parity across each z-score tranche, one notable result is average expected points. Quarterbacks playing against teams with high implied team totals feature lower average expected points — and thereby, lower DraftKings pricing. However, they still deliver average to above-average production, resulting in inflated Plus/Minus scores.

So there’s value in pivoting to the underdog opposing quarterback in these kinds of games.

### Targeting Underdog Opposing Quarterbacks

The final piece of my analysis was to combine elements from our results to highlight potential quarterback pivots for the Week 17 DFS slate.

I examined quarterbacks in games with an opening total higher than 50 (z-score=+1.00 or higher) and an implied opposing team total of 26.5 or higher (z-score=+1.00 or higher). These quarterbacks are labeled “underdogs” in the table below.

I compared these results to quarterbacks in games with an opening total higher than 50 and an implied team total of 22.8 or higher (z-score=0.00 or higher). These quarterbacks are usually favorites in high-scoring games and would — in theory — be the opposing quarterbacks to the group above. These players are labeled “favorites” in the table below.

“Underdog” quarterbacks boast comparable average actual points, improved Plus/Minus scores, improved consistency, depressed ownership and depressed DraftKings pricing compared to “favorites” in these contests.

For the Week 17 DFS slate, we have two games that match the parameters above: The Raiders at Chiefs and the 49ers at Rams. Patrick Mahomes and Jared Goff both fit our trend as “favorites” in those contests, while Derek Carr and Nick Mullens fit our trend as “underdogs.”

Based on our results, there’s more DFS value in being contrarian in these contests. Rostering Carr or Mullens exposes you to a higher historical Plus/Minus and consistency, while granting you improved tournament viability due via depressed ownership and increased salary cap maneuverability via depressed DraftKings pricing.

#### Consider targeting:

• Derek Carr, Raiders: \$5,100 DraftKings
• Nick Mullens, 49ers: \$4,700 DraftKings

After this piece is published, FantasyLabs is likely to provide news updates on a number of players mentioned here. Be sure to stay ahead of your competition with our NFL news feed.

Photo Credit: Kyle Terada-USA TODAY Sports
Pictured Above: Nick Mullens

In the weekly Fantasy Trends, we leverage the Trends tool to find quarterbacks, wide receivers and running backs with notable data points for the upcoming DFS main slate. For more of our weekly football content, visit our NFL homepage.

In the final installment of this season’s series, I wanted to examine an assumption at the core of DFS analysis: Do higher Vegas totals promote improved quarterback performance?

I began my analysis by aggregating all opening totals in our database. That effort resulted in a 2,581-game sample size dating back to 2014. I assumed a normal distribution of Vegas totals, calculated mean and standard deviation for the data set, and produced z-scores for all opening totals in the distribution. Then I analyzed quarterback performance based on those resultant z-scores.

For your reference, below is the definition for a z-score, taken from www.investopedia.com.

A Z-score is a numerical measurement of a value’s relationship to the mean in a group of values. If a Z-score is 0, it represents the score as identical to the mean score. Z-scores may also be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean. Positive and negative scores also reveal the number of standard deviations that the score is either above or below the mean.

Standardizing Vegas totals in terms of z-scores allows us to objectively and statistically determine what a “high” Vegas total actually means — and how high a Vegas total must climb in order to deliver improved average performance for the quarterbacks in that game.

Our sample produced a mean opening total of 45.64 points and a standard deviation of 3.97 points. Based on the normal curve for sample distributions, 68% of NFL games since 2014 have featured Vegas totals ranging from 41.67 to 49.61 points.

### Results: QB Fantasy Performance Based on Opening Total

These results clearly show that high total games — those with a z-score of +1.00 or higher — correlate with enhanced quarterback performance. In games with totals above 53.5, the effect is even more pronounced; quarterbacks in those games produce an impressive Plus/Minus of +3.24.

However, those kinds of games are incredibly rare. In fact, there have been only 96 such games since 2014, which represents only 3.7% of our sample population. Moreover, games with a z-score of +1.0 or higher (50 or more points) constitute only 14.7% of our sample population.

The scarcity of these games compelled me to dig deeper. So, I proceeded to perform the same statistical treatment for implied team totals and implied opposing team totals.

### Results: QB Fantasy Performance Based on Implied Team Total

These results are perhaps more drastic than our previous data set. Quarterbacks with an implied team total of z=+2.00 or higher boast a Plus/Minus of +3.64, along with a dramatically-high ownership percentage of 14.2%. At the other end of our distribution, quarterbacks with implied team totals of 15.3 or lower (z=-2.00 or lower) have a Plus/Minus of -4.25 and consistency of just 20.5%

But I’d like to draw your attention to the z=0.00 to +1.00 range toward the middle of the distribution. Quarterbacks with implied team totals of 22.8 to 26.3 boast a respectable Plus/Minus of +1.01, but an average ownership percentage of just 5.3%.

That depressed ownership is one of the key results we’re looking for when attempting to identify value at any position. Quarterbacks in “smash spots” may boast elite Plus/Minus scores, but their ownership percentages are extremely high. Moreover, their average expected points are also high, indicating elevated DraftKings pricing. But, there exists a tier of quarterbacks slightly below these with deflated DraftKings pricing and ownership who still boast improved production. Those are the kinds of quarterbacks we’re searching for.

### Results: QB Fantasy Performance based on Implied Opposing Team Total

You might be wondering: “Why should we care about the implied point total for the opposing team?” But by using our Correlations tool, we can see that opposing quarterbacks have an r=0.59 correlation with quarterbacks in the same game.

Pearson’s correlation (r) measures the strength of relationship between two variables — in this case, the strength of relationship between one quarterback’s performance and the opposing quarterback’s performance. A strong correlation (the scientific standard for which is r=0.40, depending on the specific discipline) indicates a strong relationship between two variables.

In our case, that correlation suggests that if one quarterback is successful, the opposing quarterback’s performance also typically improves.

We’ve already established that quarterbacks in high total games — and with high implied team totals — boast elevated performance. So it follows that opposing quarterbacks in those games also should boast improved production.

While our data set is rife with parity across each z-score tranche, one notable result is average expected points. Quarterbacks playing against teams with high implied team totals feature lower average expected points — and thereby, lower DraftKings pricing. However, they still deliver average to above-average production, resulting in inflated Plus/Minus scores.

So there’s value in pivoting to the underdog opposing quarterback in these kinds of games.

### Targeting Underdog Opposing Quarterbacks

The final piece of my analysis was to combine elements from our results to highlight potential quarterback pivots for the Week 17 DFS slate.

I examined quarterbacks in games with an opening total higher than 50 (z-score=+1.00 or higher) and an implied opposing team total of 26.5 or higher (z-score=+1.00 or higher). These quarterbacks are labeled “underdogs” in the table below.

I compared these results to quarterbacks in games with an opening total higher than 50 and an implied team total of 22.8 or higher (z-score=0.00 or higher). These quarterbacks are usually favorites in high-scoring games and would — in theory — be the opposing quarterbacks to the group above. These players are labeled “favorites” in the table below.

“Underdog” quarterbacks boast comparable average actual points, improved Plus/Minus scores, improved consistency, depressed ownership and depressed DraftKings pricing compared to “favorites” in these contests.

For the Week 17 DFS slate, we have two games that match the parameters above: The Raiders at Chiefs and the 49ers at Rams. Patrick Mahomes and Jared Goff both fit our trend as “favorites” in those contests, while Derek Carr and Nick Mullens fit our trend as “underdogs.”

Based on our results, there’s more DFS value in being contrarian in these contests. Rostering Carr or Mullens exposes you to a higher historical Plus/Minus and consistency, while granting you improved tournament viability due via depressed ownership and increased salary cap maneuverability via depressed DraftKings pricing.

#### Consider targeting:

• Derek Carr, Raiders: \$5,100 DraftKings
• Nick Mullens, 49ers: \$4,700 DraftKings