Official NFL Megatool User Guide

by thesanction1

The NFL Megatool from is in its fourth iteration for week 7. Already it’s been downloaded and used by 1,000’s of fantasy sports fanatics to set lineups, make start/sit decisions, and dominate their daily fantasy sports contests. The biggest complaint to date? It does too much. It’s tough for users to understand what they can see with the tool, and all the ways they can use it to inform their decisions. There have been many requests for an instruction manual to explain how it works. Ask and ye shall receive.

In this post I’ll walk through how someone might use the Megatool to optimize their week 7 lineups. This post will be updated as Megatool functionality is expanded to explain each new feature in turn. Let’s get into it…

Setup: Running the Megatool

Step 1 – download and install the Wolfram CDF player from

The Megatool uses a free, innovative technology provided by Wolfram Research called Computable Document Format or CDF for short. The resemblance to PDF here is intended – this document type is like a PDF with dynamic data-driven content and user interface elements that can be adjusted on the fly. One of the coolest things about CDF technology is that it allows you go beyond static, single-graphic style communication of statistical findings to a more dynamic, user-driven two-way tool for generating insights from data. This plug-in is required to pull of this techno-magic; downloading and installing it is step one to using the Megatool.

As a side note here: CDF technology represents a fundamental change in how we interact with data that can often times be overwhelming to an average person. People are used to having data insights force fed to them in stale, static graphics – sometimes the freedom to explore the data dynamically and discover unique insights on your own can seem like a burden: “Just tell me what to do, dammit!” is not an uncommon complaint. If you want to be force fed your fantasy decisions, this tool is not for you.

Step 2 – download and open the tool from (note: this link changes weekly to incorporate the latest data. Eventually it will be embedded at Victiv as a web-based interface.)

Once you’ve downloaded and installed the CDF player, you are ready to download the tool and start making better fantasy decisions.

Explore: Using the Megatool in Analysis Mode

When you open the tool you should some version of this:

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This is a list of players at a position of your choice, ranked by a statistical category of your choice, normalized by some other statistical category of your choice. That’s a loaded statement, so let me unpack it one control at a time.

The first control element is the Megatool Mode, which can be set to either Analysis (analyzing historical data) or Projection (projecting fantasy points for next week). While Projection is certainly the most popular mode – more along the ‘just tell me what I need to do dammit!’ lines, there are plenty of important insights to be found in the Analysis mode.

The next control element is Position – you can chose from QB, RB, WR and TE (soon to include DST).

The next control, Stat of interest, allows you to select from a variety of statistics relevant to your selected position and determines the foundational stat on which you’ll be ranking and comparing players at this position.

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The full list of available stats as of the time of this post is:

  • Passing Attempts (QB only)
  • Passing Completions (QB only)
  • Passing Yards (QB only)
  • Passer Rating (QB only)
  • Rushing Attempts
  • Rushing Yards
  • Targets
  • Receptions
  • Receiving Yards
  • Opponent passer rating allowed (at position, QB only)
  • Opponent passing yards allow (at position, QB only)
  • Opponent rushing yards allowed (at position)
  • Opponent receptions allowed (at position)
  • Opponent receiving yards allowed (at position)
  • Opponent touchdowns allowed (at position)
  • Opponent fantasy points allowed (at position)

Note: opponent allowed statistics here represent a player’s strength of schedule with regard to that statistical category. So, for example, if the player’s ‘Opponent fantasy points allowed at position’ is 17.5 it means that for the time span specified, the athlete has faced opponents who, on average, have allowed 17.5 points in the 10 games preceding their matchup against this athlete. That’s a convoluted way to say if a guy has a high Opponent fantasy points allowed stat, he has been going up against opponents who give up a lot of points to his position – he’s had an easier strength of schedule. 

Once you’ve selected the stat you’re interested in, the graph and player list will update to reflect the rankings for that stat. So far so good, this in and of itself is a handy way to explore basic stats. But basic stats doesn’t win leagues. The Megatool has baked in statistical knowledge to allow you to normalize all these stats based on relevant normalization measures. In english – if you’ve selected ‘Rushing Yards’ as your stat of interest, the next control Normalize by allows you to normalize that number by ‘Rushing Attempts’ to rank all the RB’s by their yards per carry (YPC).

While YPC is an important stat, normalization in the Megatool allows you to see so, so much more. If your Stat of Interest is set to ‘Rushing Attempts’, you can normalize by ‘Team Rushing Attempts’ to see what percentage of a teams attempts are being handed off to that RB. Also interesting is to normalize by ‘Offensive Plays’ to figure out what percentage of the offensive snaps are going to that back. To show this in action – check out how far of an outlier DeMarco Murray is on this measure below, with 40% of the Cowboy’s offensive plays being rushing attempts to this workhorse:

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Immediately you can see some interesting insights here. Many people are blaming the emergence of Darren Sproles in the Eagle’s backfield for the falloff in LeSean McCoy’s fantasy numbers – but his rushing attempts as a percentage of the Eagle’s offense are 3rd highest for RB’s in the league! Also did you realize that running the ball through Arian Foster accounts for 36% of Houston’s offensive plays this year? This is just one setting, for one position, that I basically picked at random – but already you are discovering things that can help you make better fantasy decisions.

Note: notice that for players with an injury, the injury status is listed as well (in red). This injury status is current from whenever the tool is published, so final injury status should still be verified prior to making final start/sit decisions. 

I’ll do one more example here before moving. Austin Davis has emerged as a serviceable fantasy QB this year… So I was curious whether I should buy in, or disregard Davis’ performance so far as fluky. The Megatool can help clarify the issue. Check out how Austin’s opponent fantasy points allowed (that measure of strength of schedule I mentioned earlier) stacks up to the other QB’s:

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What do you know! In the games he’s played so far Austin has faced the easiest strength of schedule among all QB’s, allowing an average of 20.5 fantasy points per game to their opposition. So when you’re buddy wants to make a bar bet that Davis will end the year as a top 10 fantasy QB, you can take him up on it with confidence – as Austin faces tougher opposition it’s almost certain his productivity will come back down to earth.

Another interesting insight that stands out is Drew Brees being a very close #2 on this measure. Brees is having a notoriously bad fantasy year compared to expectations – and this graphic shows that his year is actually worse than it seems on the surface. Brees’ poor performance has come against defenses that are, on average, very favorable fantasy match ups for QBs. So am I buying low on Brees? Maybe… but I’m being extra cautious about it. Something just isn’t right in NO so far this year.

Last example of normalization so I can get the point across of just how powerful this tool can be. If you follow fantasy football it’s probably no surprise to you that the top two fantasy QB’s this year are Andrew Luck and Peyton Manning, who are averaging 27.6 and 24.5 points respectively so far in 2014. It might be slightly interesting to note that Phillip Rivers, whose career seemed all but finished just a few years ago, is eeking out a distant third (22.6 points per game) over Jay Cutler (22.2 points per game).

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But looking at raw fantasy points per game is a shallow way to understand the data, the statistical story is much deeper and nuanced. In order to contextualize the data, we should normalize it by the number of fantasy points allowed on average by opponents these QB’s have faced so far by setting the Normalize by  control to ‘OppFantasyPointsAllowed’. When we do this we see that Rivers actually surpasses Manning – having put up 137% of the average fantasy points his opponents were allowing in the 10-games prior to their matchup.

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It’s easiest to understand this normalized stat with an example. Let’s say that the opponents Rivers has faced were allowing an average of 16.5 fantasy points to QBs, and against those opponents he put up 22.6, he has averaged:

22.6 points produced / 16.5 average points allowed = 137% of the average fantasy points allowed by his opponents  

In english: when we adjust for strength of schedule, Philip Rivers emerges as the second best fantasy QB to date behind Andrew Luck. Notice that Andrew luck is averaging an astonishing 158% of the average allowed by his opponents. Even if Luck is facing a very stiff defense allowing only 15 fantasy points on average to opposing QBs, if he maintains this level of outperformance we’d expect a solid 23.7 point performance. Getting at these sorts of figures takes a lot of data, a lot of data juggling, and the application of some careful mathematics – but it’s the type of information that can take your fantasy performance to the next level in any format, and help you make the most informed possible decision in all situations.

There is one final control I’ve yet to review in Analysis mode: Time Span. This control designates which set of statistics you’re most interested in exploring and can be set as last year’s stats (2013 Season), this year to date (2014 Season YTD), the last 5 games, last week, or next week (which only includes the opponent strengths at position categories). Time Span setting does not impact how the other controls operate, it just allows the analysis to be run on different sets of historical data.

Dominate:  Using Megatool Projection Mode 

Now that you’ve got your mind around some of the things the tool can do, it’s time to flip it into ‘Projection’ mode and start making your fantasy decisions for next week. When you switch to Projection mode, the controls will change to the following:

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Position here is self explanatory and works the same as in Analysis mode.

Projection method allows you to choose between standard and strength of schedule adjusted projections. What does this mean? For a standard projection you are looking at each player’s productivity over the Time Span specified, and blending it using the setting of Matchup weight with the average fantasy points allowed by their opponent in their upcoming matchup. As an example, if Eli Manning has averaged 18.5 points in the last 5 games and he is going against Dallas who has only allowed 15 points on average to QB’s over the last 5 games, and the matchup weight is set at 20%, the projection for Eli will be calculated as:

18.5 x 80% + 15 * 20% = 17.8

So this is great – and blending average productivity with average opponent fantasy points allowed is a very sensible way to make a projection. Having this all in one simple application is definitely handy. But the Megatool doesn’t just want to be handy, it wants you to dominate your league. Ok, it’s a bit of software, it doesn’t want you to do anything. But I want you to dominate your league, and I wrote it – so whatever.

To best project fantasy productivity you need to account for the athlete’s historical strength of schedule in order to put their performance into context (remember Austin Davis above?). Setting the Projection method to ‘Strength of schedule adjusted’ changes the background equation from being additive to being multiplicative. So, if Philip Rivers has put up 137% of his opponent’s fantasy points allowed so far this year, and he’s going against an opponent who is allowing 18.7 points to opposing QB’s on average, and you set the Matchup weight to 30%, the strength of schedule adjusted projection method computes his projection as follows:

137%*(18.7*70%) + 18.8*30% = 23.5

In Projection mode the Time span is restricted to only 2014 Fantasy Points and Last 5 Games Fantasy Points – obviously using 2013 stats to project 2014 outcomes doesn’t make much sense.

Hopefully the power of this type of analysis is apparent to you, and you aren’t scared off by the nuances and complexity of the tool. Sports data analytics is not a straightforward task – in the Megatool I try to package up the detailed type of analysis many experts use in as simple and comprehensive interface as possible. The updates to the tool that are in the works include the addition of DST information and a method for creating complete Victiv rosters based off of your projection mode settings.

Please put any feedback in the comments, or Tweet to me @TheRotoquant.

GL in all your week 7 contests. We’re running $45K in free and guaranteed contests at Victiv, so you can use the insights gleaned from the Megatool to cash in today!