Off the Charts

Off the Charts

How Teams Records Change by the Month

The Giants dominate October while the Panthers shine in December. In Green Bay, the Pack has winning records in September, October, December, and January, but drop to 50% in November. The Raiders and Broncos steadily decline throughout the season. It could be weather, or playoff situation, or injury issues but the month of the year

The Giants dominate October while the Panthers shine in December. In Green Bay, the Pack has winning records in September, October, December, and January, but drop to 50% in November. The Raiders and Broncos steadily decline throughout the season. It could be weather, or playoff situation, or injury issues but the month of the year seems to have a considerable effect on some teams success. 

Of course, there are teams that are immune like the Patriots and Browns, obviously for different reasons. 

We compiled all NFL records since 2002 by month to create the graph below. You can view the results as either totals or percents. Use the drop down to change teams.



Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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How the Super Bowl Odds Changed Through the Off Season

Super Bowl odds change as recreational and sharp bettors back their favorite team. This is a look at how the odds to win Super Bowl 53 have changed over the course of the last six months. See how the odds have shifted from post Super Bowl, to the draft and now through the preseason. The

Super Bowl odds change as recreational and sharp bettors back their favorite team. This is a look at how the odds to win Super Bowl 53 have changed over the course of the last six months. See how the odds have shifted from post Super Bowl, to the draft and now through the preseason. The Cardinals have slid from 50/1 in February to 150/1 now, while the Chargers have improved to 16/1 after being posted at 35/1 initally. See how the rest of the teams stand:

Data provided by Bovada.


Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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Reports: Vikings’ Williams fined $20K for roughing Jaguars QB

Reports: Vikings' Williams fined $20K for roughing Jaguars QB

Minnesota Vikings linebacker Antwione Williams is paying for his aggressive tendencies as the NFL continues to target players who take aim at quarterbacks.

Williams was reportedly fined $20,054 for roughing Jacksonville Jaguars quarterback Cody Kessler in an Aug. 18 preseason game

Reports: Vikings’ Williams fined $20K for roughing Jaguars QB

Minnesota Vikings linebacker Antwione Williams is paying for his aggressive tendencies as the NFL continues to target players who take aim at quarterbacks.

Williams was reportedly fined $20,054 for roughing Jacksonville Jaguars quarterback Cody Kessler in an Aug. 18 preseason game because he appeared to use extra force by using his body weight to drive the passer into the ground.

Williams, who was penalized for the infraction, voiced his displeasure Thursday on Twitter, saying, “Really got fined today for this” in response to a clip of the play.

Vikings coach Mike Zimmer didn’t agree with the officials when the penalty was called, but took another stance following the Jaguars’ 14-10 preseason victory.

“After I calmed down a little bit, I looked at it, and [Williams’] head was to the side and he was going to the side,” Zimmer said. “If he would have just rolled, but he kind of pumped him into the turf. I actually think that was a good call.”

–Field Level Media

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Is Playoff Experience an Indicator of Future Success?

Every postseason, young teams are counted out from contention because they don't have "playoff experience," but does that really matter?

To answer that question we first, we compared Super Bowl wins and playoff appearances. There are 9 teams that have made the playoffs at least 8 times since 2002. All but one of the teams

Every postseason, young teams are counted out from contention because they don’t have “playoff experience,” but does that really matter?

To answer that question we first, we compared Super Bowl wins and playoff appearances. There are 9 teams that have made the playoffs at least 8 times since 2002. All but one of the teams won at least one Super Bowl. The only team missing was the Falcons and we all know how that turned out. 

Secondly, we compared Super Bowl Wins and Playoff Win Percentage. All of the teams that have won the Super Bowl since 2002 have won 50% or more of their postseason games, regardless of the number of playoff appearances they’ve had.

While it may not be the perfect indicator, Playoff Experience is certainly a strong metric for predicting the Super Bowl winner.

The graphic below compares the number of Playoff Appearances and Postseason Win percentage for each team, also indicating whether or not they’ve won a Super Bowl since 2002. Hover over the graph to split into 4 quadrants, revealing the number of teams, and the percent of Super Bowl winners.



Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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Teams That Can’t Buy Success – A Look at the NFL’s Longest Droughts

Days before Super Bowl III, Joe Namath famously guaranteed his New York Jets would defeat the heavily favored Baltimore Colts. His guarantee came true, and New York fans rejoiced. 49 years later, the Jets faithful have had little to celebrate, apart from their postseason win over the Patriots in January of 2011. It's been a

Days before Super Bowl III, Joe Namath famously guaranteed his New York Jets would defeat the heavily favored Baltimore Colts. His guarantee came true, and New York fans rejoiced. 49 years later, the Jets faithful have had little to celebrate, apart from their postseason win over the Patriots in January of 2011. It’s been a tough go of it, but maybe things will turn around for them soon.

The last time the Browns won their division, it was called the AFC Central, and the year was 1989. Since then, they’ve had only 3 winning seasons.

For most fans, it’s bad news to hear the term Drought and their favorite team in the same conversation. We’ve compiled data on each team, and how long it’s been since their last:

  • Divisional Title
  • Playoff Appearance
  • Playoff Win
  • Super Bowl Appearance
  • Super Bowl Win

Use the drop down menu to change categories.



Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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Answering the Fantasy Football Players Injury Dilemma

All fantasy football players have had this dilemma:

Player X is my best option at WR 2 but he’s coming off of that groin injury and took limited reps in practice this week… should I start him or go with my backup who averages a couple less points?

The real question

All fantasy football players have had this dilemma:

Player X is my best option at WR 2 but he’s coming off of that groin injury and took limited reps in practice this week… should I start him or go with my backup who averages a couple less points?

The real question being asked is: what effect does being on the injury report have on average weekly performance when a player is still active for game day?

To analyze this question in an objective way, we need to look at the numbers. Specifically – we need to contrast the average or expected output of Player X when healthy (defined here as not-listed on injury report or full-participant in weekly practice) vs average or expected output of Player X when injured (defined here as listed on official injury report for the week and/or limited practice reps). But Player X is a pretty small sample size so lets aggregate the differences across the league by position and injury type. The goal is to get a better overall understanding of whether certain positions are affected more by injuries, or if certain types of injuries have a more noticeable impact on fantasy football performance.

For this information – I downloaded the full offensive stat list for each team from fantasydata.com and grabbed what I could for injury report data from nfl.com/injuries which, unfortunately, was limited to the 2017 season only. As you’ll see from the data, even an entire NFL season boils down to a pretty small sample size but there are still relevant insights to be gained.

The criteria which we used for the analysis is as follows:

Hurt: Injury listed on injury report but player active and took snaps in game

Healthy: Full practice participant with no injury specified, or not listed at all on injury report

Aggregated by player average points (standard league) when healthy vs player average points when hurt. (weeks that a player left game early and did not return the following week were removed so as not to distort the ‘healthy’ averages)

Since different players obviously average different hauls in points, we need to look at the average difference in points, isolated by player. We can then combine these across the league by position group and injury type to get a better look at the overall picture.

I’m working on creating an unbiased metric for opposing defenses so that we can more fairly drill down to how different injuries may affect specific players, however for now this will serve as a good overall indicator in the average change in production (points) between healthy vs hurt – as it would be highly improbable that all weeks when players ‘played hurt’ aligned with weaker defenses and/or all weeks when players ‘played healthy’ aligned with better ones (or vice versa).

You might have noticed that I refrained from using the word ‘drop’ or ‘decrease’ when referencing the average change week-to-week when healthy vs. hurt … and the reason for that is the available evidence is inconclusive that you should expect any change as long as said player is listed as active.

The overall distribution is pretty normal (both positive and negative) and most of the data are well within the standard margin of error week to week for each position type (about 4.18 points overall). Additionally, in most cases the higher frequency injuries (larger sample size) were closer to the healthy averages when aggregated – meaning there’s a correlation between less data and a greater deviation from the norm, and vice versa.

Avg Standard Deviation of weekly Fantasy Points by position: (Standard League, from this dataset)

QB  +-  6.49
RB  +-  4.64
TE   +-  3.08
WR +-  4.01

This further suggests that the more extreme deviations (in the data) may just be one-offs. In fact every data point outside of the 4-point margin had only 1 or 2 occurrences in 2017 to draw from and probably don’t qualify as hard evidence of any trends.

I think that may be  interesting in and of itself. This suggests that there shouldn’t be any expected change in production as long as a player is active. This also makes sense from the team’s standpoint, if you consider that by the time they allow a player to participate on gameday they expect his performance to be close-to-par. We also know that essentially every player is ‘hurting’ somewhere (from normal wear-and-tear) so ‘playing hurt’, as defined here, may be closer to the norm than most fans realize.

The net was about a 0.40 point overall reduction on average, but again with plenty of examples where players performed better than normal. It’s certainly not conclusive, however, and would be very interesting to see if this holds true over a 10 year period or more – or if the NFL has gotten better over time at diagnosing when a player is ready to come back.

Avg Change in Standard League Points (Healthy -> Inj) by Position, 2017 season

Position FantasyPoints SampleSize
RB -1.19 25
TE -0.65 18
WR -0.13 51
QB +2.74  4

Avg Change in Standard League Points (Healthy -> Inj) by Injury, 2017 season

Injury FantasyPoints SampleSize
Right Shoulder -4.66 1
Foot -4.23 1
Neck -3.97 3
Illness -3.08 2
Rib -2.92 2
Shoulder -2.80 8
Thumb -2.79 1
Groin -2.35 6
Knee -1.75  16
Toe
-1.30
3
Hamstring
-1.12
7
Abdomen
-0.95
1
Hip
-0.51
8
Calf
+0.17
5
Back
+0.43 1
Ankle
+1.15
15
Ribs
+2.54
5
Concussion
+2.71
8
Quadricep
+3.06
4
Hand
+4.82
2

*****

Stay tuned for the other side of this as we take a look at defensive players in a future post. One thing I’m curious of is the potential case that offenses attack a defensive player (or his side of the field) more often when they are known to be injured – which may lead to an increase in opportunities to make plays and accumulate points.

For reference, here is a link to the NFL’s official personnel injury report policy for the 2017 season.

Contributor to National Football Post & sports nut with training in statistics, machine learning, and data analysis from Galvanize – Seattle campus. Alumni of University of Colorado and University of Washington. Occasional boater, skier, and golfer.

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NFL Arrests by Year Since 2000

This is part two of our series comparing how different factors have influenced the arrest rate in the NFL over the years. Part one looked at crimes by month committed. With this post you can see things like how DUI's have gone down dramatically since the rise of Uber and Lyft

This is part two of our series comparing how different factors have influenced the arrest rate in the NFL over the years. Part one looked at crimes by month committed. With this post you can see things like how DUI’s have gone down dramatically since the rise of Uber and Lyft and how drug offenses increased after the NFL strengthened the steroid policy in 2005. 

When looking at this data it is important to remember that the crime rate in the NFL is typically less than the overall crime rate for men from ages 20-39, according to a study by the University of Texas. Mess around with the data and see what inferences you can draw, then let us know on our Twitter

Elise is a data scientist and a football fanatic. She was raised in Seattle where her love for sports grew as she followed the Seahawks, Mariners, and Sonics. After graduating high school, Elise attended High Point University in North Carolina for two years, then before her Junior year of college, she decided to transfer to the University of Washington for their undergraduate mathematics program. She graduated from UW in December 2017 then not long after completed the Data Science Immersive program at Galvanize in Seattle. Elise is looking forward to another competitive fantasy football season as she works on building a predictive model for NFL rushing yards.

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Wild Card Appearances (2002-2018)

Since the NFL was restructured in 2002, there are four teams that have not played in the postseason as a wild card. The Patriots, Bears, Texans and Buccaneers have either won their division or missed the playoffs completely.

In the same time frame, the Patriots have made 14 postseason appearances. Combined, the Bears, Bucs and

Since the NFL was restructured in 2002, there are four teams that have not played in the postseason as a wild card. The Patriots, Bears, Texans and Buccaneers have either won their division or missed the playoffs completely.

In the same time frame, the Patriots have made 14 postseason appearances. Combined, the Bears, Bucs and Texans have made 10 appearances. 

Amount of wild card appearances is a good metric for the continued strength of a division as a whole. The graphic below displays each division and the number of wild card appearances since 2002. The AFC North comes out on top, boasting five consecutive seasons from 2008-2012 in which they sent at least two teams to the postseason. The AFC East and NFC West each finished with only six appearances.



Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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2017 Wins and Losses

Following a loss to the Pittsburgh Steelers on December 31st 2017, the Cleveland Browns completed their perfect 0-16 season. On the same day, the Baltimore faithful watched in anguish as the Ravens gave up a last-minute touchdown to the Bengals, essentially handing their wild card spot to the Buffalo Bills.

After starting the season with

Following a loss to the Pittsburgh Steelers on December 31st 2017, the Cleveland Browns completed their perfect 0-16 season. On the same day, the Baltimore faithful watched in anguish as the Ravens gave up a last-minute touchdown to the Bengals, essentially handing their wild card spot to the Buffalo Bills.

After starting the season with 4 consecutive losses, the Los Angeles Chargers finished the season with 9 wins (and almost nabbed themselves an AFC wild card spot). The 49ers started the season in a similar fashion, but finished on a 5-game winning streak, defeating three playoff teams.

You may not be a fan of any of the aforementioned teams, but the information probably sounded a bit familiar. That’s because wins and losses tend to be the only stats that anyone remembers. The graphic below reveals the wins and losses for each team in 2017, ranked from greatest to least. It also allows you to filter based on divisional and conference games.



Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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NFL Arrests by Month

Since the turn of the century there have been 1,010 arrests of NFL players. While that number may seem high, it's actually less than the US average for men ages 20-39. Because they are constantly in the spotlight, the general public hears about these arrests frequently. After collecting the data and categorizing it

Since the turn of the century there have been 1,010 arrests of NFL players. While that number may seem high, it’s actually less than the US average for men ages 20-39. Because they are constantly in the spotlight, the general public hears about these arrests frequently. After collecting the data and categorizing it in a variety of ways, the National Football Post will be releasing a series of visualizations starting with NFL arrests by month. 

You can play around with the data to sort by type of crime and see what inferences you can draw. Some categories have a lot of arrests, like drug crimes, which dramatically increase in the offseason, when tests become sporadic. Some categories only have a single arrest in the last 18 years. 

Mobile users click here

Elise is a data scientist and a football fanatic. She was raised in Seattle where her love for sports grew as she followed the Seahawks, Mariners, and Sonics. After graduating high school, Elise attended High Point University in North Carolina for two years, then before her Junior year of college, she decided to transfer to the University of Washington for their undergraduate mathematics program. She graduated from UW in December 2017 then not long after completed the Data Science Immersive program at Galvanize in Seattle. Elise is looking forward to another competitive fantasy football season as she works on building a predictive model for NFL rushing yards.

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Comparing Team vs Divisional Wins

It's no secret that the New England Patriots have pretty much owned the AFC East for the past decade. However, did you know that the rest of the AFC East have averaged fewer than 8 wins in the same time frame? If the goal is to make the playoffs, it certainly helps when the rest

It’s no secret that the New England Patriots have pretty much owned the AFC East for the past decade. However, did you know that the rest of the AFC East have averaged fewer than 8 wins in the same time frame? If the goal is to make the playoffs, it certainly helps when the rest of your division tends to produce losing records. The flip side of the AFC East is the AFC North. The Bengals, Steelers, and Ravens have had many strong seasons, often sending two of the three teams to the playoffs (in 2011, all three teams advanced to the playoffs).

The graphic below allows you to choose a division and a team, and it displays the wins for the selected team vs. the average wins for the rest of the division.



Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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How Every Team and Division Has Fared in NFC vs. AFC Matchups

In 2018, we'll get to see Tom Brady and Aaron Rodgers battle it out on the field for the second - and possibly final - time. Fans have had to wait 4 years since the last matchup because of the NFL's division-heavy schedule. Every season, there are 64 regular-season games in which a team from

In 2018, we’ll get to see Tom Brady and Aaron Rodgers battle it out on the field for the second – and possibly final – time. Fans have had to wait 4 years since the last matchup because of the NFL’s division-heavy schedule. Every season, there are 64 regular-season games in which a team from the NFC plays a team from the AFC. Some teams, like the Patriots and Cowboys have fared well in these inter-conference matchups over the past 4 seasons. Some other teams haven’t been so fortunate. This graphic shows the success of teams and divisions over the past four years. Play around with the drop-down lists, and hover over the bars to see the results!



Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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All the NFL Suspensions for 2018 in One Place

Jameis Winston is the latest player to be suspended by the NFL after his incident with an Uber driver last winter. Jameis' incident is not a typical case, most suspensions in the NFL are drug-related.

Whether player-enhancing or player-relaxing, most suspensions fall under those two categories. As of right now there are 12 players suspended

Jameis Winston is the latest player to be suspended by the NFL after his incident with an Uber driver last winter. Jameis’ incident is not a typical case, most suspensions in the NFL are drug-related.

Whether player-enhancing or player-relaxing, most suspensions fall under those two categories. As of right now there are 12 players suspended for PEDs and two for marijuana-related charges.

Below is a list of all the players currently suspended, their charges and the length of their suspensions:

Player Team Position Reason Length (Games)
Aaron Jones Green Bay Packers RB Marijuana Possession 2
Cayleb Jones Minnesota Vikings WR PEDs 4
Corey Liuget Los Angeles Chargers DT PEDs 4
David Irving Dallas Cowboys DT PEDs 4
Demetrius Harris Kansas City Chiefs TE Marijuana arrest 1
Donald Stephenson Cleveland Browns LT PEDs 4
Jameis Winston Tampa Bay Buccaneers QB Uber Incident 3
Jamon Brown Los Angeles Rams G Substance Abuse 2
Josh Huff New Orleans Saints WR Marijuana arrest w/ firearm in vehicle 2
Josh Mauro New York Giants DT PEDs 4
Julian Edelman New England Patriots WR PEDs 4
Kentrell Brothers Minnesota Vikings LB PEDs 4
Mark Ingram New Orleans Saints RB PEDs 4
Robert Turbin Indianapolis Colts RB PEDs 4
Roy Miller Kansas City Chiefs DT “Undisclosed” 6
Rueben Foster San Francisco 49ers LB Marijuana and weapon misdemeanors 2
Thomas Davis Carolina Panthers LB PEDs 4
Vadal Alexander Oakland Raiders OL PEDs 4
Victor Bolden San Francisco 49ers WR PEDs 4
Vontaze Burfict Cincinnati Bengals LB PEDs 4

This table will be consistently updated as new players are suspended

Added notes:

Vontaze Burfict: Claimed it was Adderall in his defense hearing. That would be substance abuse not a PED under NFL rules. The NFL denied his appeal.

Mark Ingram: Claims he tested positive for a substance that is allowed under the NFL rules. The NFL denied his appeal.

Josh Huff: Released by the Eagles after his arrest. He was arrested for unlawful possession of a firearm and marijuana under 50 grams when he was pulled over for speeding.

Roy Miller: He was waived from the Chiefs after being arrested on domestic battery charges. While the NFL declined to say that was the reason for his suspension, it’s not hard to connect the dots.

Jameis Winston: Last February, an Uber driver alleged that Winston grabbed her crotch. The investigation lasted seven months but it was reported he was receiving a three-game suspension on June 21st.

Ted works more on the business side of National Football Post while contributing the occasional article. He graduated with honors in Marketing and Economics from Seattle University. A lifelong fan of Boston sports teams and avid cyclist Ted can be found on one of Seattle’s bike paths when not watching sports.

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Success Before and After a Super Bowl Win

After back-to-back 7-9 seasons, would anyone have predicted the Eagles would win Super Bowl LII? Did anyone believe that the Giants would miss the playoffs in the three seasons following the team's win over the Patriots in SB XLVI?

Predicting the success of a Super Bowl winner before the next season begins is far from

After back-to-back 7-9 seasons, would anyone have predicted the Eagles would win Super Bowl LII? Did anyone believe that the Giants would miss the playoffs in the three seasons following the team’s win over the Patriots in SB XLVI?

Predicting the success of a Super Bowl winner before the next season begins is far from an exact science. Unless it’s the Patriots, who will lose a game near the end of the regular season to a less-than-average team, soar through the playoffs and then play in an exciting Super Bowl. Also, there will be a game in there where one of their four running backs scores three touchdowns and it will be against your fantasy football team. Classic Pats. But, if you aren’t a diehard Patriots fan, your team’s season won’t be as predictable.

We decided to take a look at how teams have fared in the three years before and after they won a Super Bowl since 2008. Use the dropdown box to select a year, and hover over the dots to see the results.



Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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Visualizing NFL Shutouts Since 2008

Not even a field goal. In the NFL, shutouts are rare and represent domination for the defense and an offense that is in sorry shape. A high placing on the y-axis shows a team who has historically struggled on both sides (Browns). A high placing on the x-axis is a team with a stellar defense

Not even a field goal. In the NFL, shutouts are rare and represent domination for the defense and an offense that is in sorry shape. A high placing on the y-axis shows a team who has historically struggled on both sides (Browns). A high placing on the x-axis is a team with a stellar defense who knows how to score (Seahawks). Strong on both is a team with a great defense but bad offense (Rams).

How has your favorite team fared when it comes to shutouts? Check out the graphic below to find out:


Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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A Comparison of 2018 NFL Draft Grades

Let's imagine for a moment that you're an Arizona Cardinals fan, and ESPN's Mel Kiper Jr. is your go-to source for NFL information. You were probably a bit frustrated when he gave your team a C+ for their overall 2018 draft grade. You call your neighbor to tell him the bad news, but he tells

Let’s imagine for a moment that you’re an Arizona Cardinals fan, and ESPN’s Mel Kiper Jr. is your go-to source for NFL information. You were probably a bit frustrated when he gave your team a C+ for their overall 2018 draft grade. You call your neighbor to tell him the bad news, but he tells you that Gennaro Filice of NFL.com gave the Cardinals an A. You hang up the phone, pondering the question: “How can two experts assign such different grades?”

This is just one example of how a reader’s perception of their team can be skewed by the sites they favor. The goal of this data visualization is to compare draft grades from five notable websites (ESPN, Yahoo, Sports Illustrated, CBS, and NFL.com) and see just how much their results can vary based on the same information.

Some teams, like the Chargers, stayed consistent across all the sites. Others, like the Saints, proved pretty divisive.
Use the dropdown lists to compare different media outlets. The darker the circle, the greater the grade difference. Play around with the data and see what interesting conclusions you can draw about your favorite team, or your favorite analyst.



Sources


Martin is a data analyst that has been applauded for his ability to make the complex simple. He grew up on a farm in northern Vermont and spent his summers helping his mom lead llama treks at Smugglers’ Notch Resort.

Martin graduated from University of Vermont with a degree in Mathematics. After graduation he left Vermont to work for an educational nonprofit called City Year for two years, and followed that up by attending the data science immersive program at Galvanize in Denver. He is an avid Green Bay Packer fan, and spends his free time playing football and soccer.

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