This article is part of our According to the Data series.
As a follow-up to an earlier piece about Kickers and Defense, here is a deeper dig on some kicker draft strategies. Usually drafting a kicker is the last thing I am thinking about on draft day. However, everyone needs a kicker. With that in mind, who should be targeted? The prevailing theory is to simply nab a kicker for a team that will be an offensive powerhouse like Denver, Philadelphia, New England or Green Bay or a great defense like Seattle, Carolina and Arizona. It seems straightforward and logical, but let's see if the data supports the theory.
Data
Three pieces of data need to be examined; the kicker data, offensive team data, and defense team data.
Kicker Data
I analyzed the last three years of data for kickers. This entailed FGs made as per distance and extra points scored. I converted three seasons of data into fantasy points for four common league providers (Yahoo, ESPN, NFL.com, and CBS). For teams that had more than one kicker in a year, I added their fantasy points together to get a "team" kicker. Next, I ranked the kickers for each of the respective years based on the four scoring systems with "1" being the highest point total, and "32" being the lowest. From these four rankings, I averaged four scoring systems to provide an average rank for each of the kickers for the three seasons. Finally, I calculated the three-year average for each kicker.
Below is a table of the
As a follow-up to an earlier piece about Kickers and Defense, here is a deeper dig on some kicker draft strategies. Usually drafting a kicker is the last thing I am thinking about on draft day. However, everyone needs a kicker. With that in mind, who should be targeted? The prevailing theory is to simply nab a kicker for a team that will be an offensive powerhouse like Denver, Philadelphia, New England or Green Bay or a great defense like Seattle, Carolina and Arizona. It seems straightforward and logical, but let's see if the data supports the theory.
Data
Three pieces of data need to be examined; the kicker data, offensive team data, and defense team data.
Kicker Data
I analyzed the last three years of data for kickers. This entailed FGs made as per distance and extra points scored. I converted three seasons of data into fantasy points for four common league providers (Yahoo, ESPN, NFL.com, and CBS). For teams that had more than one kicker in a year, I added their fantasy points together to get a "team" kicker. Next, I ranked the kickers for each of the respective years based on the four scoring systems with "1" being the highest point total, and "32" being the lowest. From these four rankings, I averaged four scoring systems to provide an average rank for each of the kickers for the three seasons. Finally, I calculated the three-year average for each kicker.
Below is a table of the average kicker ranking per year, sorted by the three-year-rank average.
| 2011 | 2012 | 2013 | ||
|---|---|---|---|---|
| Team | Avg K Rank | Avg K Rank | Avg K Rank | 3 Yr Rank Avg |
| NE | 3 | 2 | 1 | 2.0 |
| SF | 1 | 11.25 | 6 | 6.1 |
| BAL | 12.25 | 6.25 | 3 | 7.2 |
| DAL | 6 | 11.75 | 9 | 8.9 |
| GB | 5 | 19 | 5.75 | 9.9 |
| HOU | 5.75 | 5.75 | 25.5 | 12.3 |
| ATL | 13.5 | 3 | 20.75 | 12.4 |
| NO | 2 | 19.25 | 16.5 | 12.6 |
| CHI | 10 | 15.25 | 13.5 | 12.9 |
| MIN | 22 | 1 | 16.25 | 13.1 |
| DEN | 30.5 | 8.5 | 2 | 13.7 |
| SEA | 18.75 | 17.75 | 4.75 | 13.8 |
| CIN | 9.75 | 9 | 24 | 14.3 |
| OAK | 4.25 | 12.75 | 26.5 | 14.5 |
| DET | 10.25 | 6 | 28.25 | 14.8 |
| SD | 9.5 | 31.25 | 6.25 | 15.7 |
| TEN | 9 | 21.25 | 18.25 | 16.2 |
| IND | 28 | 16.25 | 6 | 16.8 |
| PIT | 23.25 | 16 | 13 | 17.4 |
| BUF | 18.75 | 25.75 | 10 | 18.2 |
| TB | 22 | 9 | 25.75 | 18.9 |
| NYG | 27.25 | 4.25 | 28 | 19.8 |
| PHI | 16.5 | 22 | 21.75 | 20.1 |
| MIA | 16.25 | 26.75 | 20.5 | 21.2 |
| NYJ | 23.5 | 28.5 | 11.5 | 21.2 |
| CLE | 23.25 | 12.25 | 30 | 21.8 |
| CAR | 20 | 30.5 | 15.25 | 21.9 |
| ARI | 30.5 | 24.5 | 11.25 | 22.1 |
| KC | 28 | 23.75 | 18.25 | 23.3 |
| STL | 32 | 23 | 21.75 | 25.6 |
| WAS | 15 | 31 | 31.75 | 25.9 |
| JAC | 25 | 28.5 | 31 | 28.2 |
Offensive Data
Over the same three-year time span, the data for the number of offensive touchdowns were gathered for the 32 teams. This information was then ranked for the league, with "1" being the team with the most offensive TDs and "32" being the team with the least. This data, along with the three-year average of this ranking, is shown in the table below.
| 2011 | 2012 | 2013 | ||
|---|---|---|---|---|
| Team | Off Rank | Off Rank | Off Rank | 3 Yr Rank Avg |
| NO | 2 | 2 | 3 | 2.3 |
| NE | 3 | 1 | 7 | 3.7 |
| GB | 1 | 3 | 9 | 4.3 |
| DEN | 20 | 3 | 1 | 8.0 |
| DET | 4 | 13 | 7 | 8.0 |
| CAR | 5 | 10 | 15 | 10.0 |
| ATL | 7 | 6 | 18 | 10.3 |
| DAL | 11 | 16 | 5 | 10.7 |
| PHI | 9 | 23 | 2 | 11.3 |
| CIN | 20 | 13 | 4 | 12.3 |
| SD | 7 | 22 | 10 | 13.0 |
| NYG | 6 | 6 | 27 | 13.0 |
| MIN | 11 | 19 | 10 | 13.3 |
| SEA | 23 | 8 | 10 | 13.7 |
| SF | 19 | 10 | 14 | 14.3 |
| HOU | 11 | 9 | 29 | 16.3 |
| CHI | 25 | 21 | 5 | 17.0 |
| WAS | 26 | 5 | 21 | 17.3 |
| PIT | 17 | 18 | 18 | 17.7 |
| BAL | 14 | 13 | 29 | 18.7 |
| BUF | 14 | 17 | 25 | 18.7 |
| OAK | 14 | 23 | 22 | 19.7 |
| IND | 28 | 19 | 15 | 20.7 |
| TEN | 23 | 27 | 15 | 21.7 |
| TB | 27 | 10 | 28 | 21.7 |
| MIA | 20 | 23 | 23 | 22.0 |
| ARI | 18 | 31 | 20 | 23.0 |
| NYJ | 10 | 29 | 31 | 23.3 |
| KC | 31 | 32 | 10 | 24.3 |
| CLE | 30 | 23 | 26 | 26.3 |
| STL | 32 | 27 | 23 | 27.3 |
| JAC | 29 | 30 | 32 | 30.3 |
Defensive Data
Over the 2011. 2012 and 2013 seasons, the data for the number of touchdowns allowed by the defense were gathered for the 32 teams. This information was then ranked for the league with "1" being the team allowing the least TDs and "32" being the team allowing the most. This data, along with the three-year average of this ranking, is shown in the table below.
| 2011 | 2012 | 2013 | ||
|---|---|---|---|---|
| Team | Def Rank | Def Rank | Def Rank | 3 Yr Rank Avg |
| SEA | 5 | 1 | 1 | 2.3 |
| SF | 3 | 3 | 4 | 3.3 |
| BAL | 1 | 7 | 7 | 5.0 |
| MIA | 8 | 4 | 5 | 5.7 |
| CIN | 13 | 6 | 3 | 7.3 |
| PIT | 2 | 4 | 19 | 8.3 |
| ARI | 8 | 10 | 9 | 9.0 |
| NYJ | 8 | 16 | 12 | 12.0 |
| HOU | 4 | 12 | 21 | 12.3 |
| CHI | 8 | 2 | 27 | 12.3 |
| CAR | 29 | 11 | 2 | 14.0 |
| DEN | 13 | 7 | 24 | 14.7 |
| ATL | 13 | 7 | 25 | 15.0 |
| DET | 18 | 21 | 9 | 16.0 |
| NYG | 26 | 14 | 8 | 16.0 |
| NO | 13 | 32 | 5 | 16.7 |
| TEN | 7 | 30 | 14 | 17.0 |
| KC | 19 | 23 | 9 | 17.0 |
| CLE | 5 | 25 | 23 | 17.7 |
| STL | 22 | 12 | 19 | 17.7 |
| NE | 24 | 16 | 14 | 18.0 |
| SD | 19 | 19 | 16 | 18.0 |
| IND | 27 | 16 | 12 | 18.3 |
| DAL | 12 | 21 | 30 | 21.0 |
| GB | 24 | 15 | 26 | 21.7 |
| JAC | 13 | 23 | 29 | 21.7 |
| PHI | 22 | 28 | 16 | 22.0 |
| MIN | 27 | 19 | 31 | 25.7 |
| WAS | 19 | 26 | 32 | 25.7 |
| BUF | 31 | 31 | 18 | 26.7 |
| TB | 32 | 27 | 21 | 26.7 |
| OAK | 29 | 29 | 28 | 28.7 |
Combined Data (Sorted by Kicker Three-Year-Rank Avg)
| 2011 | 2012 | 2013 | Kicker | Offense | Defense | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Team | Avg K Rank | Off Rank | Def Rank | Avg K Rank | Off Rank | Def Rank | Avg K Rank | Off Rank | Def Rank | 3 Yr Rank Avg | 3 Yr Rank Avg | 3 Yr Rank Avg |
| NE | 3 | 3 | 24 | 2 | 1 | 16 | 1 | 7 | 14 | 2.0 | 3.7 | 18.0 |
| SF | 1 | 19 | 3 | 11.25 | 10 | 3 | 6 | 14 | 4 | 6.1 | 14.3 | 3.3 |
| BAL | 12.25 | 14 | 1 | 6.25 | 13 | 7 | 3 | 29 | 7 | 7.2 | 18.7 | 5.0 |
| DAL | 6 | 11 | 12 | 11.75 | 16 | 21 | 9 | 5 | 30 | 8.9 | 10.7 | 21.0 |
| GB | 5 | 1 | 24 | 19 | 3 | 15 | 5.75 | 9 | 26 | 9.9 | 4.3 | 21.7 |
| HOU | 5.75 | 11 | 4 | 5.75 | 9 | 12 | 25.5 | 29 | 21 | 12.3 | 16.3 | 12.3 |
| ATL | 13.5 | 7 | 13 | 3 | 6 | 7 | 20.75 | 18 | 25 | 12.4 | 10.3 | 15.0 |
| NO | 2 | 2 | 13 | 19.25 | 2 | 32 | 16.5 | 3 | 5 | 12.6 | 2.3 | 16.7 |
| CHI | 10 | 25 | 8 | 15.25 | 21 | 2 | 13.5 | 5 | 27 | 12.9 | 17.0 | 12.3 |
| MIN | 22 | 11 | 27 | 1 | 19 | 19 | 16.25 | 10 | 31 | 13.1 | 13.3 | 25.7 |
| DEN | 30.5 | 20 | 13 | 8.5 | 3 | 7 | 2 | 1 | 24 | 13.7 | 8.0 | 14.7 |
| SEA | 18.75 | 23 | 5 | 17.75 | 8 | 1 | 4.75 | 10 | 1 | 13.8 | 13.7 | 2.3 |
| CIN | 9.75 | 20 | 13 | 9 | 13 | 6 | 24 | 4 | 3 | 14.3 | 12.3 | 7.3 |
| OAK | 4.25 | 14 | 29 | 12.75 | 23 | 29 | 26.5 | 22 | 28 | 14.5 | 19.7 | 28.7 |
| DET | 10.25 | 4 | 18 | 6 | 13 | 21 | 28.25 | 7 | 9 | 14.8 | 8.0 | 16.0 |
| SD | 9.5 | 7 | 19 | 31.25 | 22 | 19 | 6.25 | 10 | 16 | 15.7 | 13.0 | 18.0 |
| TEN | 9 | 23 | 7 | 21.25 | 27 | 30 | 18.25 | 15 | 14 | 16.2 | 21.7 | 17.0 |
| IND | 28 | 28 | 27 | 16.25 | 19 | 16 | 6 | 15 | 12 | 16.8 | 20.7 | 18.3 |
| PIT | 23.25 | 17 | 2 | 16 | 18 | 4 | 13 | 18 | 19 | 17.4 | 17.7 | 8.3 |
| BUF | 18.75 | 14 | 31 | 25.75 | 17 | 31 | 10 | 25 | 18 | 18.2 | 18.7 | 26.7 |
| TB | 22 | 27 | 32 | 9 | 10 | 27 | 25.75 | 28 | 21 | 18.9 | 21.7 | 26.7 |
| NYG | 27.25 | 6 | 26 | 4.25 | 6 | 14 | 28 | 27 | 8 | 19.8 | 13.0 | 16.0 |
| PHI | 16.5 | 9 | 22 | 22 | 23 | 28 | 21.75 | 2 | 16 | 20.1 | 11.3 | 22.0 |
| MIA | 16.25 | 20 | 8 | 26.75 | 23 | 4 | 20.5 | 23 | 5 | 21.2 | 22.0 | 5.7 |
| NYJ | 23.5 | 10 | 8 | 28.5 | 29 | 16 | 11.5 | 31 | 12 | 21.2 | 23.3 | 12.0 |
| CLE | 23.25 | 30 | 5 | 12.25 | 23 | 25 | 30 | 26 | 23 | 21.8 | 26.3 | 17.7 |
| CAR | 20 | 5 | 29 | 30.5 | 10 | 11 | 15.25 | 15 | 2 | 21.9 | 10.0 | 14.0 |
| ARI | 30.5 | 18 | 8 | 24.5 | 31 | 10 | 11.25 | 20 | 9 | 22.1 | 23.0 | 9.0 |
| KC | 28 | 31 | 19 | 23.75 | 32 | 23 | 18.25 | 10 | 9 | 23.3 | 24.3 | 17.0 |
| STL | 32 | 32 | 22 | 23 | 27 | 12 | 21.75 | 23 | 19 | 25.6 | 27.3 | 17.7 |
| WAS | 15 | 26 | 19 | 31 | 5 | 26 | 31.75 | 21 | 32 | 25.9 | 17.3 | 25.7 |
| JAC | 25 | 29 | 13 | 28.5 | 30 | 23 | 31 | 32 | 29 | 28.2 | 30.3 | 21.7 |
Conclusion
The data indicates that while a powerful offense helps with identifying useful kickers, it is not a guarantee for a top one. In fact, only one kicker, New England´s (Stephen Gostkowski) showed up in both top-five averages. The offenses that had high average rankings (Green Bay, Denver, New Orleans and Detroit) all had average kicker rankings in the 10-15 range. It is safe to say the data does not support the "high power offense equals a top kicker" theory.
As for the theory concerning great defense supporting great kickers, this is also a mixed bag. On one hand are San Francisco and Baltimore, both of which have had good kickers and pretty good defenses. On the other, Seattle, Cincinnati, Pittsburgh and Miami punch holes in the theory. That said, here are some observations from the data:
• New England, San Francisco, Baltimore, Dallas and Green Bay have had solid kicking teams the last three years (Denver the last two).
• Indianapolis, San Diego and Seattle are kicking teams on the rise.
• Houston and Tennessee are kicking teams on the decline.
