Cat Carriers and Cat Killers
Players earn their fantasy value in different ways. Some players provide well-rounded stat lines that are more or less without weakness. Other players’ fantasy value is derived from strengths in a few categories or even just one category. The flip side is that some players can hurt a fantasy team with large negative values in one or more categories. These large negative values often occur in the efficiency categories (shooting percentages and turnovers).

Over the past few years, no other player has embodied the spirit of the Cat Carrier and the Cat Killer than Orlando’s own superhero, Dwight Howard. D12 is a Cat Carrier for three categories; rebounds, blocks and field goal percentage. At the same time, Howard is also a Cat Killer in two categories; free throw percentage and turnovers.
When constructing a winning Roto or Head-to-Head team, it is important to build a cohesive team while finding value throughout the draft. In H2H it is much easier to overcome weaknesses than it is in a Roto league, thus allowing for managers to take on Cat Killers without completely destroying their team’s chance of success. In Roto leagues, the Cat Killers are much harder to handle.
But in determining which Cat Carriers to draft or which Cat Killers to avoid, it is important to have a method of comparing Carriers or Killers in different categories to each other. Enter player valuation systems such as Basketball Monster or Ziguana.
Player valuation systems commonly rely on Z-Scores to allow us to compare apples (counting statistics, such as blocks) to oranges (efficiency statistics, such as field goal percentage). Since all counting statistics are on different scales, they also allow us to compare one type of apple (rebounds) to another type of apple (threes). Z-Scores do this generally by using standard deviations to rank all players against the average of a particular category. These individual Z-Scores are aggregated to assign an overall value for each player.
In trying to predict future fantasy production, past production is one of the biggest factors that comes in to play. As with most statistics, the more data you have the more reliable your conclusions. Thus, by using multiple years of data, you can better control for suspensions, injuries, down seasons and other outliers.
What follows is a list of the largest Cat Carriers and Cat Killers based on cumulative values over the past three seasons based on Basketball Monster’s Player Rankings in the nine standard categories. To eliminate any fringe players, a minimum of fifty games played was enacted. I relied on BBM’s valuations over Ziguana’s because BBM has a simple filter to limit the data to the past three seasons. Three seasons of data was used to help control for anomalies while also allowing some of the younger players to make the list.
And now, the rankings.
*Table is sortable. Click on column headers to sort data.
| Name | Category | Value |
|---|---|---|
| Camby, Marcus | Blocks | 3.90 |
| Nash, Steve | Assists | 3.61 |
| Paul, Chris | Assists | 3.51 |
| Williams, Deron | Assists | 3.29 |
| Stoudemire, Amare | FG% | 3.08 |
| Howard, Dwight | Rebounds | 3.05 |
| Howard, Dwight | FG% | 3.00 |
| O'neal, Shaquille | FG% | 2.95 |
| Kidd, Jason | Assists | 2.90 |
| Smith, Josh | Blocks | 2.89 |
| Bryant, Kobe | Points | 2.79 |
| Andersen, Chris | Blocks | 2.74 |
| James, Lebron | Points | 2.73 |
| Howard, Dwight | Blocks | 2.67 |
| Booth, Calvin | Turnovers | 2.64 |
| O'neal, Jermaine | Blocks | 2.59 |
| Wade, Dwyane | Points | 2.58 |
| Novak, Steve | Turnovers | 2.54 |
| West, Mario | Turnovers | 2.53 |
| Camby, Marcus | Rebounds | 2.51 |
| Bowen, Ryan | Turnovers | 2.50 |
| Jackson, Darnell | Turnovers | 2.48 |
| Jacobsen, Casey | Turnovers | 2.45 |
| Mourning, Alonzo | Blocks | 2.41 |
| Boozer, Carlos | FG% | 2.41 |
| Ager, Maurice | Turnovers | 2.38 |
| Madsen, Mark | Turnovers | 2.38 |
| Jones, Dwayne | Turnovers | 2.38 |
| Arenas, Gilbert | Points | 2.37 |
| Stojakovic, Peja | Threes | 2.35 |
| Lewis, Rashard | Threes | 2.35 |
| Mbenga, DJ | Turnovers | 2.35 |
| Lafrentz, Raef | Turnovers | 2.35 |
| Nowitzki, Dirk | FT% | 2.32 |
| Gasol, Pau | FG% | 2.26 |
| Curry, Eddy | FG% | 2.25 |
| Allen, Ray | Threes | 2.24 |
| Brand, Elton | Blocks | 2.24 |
| Chandler, Tyson | Rebounds | 2.21 |
| Billups, Chauncey | FT% | 2.21 |
| Dalembert, Samuel | Blocks | 2.18 |
| Anthony, Carmelo | Points | 2.17 |
| Arenas, Gilbert | Threes | 2.17 |
| Davis, Baron | Assists | 2.17 |
| Duncan, Tim | Blocks | 2.17 |
| Ming, Yao | Blocks | 2.12 |
| Biedrins, Andris | FG% | 2.12 |
| Jefferson, Al | Rebounds | 2.10 |
| Chandler, Tyson | FG% | 2.08 |
| Martin, Kevin | FT% | 2.07 |
| Boozer, Carlos | Rebounds | 2.05 |
| Duncan, Tim | Rebounds | 2.03 |
| Ager, Maurice | Rebounds | -2.01 |
| Jackson, Darnell | Steals | -2.02 |
| Brown, Andre | Steals | -2.05 |
| Westbrook, Russell | Turnovers | -2.05 |
| Lopez, Robin | Steals | -2.06 |
| Pecherov, Oleksiy | Steals | -2.07 |
| Crawford, Jamal | FG% | -2.09 |
| Alston, Rafer | FG% | -2.09 |
| Hollins, Ryan | Steals | -2.11 |
| Jones, Dwayne | Steals | -2.11 |
| Tinsley, Jamaal | FG% | -2.11 |
| Howard, Dwight | Turnovers | -2.11 |
| Chandler, Tyson | FT% | -2.14 |
| Bogut, Andrew | FT% | -2.14 |
| Madsen, Mark | Steals | -2.15 |
| Hunter, Steven | Steals | -2.15 |
| Simmons, Cedric | Steals | -2.16 |
| Jones, Solomon | Steals | -2.17 |
| Collins, Jarron | Steals | -2.17 |
| Mourning, Alonzo | FT% | -2.17 |
| Booth, Calvin | Steals | -2.19 |
| Ely, Melvin | Steals | -2.19 |
| Brezec, Primoz | Steals | -2.20 |
| Marks, Sean | Steals | -2.25 |
| Jacobsen, Casey | Steals | -2.29 |
| Arenas, Gilbert | FG% | -2.29 |
| Evans, Reggie | FT% | -2.29 |
| Ager, Maurice | Steals | -2.35 |
| Nash, Steve | Turnovers | -2.43 |
| Collins, Jason | Points | -2.60 |
| Brown, Kwame | FT% | -2.60 |
| Jacobsen, Casey | Points | -2.61 |
| Jackson, Darnell | Points | -2.61 |
| Mbenga, DJ | Points | -2.61 |
| Richard, Chris | Points | -2.63 |
| Jones, Dwayne | Points | -2.70 |
| Ruffin, Michael | Points | -2.74 |
| Booth, Calvin | Points | -2.74 |
| Okafor, Emeka | FT% | -2.77 |
| West, Mario | Points | -2.78 |
| Wallace, Ben | FT% | -2.79 |
| Madsen, Mark | Points | -2.84 |
| Wade, Dwyane | Turnovers | -2.94 |
| Curry, Eddy | FT% | -3.48 |
| O'Neal, Shaquille | FT% | -5.26 |
| Howard, Dwight | FT% | -5.95 |
Over the course of the last three seasons, the single largest positive contributor to any one category has been Marcus Camby in blocks (averaged 3.1 blocks over the past three seasons). The next three top dogs were a trio of elite point guards in Steve Nash (10.8 assists), Chris Paul (10.2 assists) and Deron Williams (10.1 assists). Rounding out the top five is Amare Stoudemire with his highly efficient scoring from the field (.572 percent shooting on 14.1 attempts per game) due in part to Nash’s aforementioned dimes.
In simply perusing the top five players on this list, it becomes apparent why punting assists is so popular in H2H leagues. If you miss a top shelf point guard in the draft, you will have trouble competing against the managers that get one of the assist Cat Carriers. If you broaden the scope to the top ten players, Jason Kidd makes an appearance at seventh overall for assists as well (9.3 assists).
If you re-sort the data to put the values in ascending order, Dwight Howard takes the top spot, also know as the best of the worst. Howard’s free throw percentage (.590 percent on 9.9 attempts per game) is the single biggest category contributor in fantasy basketball over the past three seasons, period. Unfortunately for Howard and his Roto owners, this contribution is negative. In a close second is Shaquille O’Neal’s free throw percentage impact (.524 percent shooting on 6.5 attempts per game).
To reiterate, these two values are by far the biggest single category contributions in fantasy basketball, whether positive or negative. Either of these two negative free throw percentage contributions dwarfs Camby’s positive value in blocks in comparison. For rookie managers, the lesson should now be crystal clear. When dealing with percentages, attempts matter. A lot. That is why Andris Biedrins‘ free throw percentage (.565 percent shooting on only 2.6 attempts per game) is not nearly as damaging as Howard’s or Shaq’s. It still hurts a team, but is much more managebale than Howard’s.
Another lesson that managers of all experience levels can learn from examining Cat Carriers and Cat Killers is that Cat Carriers that are not also Cat Killers are always in high demand. These players are much easier to move than Cat Carriers that are also Cat Killers. For Roto leagues, and to a lesser degree H2H teams, Cat Killers are difficult to incorporate into a team after the draft because teams need to have a specific means of moderating the impact of a Cat Killer. Thus, targeting Cat Carriers can give you lots of trade value because these players can almost singlehandedly make a team competitive in a certain category. Oftentimes, managers are looking to trade for players that help deficiencies and not players that provide solid across the board value.
By looking at these values and comparing them against each other, it is apparent why winning a Roto league with Dwight Howard is such a difficult task that few have accomplished in competitive fantasy leagues. Moreso than any other player in the league, Howard was built for H2H play and should only be drafted in Roto leagues by managers who have a clear-cut plan in place of reducing the harm caused by Superman’s free throw shooting and the chutzpah to take the plunge.