Seeing Justice Done: The Impact of the Judge on Sentencing
The recent sentencing of Paul Manafort by federal judges in two different district courts has renewed interest in the sentencing practices of individual judges. Countless studies over the years have documented a basic fact: while decisions should be determined by the law and the facts, in reality there is a third very important force at work. This ingredient is the identity of the judge assigned to a given case. Again and again, court records show that the particular predilections of individual judges influence the legal decisions that they reach, including those involving sentences.
In the Alexandria, Virginia courthouse where Manafort was sentenced by Judge Thomas Selby Ellis III on March 7, court records there show there was more than a 12-month difference among judges in the average prison sentences they give[1]. The Alexandria court is by no means exceptional in this regard.
The sentencing record of Judge Ellis when compared to his colleagues on the same bench show he has tended to hand down longer prison terms. For example, during calendar 2018 Judge Ellis sentenced a total of 73 defendants. His average sentence across all offenses was 90.6 months in prison - much longer than the other judges in his district. However, considering only the 11 white collar offenders sentenced by Judge Ellis, he awarded the lowest average among his colleagues. A similar pattern is found over the past five years. Judge Ellis was among the Alexandria judges who handed out overall higher average sentences, with the exception for white collar offenders where his sentences tended to be in the lower range for judges on that bench.
TRAC's Study Comparing Judge Sentencing Records
The existence of judge-to-judge differences in sentences of course is not synonymous with finding unwarranted disparity in sentencing practices. A key requirement for achieving justice is that the judges in a court system have sufficient discretion to consider the totality of circumstances in deciding that a sentence in a specific case is just. No set of rules, including the Federal Sentencing Guidelines[2], can substitute for this necessary flexibility.
But a fair court system always seeks to provide equal justice under the law, working to ensure that sentencing patterns of judges not be widely different when they are handling similar kinds of cases.
The record of Judge Ellis contrasts somewhat with that of Judge Amy Berman Jackson who serves on the District of Columbia court and sentenced Manafort in a separate case on March 13, six days later. Her overall sentencing record is much more typical of others on the same court. It does appear, however, had Manafort been sentenced by a different judge on the Washington federal court his sentence could have been quite different. This is because court records show that the average prison sentence between judges at that courthouse differed by 24 months. (Because the Washington federal court has a smaller number of white collar matters than the one in Alexandria, there is an insufficient number of cases to compare sentencing patterns on just white collar crimes.)
For years, the Transactional Record Access Clearinghouse (TRAC) at Syracuse University has systematically been compiling judge-by-judge, case-by-case, sentencing records[3]. The Center has just completed updating its detailed sentencing records on all U.S. District Court Judges through the end of December 2018. Results reported here highlight courthouses that have the most as well as the least judge-to-judge differences in prison sentences. The goal of systematically examining sentences is not to develop a lockstep sentencing system. Rather, the goal is to provide both the courts and the public with detailed information so that they can examine whether justice is being achieved.
Findings
This study compares 155 federal courthouses in the country. To be included, the courthouse had to have two or more U.S. District Court judges who had sentenced defendants in at least 50 cases during the past five years (January 2014 - December 2018). A total of 767 judges serving at these courthouses met this criteria. Each handled the sentencing on average in 277 criminal cases. The prison sentences between the judge with the lowest average prison sentence was compared with the judge with the highest average sentence at each courthouse, and the difference in sentence length between the two was computed[4]. The difference in the median prison sentence was also recorded.
(Click for larger image)
As shown in Table 1 and Figure 1, 66 of these judges served at 6 courthouses where the average prison sentences length differed by more than 48 months. Half of the judges served at courthouses where the average prison sentence was at least 23 months.
Between Lowest vs. Highest
Judge Average Prison Sentence
| Range in Average Prison Sentence | Number of Courthouses* | Judges at These Courthouses* |
| >48 months | 6 | 66 |
| >42-48 months | 4 | 46 |
| >36-42 months | 9 | 67 |
| >30-36 months | 12 | 98 |
| >24-30 months | 12 | 75 |
| >18-24 months | 27 | 124 |
| >12-18 months | 31 | 143 |
| >6-12 months | 31 | 93 |
| >0-6 months | 23 | 55 |
| Total | 155 | 767 |
Having larger numbers of judges usually makes it more challenging to have them all closely agree in their sentencing practices. Thus, as shown in Figure 2 (at the end of this report), courthouses with only 2 sitting U.S. District Court judges had a higher likelihood of having less than 6 months differences between the two judges in their average prison sentences. However, it was no guarantee as differences ranged as high as 45 months for one 2-judge courthouse.
While the courthouses with the largest number of judges tended to place towards the top in their range in sentences, they were by no means the courthouses that had the largest sentence differences. The Orlando courthouse in the Middle District of Florida with 7 judges had a range of over 80 months between the judge with the shortest versus the longest average prison sentence. This was followed by the Greenbelt courthouse in Maryland with over 64 months difference among the 7 judges serving there.
The statistics for each of the 155 federal courthouses included in this study are given in Table 2 at the end of the report.
Conclusion
It is well to keep in mind that judges after all are human and we ask them to exercise their best judgments in rendering decisions. So differences should be expected and are indeed inevitable. But when judge-to-judge differences become extreme they can undermine the public's confidence in the fairness of our judicial system.
(Click for larger image)
January 2014 - December 2018
(click title to open in a new window)
| District | Courthouse | Number of U.S. District Court Judges | Prison Sentence Range (Months) Between Lowest-Highest Judge's | |
| Median Sentences | Average Sentences | |||
| Ala, M | Montgomery | 2 | 1.0 | 0.2 |
| Ala, N | Birmingham | 7 | 18.0 | 25.6 |
| Ala, S | Mobile | 4 | 24.5 | 22.2 |
| Alaska | Anchorage | 3 | 11.0 | 6.8 |
| Arizona | Phoenix | 12 | 28.0 | 32.7 |
| Arizona | Tucson | 7 | 9.0 | 12.7 |
| Ark, E | Little Rock | 7 | 10.5 | 17.3 |
| Cal, C | Los Angeles | 17 | 30.5 | 32.8 |
| Cal, C | Riverside | 2 | 24.0 | 33.4 |
| Cal, C | Santa Ana | 5 | 13.0 | 10.3 |
| Cal, E | Fresno | 3 | 13.5 | 12.1 |
| Cal, E | Sacramento | 6 | 9.5 | 16.5 |
| Cal, N | Oakland | 2 | 0.0 | 5.8 |
| Cal, N | San Francisco | 9 | 32.5 | 39.4 |
| Cal, N | San Jose | 3 | 9.0 | 9.6 |
| Cal, S | San Diego | 17 | 12.0 | 17.5 |
| Colorado | Denver | 10 | 14.0 | 27.0 |
| Conn | Bridgeport | 4 | 21.0 | 25.1 |
| Conn | Hartford | 5 | 18.5 | 19.3 |
| D. C. | DC | 8 | 11.0 | 23.7 |
| Delaware | Wilmington | 4 | 22.0 | 22.9 |
| Fla, M | Ft. Myers | 2 | 3.0 | 6.9 |
| Fla, M | Jacksonville | 5 | 18.0 | 22.9 |
| Fla, M | Orlando | 7 | 52.0 | 80.2 |
| Fla, M | Tampa | 9 | 48.0 | 59.7 |
| Fla, N | Pensacola | 2 | 6.0 | 14.6 |
| Fla, N | Tallahassee | 2 | 1.5 | 1.3 |
| Fla, S | Ft. Lauderdale | 4 | 5.0 | 6.4 |
| Fla, S | Miami | 13 | 19.0 | 28.6 |
| Fla, S | West Palm Beach | 4 | 16.5 | 2.0 |
| Ga, M | Albany | 2 | 7.5 | 12.5 |
| Ga, M | Macon | 3 | 16.0 | 15.6 |
| Ga, N | Atlanta | 9 | 24.0 | 42.9 |
| Ga, S | Augusta | 2 | 10.0 | 0.3 |
| Ga, S | Savannah | 2 | 20.0 | 32.3 |
| Hawaii | Honolulu | 5 | 18.0 | 31.9 |
| Idaho | Boise | 2 | 0.0 | 5.8 |
| Ill, C | Peoria | 3 | 18.0 | 18.9 |
| Ill, C | Urbana | 2 | 24.0 | 20.4 |
| Ill, N | Chicago | 21 | 33.0 | 30.5 |
| Ill, N | Rockford | 2 | 5.0 | 9.4 |
| Ill, S | Benton | 2 | 48.0 | 32.9 |
| Ill, S | East St. Louis | 3 | 2.5 | 10.8 |
| Ind, N | Hammond | 4 | 3.0 | 16.7 |
| Ind, N | South Bend | 2 | 6.0 | 4.4 |
| Ind, S | Indianapolis | 4 | 16.0 | 17.2 |
| Iowa, N | Sioux City | 2 | 10.0 | 0.1 |
| Iowa, S | Des Moines | 4 | 39.0 | 37.3 |
| Kansas | Kansas City | 2 | 12.0 | 22.9 |
| Kansas | Topeka | 3 | 14.0 | 18.4 |
| Kansas | Wichita | 2 | 36.0 | 45.1 |
| Ken, E | Lexington | 2 | 2.0 | 2.4 |
| Ken, E | London | 2 | 18.0 | 22.5 |
| Ken, W | Louisville | 3 | 14.5 | 10.6 |
| La, E | New Orleans | 8 | 23.5 | 20.7 |
| La, M | Baton Rouge | 4 | 12.5 | 13.2 |
| La, W | Shreveport | 3 | 26.5 | 22.0 |
| Maine | Portland | 4 | 9.5 | 21.0 |
| Maryland | Baltimore | 8 | 30.0 | 41.0 |
| Maryland | Greenbelt | 7 | 45.0 | 64.3 |
| Mass | Boston | 11 | 28.0 | 33.9 |
| Mass | Worcester | 2 | 12.0 | 12.1 |
| Mich, E | Ann Arbor | 2 | 5.0 | 12.4 |
| Mich, E | Detroit | 18 | 18.0 | 40.8 |
| Mich, E | Flint | 2 | 0.5 | 9.1 |
| Mich, W | Grand Rapids | 4 | 18.0 | 15.1 |
| Minnesota | Minneapolis | 6 | 12.5 | 17.0 |
| Minnesota | St. Paul | 3 | 10.5 | 15.2 |
| Miss, N | Aberdeen | 2 | 4.0 | 1.7 |
| Miss, N | Oxford | 2 | 1.0 | 3.7 |
| Miss, S | Gulfport | 2 | 0.0 | 3.6 |
| Miss, S | Jackson | 4 | 15.0 | 7.4 |
| Mo, E | St. Louis | 8 | 13.5 | 18.7 |
| Mo, W | Kansas City | 9 | 20.0 | 34.4 |
| Montana | Missoula | 2 | 27.0 | 27.2 |
| N Car, E | Raleigh | 2 | 7.0 | 13.3 |
| N Car, M | Greensboro | 3 | 6.0 | 7.1 |
| N Car, M | Winston Salem | 2 | 13.0 | 10.1 |
| N Car, W | Asheville | 2 | 4.0 | 12.9 |
| N Car, W | Charlotte | 3 | 27.0 | 18.7 |
| N Mexico | Albuquerque | 8 | 27.3 | 38.6 |
| N Mexico | Las Cruces | 2 | 0.1 | 0.8 |
| N. J. | Camden | 5 | 17.0 | 12.0 |
| N. J. | Newark | 10 | 34.5 | 23.7 |
| N. J. | Trenton | 5 | 26.5 | 26.7 |
| N. Y., E | Brooklyn | 18 | 18.0 | 58.7 |
| N. Y., E | Central Islip | 6 | 21.0 | 21.1 |
| N. Y., N | Albany | 3 | 18.5 | 21.8 |
| N. Y., N | Syracuse | 3 | 6.0 | 21.5 |
| N. Y., S | Manhattan | 30 | 37.0 | 47.2 |
| N. Y., S | White Plains | 4 | 9.0 | 20.3 |
| N. Y., W | Buffalo | 3 | 15.0 | 14.4 |
| N. Y., W | Rochester | 4 | 30.0 | 27.8 |
| Nebraska | Lincoln | 2 | 6.0 | 6.9 |
| Nebraska | Omaha | 4 | 6.0 | 5.4 |
| Nevada | Las Vegas | 7 | 31.0 | 27.7 |
| Nevada | Reno | 4 | 11.0 | 12.2 |
| New Hamp | Concord | 5 | 14.5 | 15.6 |
| Ohio, N | Akron | 2 | 6.0 | 1.8 |
| Ohio, N | Cleveland | 6 | 15.0 | 19.4 |
| Ohio, N | Toledo | 3 | 7.0 | 6.4 |
| Ohio, S | Cincinnati | 2 | 0.0 | 4.1 |
| Ohio, S | Columbus | 6 | 16.0 | 16.0 |
| Ohio, S | Dayton | 3 | 3.0 | 10.3 |
| Okla, N | Tulsa | 3 | 15.0 | 8.6 |
| Okla, W | Oklahoma City | 6 | 12.0 | 13.8 |
| Oregon | Eugene | 2 | 12.0 | 9.6 |
| Oregon | Portland | 6 | 24.0 | 35.1 |
| Penn, E | Allentown | 3 | 12.0 | 22.9 |
| Penn, E | Philadelphia | 22 | 52.0 | 58.5 |
| Penn, E | Reading | 2 | 18.5 | 14.9 |
| Penn, M | Harrisburg | 5 | 14.5 | 19.7 |
| Penn, M | Scranton | 5 | 31.5 | 28.0 |
| Penn, W | Pittsburgh | 9 | 22.5 | 24.9 |
| Puer Rico | Hato Rey, Puerto Rico | 8 | 16.0 | 17.1 |
| R. I. | Providence | 3 | 12.5 | 8.0 |
| S Car | Charleston | 3 | 12.0 | 6.2 |
| S Car | Columbia | 3 | 34.0 | 52.0 |
| S Car | Florence | 2 | 20.0 | 31.7 |
| S Car | Greenville | 4 | 16.0 | 14.4 |
| Tenn, E | Chattanooga | 3 | 9.0 | 7.2 |
| Tenn, E | Knoxville | 4 | 27.5 | 36.8 |
| Tenn, M | Nashville | 5 | 9.5 | 9.9 |
| Tenn, W | Memphis | 6 | 27.0 | 37.6 |
| Texas, E | Beaumont | 3 | 31.0 | 28.1 |
| Texas, E | Sherman | 2 | 14.0 | 12.0 |
| Texas, E | Tyler | 2 | 14.0 | 1.4 |
| Texas, N | Dallas | 8 | 27.0 | 36.6 |
| Texas, N | Fort Worth | 2 | 32.0 | 39.2 |
| Texas, S | Brownsville | 4 | 6.0 | 10.7 |
| Texas, S | Corpus Christi | 3 | 9.0 | 15.4 |
| Texas, S | Houston | 12 | 18.0 | 22.8 |
| Texas, S | Laredo | 3 | 2.0 | 4.2 |
| Texas, S | McAllen | 3 | 6.0 | 8.3 |
| Texas, W | Austin | 2 | 9.0 | 19.1 |
| Texas, W | Del Rio | 2 | 1.0 | 9.1 |
| Texas, W | El Paso | 5 | 2.0 | 2.9 |
| Texas, W | Midland | 2 | 11.0 | 9.2 |
| Texas, W | San Antonio | 4 | 4.0 | 10.6 |
| Utah | Salt Lake City | 9 | 39.0 | 34.4 |
| Vermont | Rutland | 2 | 4.0 | 1.8 |
| Virg, E | Alexandria | 7 | 6.5 | 12.1 |
| Virg, E | Norfolk | 6 | 24.0 | 27.8 |
| Virg, E | Richmond | 5 | 44.5 | 45.3 |
| Virg, W | Roanoke | 3 | 3.0 | 9.2 |
| W Virg, N | Wheeling | 2 | 1.5 | 1.0 |
| W Virg, S | Charleston | 3 | 14.0 | 16.3 |
| Wash, E | Richland | 2 | 11.0 | 9.3 |
| Wash, E | Spokane | 4 | 9.0 | 18.9 |
| Wash, E | Yakima | 2 | 14.0 | 19.1 |
| Wash, W | Seattle | 7 | 13.0 | 12.6 |
| Wash, W | Tacoma | 3 | 10.5 | 3.0 |
| Wisc, E | Milwaukee | 5 | 25.0 | 17.6 |
| Wisc, W | Madison | 3 | 16.0 | 11.7 |
| Wyoming | Cheyenne | 2 | 3.0 | 4.6 |
Footnotes
[1] This is a conservative estimate. To minimize random difference among judge caseloads, Table 1 is based upon the average prison sentence for each case - where cases with a single defendant counted the same as cases with multiple defendants.
[2] A system of "sentencing guidelines" for federal judges was established during the eighties in an attempt to reduce sentencing disparity. Originally mandatory, following a U.S. Supreme Court decision in 2005, they are now advisory. While judges must consider the guidelines, they are not required to follow them.
[3] For more information about this TRAC database and how we developed it, see The Development of Judge-Specific Federal Sentencing Data at TRAC. For reports on individual judges, see TRAC's Judge Info Center. See also past TRAC reports highlighting differences in sentencing practices among federal courthouses that are available there. TRAC also produces a regular series on judge-to-judge differences in federal civil cases wait times and pending caseloads as well as Immigration Court asylum decisions.
[4] Given the fairly large number of defendants sentenced by each judge, where there is random assignment of cases to judges then statistically speaking each judge should have closely comparable caseloads so that differences in the nature of the offenses and defendants' histories are roughly comparable. Because random assignment is based upon "cases," in the results reported here each case was weighted the same so that cases where there were multiple defendants did not have a greater influence.
TRAC data on the workloads of federal judges are part of TRAC's Judge Information Center. TRAC compiles, verifies, and publishes information on the workloads of federal district court judges. The free Criminal Caseload Tool provides information on criminal caseloads. TRAC's free Civil Caseload Tool provides rankings for nearly every federal district court judge in the country — by the number of civil cases pending at the time of the last update and the number closed in the year prior to the last update. The Judge Information Center also provides information on Immigration Court judges.
In addition to the free caseload data, a subscription to the Center provides access to custom reports on each judge, showing in greater detail the composition of the judge's caseload, the time on average it takes to close cases, how those closing times compare to other judges in the district, and a detailed look at the cases the judge took the longest to close.
TRAC is a nonpartisan, nonprofit data research center affiliated with the Newhouse School of Public Communications and the Whitman School of Management, both at Syracuse University. For more information, to subscribe, or to donate, contact trac@syr.edu or call 315-443-3563.