Charting Outcomes in the Match – US MD Applicants: Data & Trends

What Is Charting Outcomes in the Match?

Charting Outcomes in the Match is a biennial report published by the National Resident Matching Program (NRMP). It aggregates applicant-level data submitted through ERAS and the NRMP rank order list system to produce matched-vs.-unmatched comparisons across dozens of applicant characteristics: USMLE scores, research output, honors recognition, and rank list length. The report is the closest thing US GME has to an evidence base for application strategy.

It is distinct from the NRMP's Main Residency Match Results and Data report, which is released annually after each Match and covers aggregate fill rates, position counts, and applicant totals. Results and Data tells you how many positions were offered and filled. Charting Outcomes tells you what the applicants who filled them looked like—and, critically, what the applicants who did not fill them looked like.

Because it is biennial, the most recently published edition always lags the current application cycle by at least one to two years. That lag matters and is addressed in the limitations section below. The official PDF is published at nrmp.org; every figure on this page is drawn from that source.

Separate Charting Outcomes editions are published for US MD seniors, US DO seniors, and independent applicants (which includes most IMGs). This page covers US MD applicants only. DO and IMG applicants should consult the relevant companion editions and the PGY Zero data pages for those groups.

Overall Match Rate for US MD Seniors

All figures in this section: NRMP Charting Outcomes in the Match, US MD Seniors edition, 2024 data year (covering the 2024 Main Residency Match).

US MD seniors consistently post the highest aggregate match rates of any applicant category in the Main Residency Match. In the 2024 Charting Outcomes cycle, the overall match rate for US MD seniors was approximately 93–94%—a figure that has been stable across the prior two biennial cycles and reflects both strong applicant preparation and the structural advantage of applying as a senior from an LCME-accredited school.

Data year stamp: Match rate figure = NRMP Charting Outcomes in the Match: US MD Seniors, 2024 edition, published nrmp.org. Confirm the current edition before citing.

The headline rate, however, obscures meaningful variance. That aggregate includes applicants in very high-match-rate specialties (family medicine, internal medicine categorical) who elevate the overall number, and it excludes applicants who withdrew, scrambled into unaccredited positions, or did not submit a rank list. Specialty-level rates, shown in the next section, are the operationally relevant figures for self-assessment.

Trend: The 2022 and 2024 editions show the overall US MD senior match rate as essentially flat—movement of less than one percentage point across cycles. The more informative trend is within competitive specialties, where unmatched counts have fluctuated more than the aggregate suggests.

Match Rates by Specialty

All figures: NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition. Figures represent applicants who submitted a rank order list.

The table below organizes specialties from highest to lowest match rate for US MD senior applicants. Because position counts and applicant volumes shift each cycle, the absolute matched/unmatched counts matter as much as the percentage—a specialty with a 90% match rate and 20 applicants is a different risk profile than one with 90% and 1,000 applicants.

How to read the table: "Matched" = received a position via the NRMP algorithm. "Unmatched" = submitted a rank list, did not match. Applicants who did not submit a rank list (withdrew, soap-only, etc.) are excluded from NRMP's denominators in Charting Outcomes.

Important: Figures above are approximate, derived from NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition. Small-N specialties (thoracic surgery, plastic surgery) have wide confidence intervals around percentages; treat rates as illustrative rather than precise. Always download the current NRMP PDF at nrmp.org for exact figures before using these numbers in advising or decision-making.

Several patterns are worth naming directly:

• High-volume, high-match-rate specialties (family medicine, internal medicine, pediatrics) match the largest absolute numbers of applicants and have unmatched counts that are small relative to total applicants—but those unmatched applicants still number in the dozens to low hundreds, and they are not randomly distributed by preparation profile.
• Competitive surgical specialties (neurological surgery, orthopedic surgery, plastic surgery, otolaryngology) have both lower match rates and meaningful unmatched absolute counts despite small total applicant pools. A 25–30% non-match probability is a real planning constraint, not a theoretical one.
• Emergency medicine moved from a high-match-rate specialty to a tighter market over the 2020–2024 period; consult the current Charting Outcomes edition for the most recent data before treating it as a "safe" backup field.

USMLE Step 1 Scores: Matched vs. Unmatched

All figures: NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition. Step 1 numeric scores reported only for applicants who tested before the January 2022 pass/fail transition; pass/fail applicants are counted separately.

Step 1 became pass/fail for tests administered on or after January 26, 2022. For the 2024 Match, a substantial proportion of US MD seniors who applied had taken Step 1 under the pass/fail system and therefore have no numeric score. NRMP reports distributions for applicants who have numeric scores where sample sizes permit; the pass/fail cohort is reported as a binary. This dual-reporting situation will persist for several more cycles until the scored cohort ages out of the applicant pool entirely.

What the data show for applicants with numeric Step 1 scores:

• In research-intensive, highly competitive specialties (neurological surgery, plastic surgery, dermatology, orthopedic surgery, radiation oncology), mean Step 1 scores for matched US MD applicants consistently run well above the national mean, with 10th-percentile matched scores at or above what was historically the overall mean for all test-takers.
• In higher-volume specialties (internal medicine, family medicine, psychiatry, pediatrics), the matched-vs.-unmatched Step 1 score gap is narrower, and the 10th-percentile matched score is meaningfully lower—reflecting that these fields assess applicants on a broader profile.
• In virtually every specialty, the mean Step 1 score for unmatched US MD seniors is lower than the mean for matched applicants—but the distributions overlap. Unmatched applicants include people with very strong Step 1 scores who were underprepared in other dimensions, and matched applicants include people with lower scores who competed successfully on other dimensions.

Specialty-level Step 1 score distributions (matched vs. unmatched, US MD seniors, numeric score cohort):

Data year stamp: All score figures approximate; derived from NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org. Small unmatched subgroup N in several specialties makes unmatched means unstable—interpret with caution. Pass/fail cohort data not reflected in this table.

Pass/fail cohort applicants: For applicants with only a pass result on Step 1, Charting Outcomes reports match rates but cannot report score distributions. The operational implication is that Step 2 CK becomes the primary numeric signal available to programs for stratifying these applicants—see the next section.

USMLE Step 2 CK Scores: Matched vs. Unmatched

All figures: NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org.

Step 2 CK has become the primary numeric score available to residency programs for applicants who took Step 1 under the pass/fail system. Its weight in screening and ranking decisions has increased materially since the 2022 transition, a shift that is visible in Charting Outcomes data: the matched-vs.-unmatched Step 2 CK gap widened in the 2024 edition relative to prior cycles, particularly in competitive specialties.

Key patterns across the 2024 data:

• In every specialty tracked, matched US MD applicants have higher mean Step 2 CK scores than unmatched applicants. The magnitude of the gap varies by specialty competitiveness.
• For competitive surgical subspecialties (neurological surgery, plastic surgery, orthopedic surgery), matched applicant means are in the upper range of the score distribution, and 10th-percentile matched scores are above 250.
• For higher-volume specialties (internal medicine, family medicine, psychiatry), matched means are lower and the distributions broader—but even here, a Step 2 CK score below the matched 10th percentile is a meaningful risk factor when combined with other application weaknesses.
• The pass/fail Step 1 cohort shows a tighter Step 2 CK distribution among matched applicants than the historic scored-Step-1 cohort, consistent with programs placing more weight on the single available numeric signal.

Data year stamp: Figures approximate; NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org. Small unmatched N in subspecialties makes means unstable.

Practical implication: An applicant without a numeric Step 1 score should treat Step 2 CK as their primary academic signal and target a score at or above the matched mean for their intended specialty before submitting applications. A Step 2 CK below the matched 10th percentile for a given specialty is a concrete risk factor that informs both whether to apply broadly and how to structure the rank list.

Research Experiences and Publications

All figures: NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org. Research metrics are self-reported via ERAS and aggregated by NRMP; definitions of "abstract," "presentation," and "publication" reflect ERAS application categories.

Research output in Charting Outcomes is reported as mean counts of abstracts, presentations, and publications for matched vs. unmatched applicants. These are blunt instruments—a first-author publication in a high-impact journal and a conference abstract from a summer project count differently in practice but identically in the count—but the aggregate data are directionally informative.

Research-heavy vs. research-light specialties:

The Charting Outcomes data cleanly separate specialties into two clusters:

• Research-intensive specialties: Neurological surgery, plastic surgery (integrated), dermatology, radiation oncology, and orthopedic surgery show the largest matched-vs.-unmatched gaps in research output. Matched applicants in these fields carry mean publication counts that are meaningfully higher than unmatched applicants, and the 10th-percentile matched applicant typically has more research output than the median applicant in a research-light specialty. In neurological surgery, matched applicants average well above 10 abstracts/presentations and multiple publications; unmatched applicants have fewer across all categories.
• Research-light specialties: Family medicine, psychiatry, pediatrics, and internal medicine show smaller matched-vs.-unmatched gaps in research counts. A matched applicant in family medicine may have zero publications and still be competitive; in neurological surgery, zero publications places an applicant below the 10th percentile of matched peers.

Data year stamp: Figures approximate; NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org. Publication counts are self-reported ERAS entries; quality, authorship position, and journal tier are not captured.

Interpretation caveat: Research count data have a well-known inflation problem. ERAS allows applicants to enter poster presentations at local conferences and in-progress projects alongside peer-reviewed publications in the same fields. The mean counts for competitive specialties include applicants with genuine research portfolios and applicants who have maximized ERAS fields. Programs in research-intensive specialties weight first-authorship, journal impact, and presenter status in ways the count data cannot capture. A single first-author publication in a peer-reviewed surgical journal carries more signal than five conference abstracts for most programs in neurological surgery or plastic surgery.

Number of Programs Ranked

All figures: NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org.

Rank list length is one of the most directly actionable variables in Charting Outcomes. The NRMP algorithm is applicant-optimal under truthful ranking—ranking more programs you would genuinely accept can only improve or maintain your match probability, never decrease it. The data bear this out: matched applicants consistently rank more programs than unmatched applicants in every specialty tracked.

The matched-vs.-unmatched rank list gap is larger than most applicants expect. In some specialties, unmatched US MD seniors ranked lists half as long as matched peers. This reflects a combination of strategic under-listing (applicants confident in their top programs who did not hedge) and application under-breadth (applicants who received too few interview offers to build a longer list).

*"NRMP-Derived Probability Threshold" = approximate rank list length at which, per NRMP's own modeling in Charting Outcomes, match probability exceeds 90% for that specialty for a typical US MD applicant. These are read from NRMP probability curves; they are not guarantees and vary with applicant profile.

Data year stamp: NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org. Rank list length data reflect programs submitted, not interviews received; the two are correlated but not identical.

The actionable principle: If you receive interviews, rank every program you would genuinely accept a position at. The algorithm cannot penalize a longer honest list. The Charting Outcomes data show that unmatched applicants routinely ranked fewer programs than the threshold associated with high match probability—whether by choice or by insufficient interview volume. Both are preventable with the right application strategy upstream. For applicants who receive fewer interviews than the specialty threshold, the SOAP (Supplemental Offer and Acceptance Program) preparation becomes a first-order priority, not a backup afterthought.

AOA and Honors Recognition

All figures: NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org.

Alpha Omega Alpha (AOA) honor society membership and Latin honors (summa/magna/cum laude at graduation) appear in Charting Outcomes as binary variables. Their presence among matched applicants varies substantially by specialty.

Important structural context: AOA membership is not available at all LCME-accredited medical schools. An increasing number of schools have suspended or eliminated AOA chapters, and the AAMC has tracked this trend. As of the 2024 application cycle, a meaningful fraction of US MD seniors graduated from schools without active AOA chapters and therefore cannot have AOA membership regardless of academic standing. NRMP acknowledges this in Charting Outcomes; programs at research-intensive institutions increasingly account for it. An applicant without AOA from a school without a chapter is not disadvantaged relative to an applicant without AOA from a school that has one—but the data table does not make that distinction.

Data year stamp: Figures approximate; NRMP Charting Outcomes in the Match, US MD Seniors, 2024 edition, nrmp.org. AOA availability varies by institution; these percentages include applicants from schools both with and without active AOA chapters.

The data confirm that AOA membership is enriched among matched applicants in competitive specialties—but even in dermatology, the most AOA-enriched specialty here, the large majority of matched applicants (roughly two-thirds) did not have AOA. AOA is a positive signal; its absence is not disqualifying. Applicants from schools without AOA chapters should note this explicitly in applications to competitive programs where the difference might otherwise be misread.

Program Signals and MSPE Timing

Signal data below reflect ERAS program signaling as reported or discussed in NRMP and AAMC publications through the 2024 cycle. The signaling system has evolved; verify current signal allocations on the AAMC/ERAS website for the active application year. See also the PGY Zero signaling strategy page for application-year-specific guidance.

The ERAS program signaling system—introduced for most specialties on a phased basis starting in 2021—allows applicants to designate a limited number of programs as high-interest beyond the standard application. Signal allocation varies by specialty and has changed across cycles; consult the current season timeline and the PGY Zero signaling strategy page for current counts.

What Charting Outcomes does and does not tell us about signaling:

The 2024 Charting Outcomes edition includes limited signal-related data, primarily as aggregate interview invitation rates for signaled vs. non-signaled applications. The directional finding, consistent with AAMC specialty-level analyses, is that signals increase interview invitation probability at signaled programs—particularly at programs that are selective or geographically concentrated. The effect size varies by specialty and by program tier. The data do not permit individual-level inferences; a signal to a program far above your profile does not reliably produce an interview.

NRMP does not currently publish a full Charting Outcomes breakdown of matched-vs.-unmatched applicants stratified by signal use in the same format as score or rank list data. As the signaling system matures across cycles, this data will become more interpretable. For now, the operational guidance derived from available AAMC and NRMP publications is:

• Signals are most valuable when allocated to programs where your profile is genuinely competitive—programs where you are near or above the matched applicant mean for that program, not where you are aspirationally below it.
• Wasting signals on programs likely to interview you anyway, or on programs where your profile falls well short, reduces expected value.
• Geographic signals (to programs in a specific region where you have demonstrated ties) show the strongest evidence of increasing interview probability in AAMC specialty-level analyses.

MSPE release: The Medical Student Performance Evaluation (MSPE, "Dean's Letter") is released on a standardized date in October each application cycle (see the current season timeline for the exact date). Charting Outcomes does not publish matched-vs.-unmatched data stratified by MSPE content. The MSPE matters primarily for narrative context and clerkship performance documentation; its impact is most visible at selective programs with holistic review processes. Applicants whose MSPE will contain discrepant information relative to their application narrative should address this proactively in their personal statement or addendum.

How to Read These Charts as a PGY-Zero Applicant

Charting Outcomes data are useful precisely to the extent you use them correctly. Three errors account for most of the strategic mistakes applicants make when interpreting this report.

Error 1: Anchoring on the mean and treating it as a floor

The mean Step 2 CK or mean publication count for matched applicants is a central tendency statistic for a heterogeneous population. Roughly half of matched applicants are below the mean on any given metric. An applicant below the matched mean in one dimension who is above the matched mean in several others has a competitive overall profile. The error is treating the mean as a minimum threshold rather than a central point in a distribution.

Correct use: Locate yourself on the full distribution (10th–90th percentile range) for your target specialty on each available metric. A Step 2 CK below the 10th percentile of matched applicants is a genuine risk factor; a score between the 10th and 25th percentile is a relative weakness that needs to be offset by strength elsewhere; a score above the median is not a concern in isolation.

Error 2: Profile-matching to one specialty without triangulating program-level data

Charting Outcomes aggregates all programs in a specialty. An internal medicine program at a major academic medical center and a community internal medicine program appear in the same data. A Step 2 CK that puts you at the matched median for internal medicine overall may put you below the interview threshold for the top quartile of academic IM programs and well above it for community programs. Charting Outcomes is a starting point; program-specific data (available through some specialty-level FREIDA entries, program websites, and the AAMC's residency explorer tools) refines the analysis.

Error 3: Reading the unmatched applicant profile as "what not to be" rather than "what the risk is"

The unmatched applicant profile in Charting Outcomes is not a description of an inadequate applicant. It is a statistical description of a group of applicants who, for a combination of profile, application strategy, and rank list construction reasons, did not receive a position. Some unmatched applicants have strong profiles but narrow rank lists. Some have lower scores but applied to competitive-only programs. The data cannot separate these. Use the unmatched profile to identify dimensions where risk concentrates, not as a character profile of who fails to match.

Percentile self-assessment: a practical protocol

1. Download the current NRMP Charting Outcomes PDF (nrmp.org) for US MD seniors.
2. For each metric (Step 2 CK, research, rank list length), locate your value relative to the matched distribution for your primary specialty.
3. Note whether you are above median, between median and 10th percentile, or below 10th percentile on each metric.
4. For any metric where you are below the matched 10th percentile, that is an application planning constraint: it informs how broad to apply, whether to include backup specialties or positions, and how to construct the rank list.
5. Triangulate with program-level signals (interview invitations received, program communication) once the application cycle opens—real-time feedback updates your probability estimate in ways no historical dataset can.

Competitive vs. Less-Competitive Specialties: Head-to-Head

The same applicant profile reads very differently depending on specialty context. Four comparisons illustrate why specialty choice and realistic self-assessment must happen together.

Dermatology vs. Psychiatry

A US MD senior with a Step 2 CK score at the matched mean for psychiatry is, in approximate terms, at or below the 25th percentile of matched dermatology applicants. The same score that makes an applicant broadly competitive across psychiatry programs would place them below the interview threshold at a majority of dermatology programs. Research output at the matched mean for psychiatry (approximately 2 publications) is below the 25th percentile of matched dermatology applicants. These two specialties are not on a continuum; they require fundamentally different preparation profiles.

Orthopedic Surgery vs. General Surgery

Both are surgical fields with significant overlap in training pathway and clinical appeal to many applicants. But orthopedic surgery's match rate is meaningfully lower than general surgery's, and the matched orthopedic surgery applicant profile is stronger on nearly every metric: higher Step scores, more research, more programs ranked. An applicant with a general surgery-range Step 2 CK and limited research who applies to orthopedic surgery as a primary specialty without a genuine backup surgical field is accepting a materially higher non-match probability than the aggregate orthopedic match rate suggests—because that aggregate includes applicants with much stronger profiles.

Emergency Medicine vs. Internal Medicine (Categorical)

These two high-volume specialties are often discussed as comparable in competitiveness. The 2024 Charting Outcomes data suggest they are not equivalent. Emergency medicine's match rate has declined across recent cycles while internal medicine's has remained stable. The matched EM applicant mean Step 2 CK is higher than the matched IM categorical mean, the unmatched EM applicant count is proportionally higher relative to total applicants, and the rank list length threshold for high match probability is similar between the two despite EM having fewer total positions. An applicant applying to both as co-primaries with an IM-range profile should understand that IM is more forgiving of a weaker numeric profile than EM currently is.

Radiation Oncology vs. Diagnostic Radiology

Both are often grouped as competitive imaging/procedural fields. But radiation oncology has a significantly smaller position count than diagnostic radiology, and the absolute number of unmatched applicants relative to total applicants is proportionally high in radiation oncology. A step-2 CK that places an applicant in the matched range for diagnostic radiology may fall short of the matched mean for radiation oncology. Research expectations are also higher in radiation oncology on average. Applicants considering both fields should not treat diagnostic radiology as a simple safety backup for radiation oncology without explicitly checking profile fit for radiology independently.

Limitations and Caveats of Charting Outcomes Data

Using Charting Outcomes well requires understanding what it cannot tell you. The following limitations are material, not boilerplate.

Biennial lag

Charting Outcomes is published approximately every two years, covering Match cycles that closed before publication. A specialty's competitiveness landscape can shift meaningfully within two years—emergency medicine's trajectory since 2021 is the clearest recent example. The biennial cycle means the most recently available Charting Outcomes edition describes a cohort that may not represent current program behavior. Supplement with annual NRMP Results and Data releases and AAMC ERAS application statistics, which are published annually and more current.

Self-reported ERAS data

Research output figures (publications, abstracts, presentations) in Charting Outcomes are derived from ERAS application entries, which are self-reported and not systematically verified. This creates two problems: inflation (applicants may list incomplete or low-quality work) and inconsistency (different applicants categorize identical activities differently across ERAS fields). The true research quality distribution is not captured.

Exclusion of couples match

Couples match applicants are included in Charting Outcomes figures but are not separately identified. Couples match applicants have characteristically different geographic constraints and rank list structures. Their inclusion in aggregate data slightly distorts both the rank list length and the match rate figures for affected specialties. Applicants entering the couples match should note this and consult NRMP's separate couples match analysis where available.

DO and IMG applicants are not included in this edition

Charting Outcomes publishes separate editions for US MD seniors, US DO seniors, and independent applicants. The figures on this page apply only to US MD seniors. DO applicants, IMGs, and reapplicants who have applied in prior cycles are described in separate Charting Outcomes volumes. Applying this page's data to those populations is methodologically incorrect and will produce miscalibrated self-assessments.

Subspecialty nuance is lost in specialty-level aggregation

Internal medicine categorical match data aggregate all categorical IM programs regardless of whether they are community, university-affiliated, or major academic research programs. A research-focused academic IM program may have interview thresholds that more closely resemble a competitive surgical subspecialty than the IM aggregate would suggest. The aggregate data set a floor; they do not describe the ceiling within a specialty.

Pass/fail Step 1 transition creates a mixed cohort

The 2024 Charting Outcomes edition includes applicants with numeric Step 1 scores (tested before January 2022) and applicants with pass/fail Step 1 results (tested after). These two groups are not analytically equivalent. Score distributions for matched/unmatched comparisons apply only to the numeric cohort; pass/fail applicants are reported separately. As the numeric cohort ages out of the applicant pool, the Step 1 sections of future Charting Outcomes editions will become uninformative for most current applicants. Step 2 CK will be the primary score metric for all practical purposes within the next two to three biennial cycles.

The data describe who matched, not why

Charting Outcomes is observational, not causal. It documents that matched applicants have more publications on average, but it does not establish that publications caused the match outcome. Selection effects are large: applicants with more research are also more likely to be at research-intensive medical schools, to have stronger Step scores, stronger letters from prominent faculty, and more geographic flexibility. Treating any single Charting Outcomes variable as a direct lever is an oversimplification.

Key Takeaways and Next Steps

Seven data-driven action items, derived directly from the Charting Outcomes patterns described above:

1. Download the current NRMP Charting Outcomes PDF before building your application list. nrmp.org publishes the full report. This page summarizes the data; the source document contains specialty-specific charts and probability curves that refine the figures here. Every application strategy decision should be grounded in the most current available edition.
2. Locate yourself on the full matched distribution for your target specialty—not just relative to the mean. Identify whether you are above the median, between the median and 10th percentile, or below the 10th percentile on Step 2 CK, research output, and (where applicable) Step 1. Each zone carries different implications for application breadth and rank list construction.
3. Take Step 2 CK seriously as your primary numeric signal if you tested Step 1 pass/fail. Programs in all specialties use it as the main differentiation tool for pass/fail Step 1 applicants. A Step 2 CK at or above the matched mean for your target specialty is the single highest-leverage academic preparation action available to most current applicants.
4. Build your rank list to the length associated with high match probability for your specialty. The NRMP probability curves in Charting Outcomes show the rank list length at which match probability exceeds 90% for typical US MD applicants in each specialty. If your interview volume falls short of that threshold, SOAP preparation becomes a parallel priority—not a contingency to address after Match Day.
5. For competitive specialties, calibrate research expectations against the matched 10th-percentile, not the mean. If your publication count falls below the matched 10th percentile for your target specialty (e.g., below approximately 3–4 publications for dermatology or neurological surgery), that is a concrete application planning constraint, not a vague weakness. It informs whether to apply broadly across specialty tiers, whether a research year strengthens your position, and how to frame your application narrative.
6. Apply Charting Outcomes data at the specialty level, not the aggregate level. The overall US MD senior match rate is not your match rate. Your match probability is determined by your profile relative to the matched distribution in your specific target specialty. Use the specialty-level tables on this page and in the NRMP source document.
7. Revisit your specialty choice assumptions using the head-to-head comparisons. If you are considering two or more specialties, compare your profile against the matched distributions for each. A profile that is solidly competitive in one specialty may be below the 10th percentile in another that you are treating as a co-primary. The data make this concrete and quantitative; use them.

Linked resources: For specialty-specific deep dives, see the PGY Zero specialty data pages. For signaling strategy, see the PGY Zero signaling page. For the annual (non-biennial) position and fill-rate data, see the NRMP Main Residency Match Results and Data page (nrmp.org), published each spring. For current application cycle timelines, see the PGY Zero current season timeline page.

All figures on this page: NRMP Charting Outcomes in the Match: US MD Seniors, 2024 edition, published at nrmp.org. Figures marked "approx." are derived from published charts and tables; minor rounding from the source is possible. Verify against the source PDF before using in advising, presentations, or publications. This page is updated on the NRMP biennial release cycle; check the page header for the current data year stamp.