5 FiveLetterWords
Very unlikely Accepted guess F tier for first-turn info

NAZAR

NAZAR is an accepted guess. Its modelled answer likelihood is very unlikely; no globally completed appearance is recorded here.

Meaning and pronunciation

Noun

An eye-shaped amulet supposed to protect against the evil eye in certain cultures.

Source: Wiktionary contributors · CC BY-SA 4.0. Corrections.

Etymology

Borrowed from Ottoman Turkish نظر (now Turkish nazar (boncuğu)), from Arabic نَظَر (naẓar).

Source: Wiktionary (CC BY-SA)

How it sounds

Two syllables, stress on the second syllable Say it NAHZAHR.

Rhymes with CIGAR STARR TATAR DINAR BAZAR

Use NAZAR in a puzzle

As an opener, it rules out about 88.1% of possible answers.

Open Solver with NAZAR Open Word Finder

Wordle status

Answer chance: very unlikely. Roughly 0.05% within a year (about 1 in 2,113), under the model through 2026-11-05. This is an estimate, not a publisher forecast. How this is calculated.

Playable guess

Yes

Included in the Wordle guess list used by our tools.

Earlier benchmark pool

No

Membership in the preserved uniform benchmark; it is not a future eligibility rule.

Past Wordle answer

No completed appearance

No appearance in our globally completed history. A recent puzzle may still be live elsewhere.

The possible-answer list is the solver's current list and may change when Wordle adds new answers.

How NAZAR performs as a guess

Wordle accepts NAZAR as a guess. It is outside this preserved uniform benchmark’s answer pool; that is not a claim about future eligibility.

Played as an opener, it lands at least one colored tile in 73.5% of games, misses completely in 26.5%, and leaves about 284 possible answers on average.

In the previous complete opener benchmark, it ranks #12,685 of 14,855 openers, averaging 3.83 guesses in games solved within six turns.

Try your feedback pattern

Tap the tiles to match your feedback, then see the ranked follow-up guesses.

All gray? Tap a tile to cycle gray → yellow → green.
See strategy patterns

Useful pattern pages

If you only know part of the word, start with one of these matching patterns.

N___R N in the 1st position and R in the 5th position N__A_ N in the 1st position and A in the 4th position _A__R A in the 2nd position and R in the 5th position NA_AR N in the 1st position, A in the 2nd position, A in the 4th position, and R in the 5th position

Explore lists that match the beginning, ending or letters in NAZAR.

First-turn measures

All four describe NAZAR used as an opening guess. Entropy is the same idea as “avg ruled out” on a log scale: a higher number means the guess splits the possible answers into more, smaller groups.

3.89 Entropy (bits)
284 Avg remaining
0.0% Exact match
88.1% Avg ruled out

As an opening guess: previous benchmark

How NAZAR performed in the previous complete opener benchmark, against its captured answer snapshot. These research figures are separate from today's solver recommendations. See the data page for the method.

3.83 Avg guesses
99.83% Solved within six
0.71 Spread of game lengths
#12,685 Rank among openers
Opening with NAZAR left 4 of the snapshot's answers unsolved after six guesses. A spread of 0.71 means those games clustered within about 0.71 of a guess of the 3.83 average. It ranks #12,685 of 14,855 openers by average guesses in games solved within six.
1 guess
0
2 guesses
40
3 guesses
676
4 guesses
1,301
5 guesses
306
6 guesses
27

Composition

4/5 unique
2 vowels
Common:
ANR

Feedback chances

Any hit (G/Y)
74%
Green tile
27%
All gray
26%

When NAZAR is useful later

NAZAR tied for the smallest expected survivor count in 1 of 54 sampled positions where it was legal. This designed sample is not a measure of how often real players should use it.

After STARE: 4 candidates, normal mode

STARE: 02110 (0 = grey, 1 = yellow, 2 = green).

Remaining answers: ATRIA, ATRIP, ATTAR, OTTAR.

With a budget of 5 more guesses, NAZAR is an information probe, outside this survivor list. It leaves 1.00 candidates on average under the model. Every feedback identifies a single candidate; another turn may be needed to submit it.

Try this position in the Solver
Sample and method

Every saved board is reachable within a six-turn game. Remaining turns equal six minus the saved history length. The sampling policy is independent of the expected-survivor metric. Two states at each of three depths per opener were selected by a fixed hash from an independent candidate-only sampling policy. Every accepted guess was evaluated. Model answer-model-2026-11-05-9183a914c959, data through 2026-11-05. The score measures expected survivors, not proved solve length or human difficulty.

How this is calculated.

How the solver finds NAZAR

The strategy receives only earlier guesses and their feedback. It does not know the answer before choosing a move. Guessing the answer itself on turn one is a lucky one-turn result, not a recommended general strategy.

Normal mode

Our solver: bounded weighted policy. Current-pool replay over 14,855 accepted words. Model through 2026-11-05.

  1. The fixed opener tests its five letters.

    14,855 before → 121 after. This feedback leaves 121 candidates.

    All 121 surviving candidates

    BAIRN, BAJRA, BAJRI, BAKRA, BAZAR, CAIRD, CAIRN, CAPRI, CAURI, DAIRY, DAMAR, FAIRY, FAKIR, FAQIR, FAURD, FAVOR, GAZAR, HAIRY, JAGIR, JAGRA, KABAR, KAFIR, KAPUR, KAURI, KAURU, KAURY, LAARF, LAARI, LABOR, LABRA, LAGAR, LAHAR, LAIRD, LAIRY, LAURA, LAVRA, LAZAR, MACRO, MADAR, MAJOR, MAKAR, MALAR, MANOR, MAURI, MAYOR, MAZAR, NADIR, NAGAR, NAGOR, NAIRA, NAIRU, NAVAR, NAZAR, NAZIR, PADRI, PAGRI, PALAR, PANIR, PAPRI, PAYOR, RABBI, RABIC, RABID, RACON, RADAR, RADDI, RADDY, RADGY, RADIF, RADII, RADIO, RADIX, RADON, RAFFY, RAFIK, RAFIQ, RAGGA, RAGGY, RAHUI, RAIAH, RAINY, RAIRD, RAJAH, RAKHI, RAKIA, RAKKI, RALLI, RALLY, RALPH, RAMAL, RAMIN, RAMMY, RAMON, RANCH, RANDO, RANDY, RANGA, RANGI, RANGY, RANID, RANNY, RAPID, RAPIN, RAULI, RAUPO, RAVIN, RAWDY, RAWIN, RAWLY, RAYAH, RAYON, RAZAI, RAZOO, RAZOR, VAIRY, VAJRA, VALOR, VAPOR, WAZIR, YAIRD, ZABRA

    Decision measures before feedback

    Expected remaining candidates: 414.45. Information: 5.74 bits. These measures describe the decision before its realised feedback.

  2. Test RADIO against the 121 candidates consistent with the earlier rows.

    121 before → 25 after. This feedback leaves 25 candidates.

    All 25 surviving candidates

    BAJRA, BAKRA, BAZAR, GAZAR, JAGRA, KABAR, KAPUR, KAURU, KAURY, LAARF, LABRA, LAGAR, LAHAR, LAURA, LAVRA, LAZAR, MAKAR, MALAR, MAZAR, NAGAR, NAVAR, NAZAR, PALAR, VAJRA, ZABRA

    Decision measures before feedback

    Expected remaining candidates: 8.442. Information: 3.372 bits. These measures describe the decision before its realised feedback.

  3. Test LABRA against the 25 candidates consistent with the earlier rows.

    25 before → 6 after. This feedback leaves 6 candidates.

    All 6 surviving candidates

    GAZAR, MAKAR, MAZAR, NAGAR, NAVAR, NAZAR

    Decision measures before feedback

    Expected remaining candidates: 2.84. Information: 3.433 bits. These measures describe the decision before its realised feedback.

  4. Test GAZAR against the 6 candidates consistent with the earlier rows.

    6 before → 2 after. This feedback leaves 2 candidates.

    All 2 surviving candidates

    MAZAR, NAZAR

    Decision measures before feedback

    Expected remaining candidates: 1.667. Information: 1.918 bits. These measures describe the decision before its realised feedback.

  5. Test MAZAR against the 2 candidates consistent with the earlier rows.

    2 before → 1 after. This feedback leaves 1 candidate.

    All 1 surviving candidates

    NAZAR

    Decision measures before feedback

    Expected remaining candidates: 1.0. Information: 1.0 bits. These measures describe the decision before its realised feedback.

  6. Submit the only remaining candidate.

    1 before → 1 after. The answer is submitted and solved.

    All 1 surviving candidates

    NAZAR

    Decision measures before feedback

    Expected remaining candidates: 1.0. Information: 0.0 bits. These measures describe the decision before its realised feedback.

Solved in 6 guesses. Uniquely identified on turn 5.

Continue this board in the Solver

Hard Mode

Our solver: bounded weighted policy. Current-pool replay over 14,855 accepted words. Model through 2026-11-05.

  1. The fixed opener tests its five letters.

    14,855 before → 121 after. This feedback leaves 121 candidates.

    All 121 surviving candidates

    BAIRN, BAJRA, BAJRI, BAKRA, BAZAR, CAIRD, CAIRN, CAPRI, CAURI, DAIRY, DAMAR, FAIRY, FAKIR, FAQIR, FAURD, FAVOR, GAZAR, HAIRY, JAGIR, JAGRA, KABAR, KAFIR, KAPUR, KAURI, KAURU, KAURY, LAARF, LAARI, LABOR, LABRA, LAGAR, LAHAR, LAIRD, LAIRY, LAURA, LAVRA, LAZAR, MACRO, MADAR, MAJOR, MAKAR, MALAR, MANOR, MAURI, MAYOR, MAZAR, NADIR, NAGAR, NAGOR, NAIRA, NAIRU, NAVAR, NAZAR, NAZIR, PADRI, PAGRI, PALAR, PANIR, PAPRI, PAYOR, RABBI, RABIC, RABID, RACON, RADAR, RADDI, RADDY, RADGY, RADIF, RADII, RADIO, RADIX, RADON, RAFFY, RAFIK, RAFIQ, RAGGA, RAGGY, RAHUI, RAIAH, RAINY, RAIRD, RAJAH, RAKHI, RAKIA, RAKKI, RALLI, RALLY, RALPH, RAMAL, RAMIN, RAMMY, RAMON, RANCH, RANDO, RANDY, RANGA, RANGI, RANGY, RANID, RANNY, RAPID, RAPIN, RAULI, RAUPO, RAVIN, RAWDY, RAWIN, RAWLY, RAYAH, RAYON, RAZAI, RAZOO, RAZOR, VAIRY, VAJRA, VALOR, VAPOR, WAZIR, YAIRD, ZABRA

    Decision measures before feedback

    Expected remaining candidates: 414.45. Information: 5.74 bits. These measures describe the decision before its realised feedback.

  2. Test RADIO against the 121 candidates consistent with the earlier rows.

    121 before → 25 after. This feedback leaves 25 candidates.

    All 25 surviving candidates

    BAJRA, BAKRA, BAZAR, GAZAR, JAGRA, KABAR, KAPUR, KAURU, KAURY, LAARF, LABRA, LAGAR, LAHAR, LAURA, LAVRA, LAZAR, MAKAR, MALAR, MAZAR, NAGAR, NAVAR, NAZAR, PALAR, VAJRA, ZABRA

    Decision measures before feedback

    Expected remaining candidates: 8.442. Information: 3.372 bits. These measures describe the decision before its realised feedback.

  3. Test LABRA against the 25 candidates consistent with the earlier rows.

    25 before → 6 after. This feedback leaves 6 candidates.

    All 6 surviving candidates

    GAZAR, MAKAR, MAZAR, NAGAR, NAVAR, NAZAR

    Decision measures before feedback

    Expected remaining candidates: 2.84. Information: 3.433 bits. These measures describe the decision before its realised feedback.

  4. Test GAZAR against the 6 candidates consistent with the earlier rows.

    6 before → 2 after. This feedback leaves 2 candidates.

    All 2 surviving candidates

    MAZAR, NAZAR

    Decision measures before feedback

    Expected remaining candidates: 1.667. Information: 1.918 bits. These measures describe the decision before its realised feedback.

  5. Test MAZAR against the 2 candidates consistent with the earlier rows.

    2 before → 1 after. This feedback leaves 1 candidate.

    All 1 surviving candidates

    NAZAR

    Decision measures before feedback

    Expected remaining candidates: 1.0. Information: 1.0 bits. These measures describe the decision before its realised feedback.

  6. Submit the only remaining candidate.

    1 before → 1 after. The answer is submitted and solved.

    All 1 surviving candidates

    NAZAR

    Decision measures before feedback

    Expected remaining candidates: 1.0. Information: 0.0 bits. These measures describe the decision before its realised feedback.

Solved in 6 guesses. Uniquely identified on turn 5.

Continue this board in the Solver

How the fixed opener panel performs on this answer

OpenerFirst feedbackSurvivorsNormalHard Mode
TARSE02100 (0 grey, 1 yellow, 2 green)12166
CRANE01110 (0 grey, 1 yellow, 2 green)8766
SLATE00100 (0 grey, 1 yellow, 2 green)110155
ADIEU10000 (0 grey, 1 yellow, 2 green)20196Not solved in six
STARE00110 (0 grey, 1 yellow, 2 green)3865Not solved in six
AUDIO10000 (0 grey, 1 yellow, 2 green)25136Not solved in six
RAISE12000 (0 grey, 1 yellow, 2 green)1625Not solved in six
ROATE10100 (0 grey, 1 yellow, 2 green)44765
SALET02000 (0 grey, 1 yellow, 2 green)57166
Normal mode
1 guess: 0 · 2 guesses: 0 · 3 guesses: 0 · 4 guesses: 0 · 5 guesses: 3 · 6 guesses: 6 · Failed in six: 0
Hard Mode
1 guess: 0 · 2 guesses: 0 · 3 guesses: 0 · 4 guesses: 0 · 5 guesses: 2 · 6 guesses: 3 · Failed in six: 4

The nine openers use the same pool and continuation policy. Across both modes: 5–6 guesses among successes; 4 of 18 configurations failed. This is performance on this answer, not an overall opener ranking.

18 openers set up a two-turn opportunity; examples include NIGER, NAGAR, NAZIR, NIZAM, ZAMAN, HAZAN, NAMAZ, MIZEN, ZONER, NGRAM. After their feedback, this answer is among the most likely survivors with at least half the model probability. This is an opportunity, not a guarantee. An opener that immediately solves is excluded.

Why this answer can be difficult

The answer contains 2 copies of A. Feedback allocates exact matches before misplaced copies; a grey duplicate does not erase another coloured copy.

The worked board still allows 6 different answers at one later decision: GAZAR, MAKAR, MAZAR, NAGAR, NAVAR, NAZAR. These are mechanical alternatives, not a judgement of vocabulary difficulty.

Vocabulary evidence and voluntary player results are reported separately from these solver observations.

Closest competing answers in this board

These words all fit the earlier feedback, rather than merely sharing similar spelling: GAZAR, MAKAR, MAZAR, NAGAR, NAVAR, NAZAR.

A lesson from this route

Before GAZAR, 6 words still fit. Its feedback left 2; check the full survivor list before choosing the next answer.

Try another opener or a different move

How this is calculated

The current policy checks all remaining candidates and up to 128 fixed probes. At six or fewer candidates it uses bounded lookahead, preferring modelled six-turn success, then speed among successes. Larger states use expected survivors as a heuristic. These are recommendations, not proofs of optimal play. Hard Mode retains green positions and revealed letter counts; it allows grey letters and a yellow in the same position. Candidate-only play is stricter.

Methods and limitations

Feedback distribution

NAZAR can come back 61 different ways. These are the most likely, and how many of the possible answers give each one:

635 answers
321 answers
249 answers
210 answers
130 answers
119 answers
112 answers
70 answers
65 answers
59 answers
52 answers
40 answers
38 answers
37 answers
24 answers
21 answers
18 answers
17 answers
17 answers
17 answers
14 answers
10 answers
9 answers
9 answers
8 answers
6 answers
6 answers
6 answers
5 answers
5 answers

Letter-value totals

Base letter-value totals for NAZAR; these do not show whether either game accepts the word.

Scrabble

N1A1Z10A1R1
Total: 14 points

Words With Friends

Total: 15 points

Scores shown are base values without double/triple letter or word bonuses.

Try next

TOILE TOISE SLATE BLITE SOILY TRACE

Strategy after playing NAZAR

What the solver recommends next for each way the board can respond to NAZAR.

Quick reference

Largest feedback groups after playing NAZAR:

27% chance
Suggested:
TOILE
13% chance
Suggested:
TOISE
10% chance
Suggested:
TOILE

Follow-ups for common patterns

Ranked follow-up guesses for the 10 most common feedback patterns.

26.5% →
TOILE 6.09 bits
13.4% →
TOISE 5.57 bits
10.4% →
TOILE 5.39 bits
8.8% →
SLATE 5.63 bits
5.4% →
BLITE 4.69 bits
5.0% →
SOILY 3.78 bits
4.7% →
TRACE 4.69 bits
2.9% →
STILE 4.55 bits
2.7% →
GROIN 4.45 bits
2.5% →
CLEAT 4.53 bits

Research on NAZAR

Game-tree analysis and word research for NAZAR, with an explanation for each figure.

Optimal play

Opening with NAZAR, a proven-optimal strategy averages 3.88 guesses and ranks #13,436 of 14,855 legal openers. The best proven opener, TARSE, averages 3.55.

No guaranteed hard-mode solve In hard mode, no strategy that opens with NAZAR can guarantee a solve within six guesses.

Our six-turn simulation says 3.83, at or below the proven-optimal 3.88, because the two figures score different answer lists.

These figures come from exhaustive game-tree search and are exact for the NYT lists of July 2023 (3,158 answers). They do not use the site's working answer pool.

Familiarity and learning

Frequency
NAZAR sits in the advanced band of the wordfreq scale, appearing less than once per million words in the source corpus. Corpus frequency does not measure every reader’s familiarity.

Sources: Optimal-play values: Alex Selby's exhaustive Wordle analysis (MIT); Pronunciation: CMU Pronouncing Dictionary (BSD); Word frequency: wordfreq (data CC BY-SA 4.0).