A letter’s address changes its odds

Overall frequency across 18,000 slots

E appears 2,268 times, or 12.6% of every letter position in the dataset. R follows at 1,600 appearances, then A at 1,475. The next group is much tighter: I appears 1,190 times, T 1,181, N 1,133, L 1,057, and O 1,056.

These totals count every occurrence, including repeated copies within one word. They describe the curated pool as a whole, not what remains after a particular board has eliminated letters.

The first position favors consonants

S alone begins more than one in eight candidates. That makes an unplaced yellow S a reasonable first-position test, but only when the board permits it. A gray S is far more valuable than the table: direct evidence always replaces the prior frequency.

The middle positions change leaders

A dominates position two with 540 appearances, followed by E at 488 and O at 396. Position three flips back toward consonants: R leads with 364, followed by N at 253 and T at 228. Position four then swings to I, which appears 435 times—14.5% of that column.

Position five is where E becomes especially strong. It appears there 684 times, more than twice the count of second-place L at 303. N follows closely at 297. These shifts explain why moving a yellow letter one column at a time is inefficient: good placement tests should reflect how word structure changes across the row.

The final-position leaderboard

The top five letters account for 67.9% of all endings in the pool. Even so, one third end with something else. The table is useful for ordering plausible candidates, not deleting every less-common ending.

A disciplined way to use frequency

Begin with the board’s hard constraints: greens stay fixed, yellows move, grays leave unless quantity logic says otherwise, and pink reserves additional copies. Then use position frequency to rank the candidates that survive. This avoids the trap of choosing a statistically common shape that contradicts direct clues.

Because the candidate pool is curated, these numbers also reflect SIXY’s fairness standards. They are more relevant to this game than a frequency table built from books, headlines, or every dictionary entry. Read the word standards for that curation process, or return to the Word Lab overview.