Power Index Methodology

How Play to Clinch rates and ranks college dual-match teams. The model is a direct sibling of oregontennis.org's Power Index — the same APR + FQI + oGS engine that seeds every simulation. It measures both winning (through APR) and flight-level play against real competition (through FQI and oGS), because in tennis not all wins are created equal.

Overview & Formula

The Power Index is a composite rating combining three weighted components: a team's Adjusted Power Rating (APR), its Flight Quality Index (FQI), and its opponent-weighted Game Share (oGS). Together they capture how often a team wins, how it competes at the flight level against the opponents it faced, and how close those flights actually were in games.

APR measures team-level win/loss performance against a strength-of-schedule backdrop. FQI measures how many individual flights a team wins, weighted both by the competitive significance of the flight (#1 flights count more than #4 flights) and by opponent strength. oGS measures the share of games (not just flights) the team won, scaled by the same opponent multiplier — so a 6–2 flight loss where the games went 49–30 reads as more competitive than a 6–2 flight loss where the games went 50–5.

APR — Adjusted Power Rating

APR is the standard RPI formula: a team's own winning percentage combined with its strength of schedule. Ties count as half a win and half a loss.

Opponent win percentage is the largest component because strength of schedule matters most — beating a 14–1 team means more than beating a 1–14 team. APR alone is only half the story, though: a dual result is just win/loss/tie and hides how a team won and against whom. FQI and oGS fill that gap.

FQI — Flight Quality Index

FQI measures how well a team plays at the flight level, weighted by the competitive significance of each flight and by the strength of each opponent — a single 0–1 number. Each match's flight score is multiplied by a factor based on the opponent's APR, normalized so a median-APR opponent is neutral (1.0), stronger opponents amplify (> 1.0), and weaker ones discount (< 1.0).

Flight	Weight	Rationale
1st Singles	1.00	Full weight — top competitive position
2nd Singles	0.75	High competition, strong players
3rd Singles	0.25	Developing position
4th Singles	0.10	Often newest varsity player
1st Doubles	1.00	Full weight — top competitive position
2nd Doubles	0.50	Solid competitive position
3rd Doubles	0.25	Developing position
4th Doubles	0.10	Often newest varsity pair

Per dual, flight-weighted performance is the sum of flight weights earned ÷ the sum of weights contested. Weighting discourages stacking strong players at low flights and fattening a record against easy opponents; it rewards flight-level competitiveness against strong opponents.

oGS — Opponent-Weighted Game Share

oGS is the opponent-weighted share of games (not flights) a team won. Where FQI tracks who won which flights, oGS tracks how lopsided those flights were in actual games.

Set type matters: best-of-3 sets and 8-game pro sets contribute raw game totals; a set tiebreak (7–6) counts as one deciding game; a 10-point match tiebreak in lieu of a third set is one game to the winner, zero to the loser. (Both alternative formats Play to Clinch supports — see the match-format toggles — feed oGS this way.)

Head-to-Head Tiebreakers

After Power Index scores are computed, head-to-head results break ties in two phases: in-conference (teams within 2 conference-rank positions swap to honor a direct result) and overall (adjacent teams whose Power Index is within 2% swap if the lower-ranked team won the meeting). Split series fall back to the higher FQI. Thresholds keep a single upset from leapfrogging large rating gaps.

Alternative Models (A/B test)

The Model selector above the rankings table re-binds the Rank / Power Index columns to a chosen model.

TOSS — primary

QWS — experimental (quality-weighted)

Replaces RPI-style APR with an ITA-style quality-weighted-wins model, iterated to convergence: each win earns points equal to the opponent's Power Index × 100, each loss costs a flat 50.

Legacy — pre-2026 RPI

FAQ

Why not just use RPI?

RPI works where the final score reflects team quality. In tennis a dual result is win/loss/tie and hides what happened underneath — a 5–3 win stacking the bottom of the lineup looks identical to a dominant 8–0. FQI and oGS look at individual flights and games, weighted by significance and opponent strength.

Where does the data come from?

In Play to Clinch, every number is produced by the simulation: the engine runs the doubles point and six singles for each dual, and the season's results feed APR, FQI and oGS. Real schools, simulated players.