Power Index Methodology

The Power Index is a composite rating that combines 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 a team competes at the flight level against the opponents they 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 the strength of the opponent. oGS measures the share of games (not just flights) the team won across the season, scaled by the same opponent-strength multiplier — so a 6–2 flight loss where the games went 49–30 is read as more competitive than a 6–2 flight loss where the games went 50–5.

APR uses the same RPI formula that the OSAA uses for sports like volleyball and basketball. It combines a team's own winning percentage with its strength of schedule.

The three components are:

Win Percentage (25%): The team's own dual-match winning percentage. Ties count as half a win and half a loss.

Opponent Win Percentage (50%): The average winning percentage of every team on the schedule. This is the largest component because strength of schedule matters most — beating a 14-1 team means more than beating a 1-14 team.

Opponent's Opponent Win Percentage (25%): The average winning percentage of every opponent's opponents. This smooths out schedule quirks and validates the strength-of-schedule number.

These rankings are independent and not produced by the OSAA. APR (Adjusted Power Rating) is just a different name for the same underlying formula. We want to be clear that while the math is identical, the output and application are our own.

APR tells you how often a team wins dual matches, but a dual match result in tennis is just "Win/Loss/Tie." It doesn't tell you how a team won or against whom. A team that wins 5-3 with depth across all flights looks identical in APR to a team that wins 5-3 because it stacks its top flights and forfeits the rest. A team that loses 3-5 to the #1 team in the state looks identical to a team that loses 3-5 to the weakest team in the state. The Flight Quality Index fills both gaps.

The Flight Quality Index measures how well a team plays at the flight level, weighted both by the competitive significance of each flight and by the strength of each opponent. It's a single 0–1 number that answers the question: "across every dual match this team played, how well did they perform at flight-level given who they were playing?"

Internally, FQI is built in two layers on top of a base Flight-Weighted Score (FWS). The first layer weights flights by position (1st flights count more than 4th flights). The second layer weights each match by the opponent's strength. The team's FQI is the opponent-weighted mean of per-match flight scores. The name oFWS (opponent-weighted Flight-Weighted Score) refers to this metric in general; FQI is the Oregon-specific label.

In a dual match, teams play up to 8 flights: 4 singles and 4 doubles. But not all flights carry the same competitive weight. The #1 singles and #1 doubles positions are where teams put their best players and are contested most seriously. Lower flights (3rd and 4th positions) are often less competitive, sometimes featuring newer or developing players.

Without flight weighting, a team could game the system by loading its 3rd and 4th flights with strong players to rack up easy wins at positions where opponents field their weakest. Weighting the flights reflects the reality of how competitive tennis lineups actually work.

Per dual match, a team's flight-weighted performance is the sum of flight weights earned divided by the sum of flight weights contested, producing a 0–1 per-match score.

An 8–0 sweep of the weakest team in the state and an 8–0 sweep of the #1 team in the state are not equivalent achievements, but an opponent-blind metric counts them as the same. Similarly, a competitive 3–5 flight loss against a state power is a different result than a 3–5 flight loss against a bottom-quartile team. Weighting per-match flight performance by opponent strength corrects both distortions.

Each match's flight score is multiplied by a factor based on the opponent's APR, normalized so that a median-APR opponent is neutral (multiplier 1.0), above-median opponents amplify the match's contribution (multiplier > 1.0), and below-median opponents discount it (multiplier < 1.0). Unknown opponents (cross-state teams, non-ranked opponents) default to neutral. This preserves credit for beating teams at your competitive level while correcting the schedule-quality blindness that a raw flight-win percentage would have.

Discourages: Stacking weaker players at top flights is still penalized by flight weights (a 4th-singles win is worth 0.10 even if you put a star there). Fattening record against easy opponents is now also discounted, because below-median opponents multiply each flight-win contribution downward.

Rewards: Flight-level competitiveness against strong opponents. A team that goes 4–4 in flights against the #1 team in the state scores better on FQI than a team that goes 6–2 against a bottom-quartile team. Winning flights you're "supposed to" against peer-level opposition is still credited at roughly its baseline value. The metric does not require teams to play up — it just ensures that scheduling up is at least neutral rather than punishing.

FQI+ is a classification-adjusted version where 100 equals the classification average. A team with FQI+ of 115 has flight quality 15% above the average for its classification; an FQI+ of 85 is 15% below. FQI+ appears as a hover tooltip on the rankings table and on team detail views. It contextualizes FQI across classifications where the overall level of competition varies.

oGS is the opponent-weighted share of games (not flights) a team won across the season. It's the third component of the Power Index, alongside APR and FQI. Where FQI tracks who won which flights, oGS tracks how lopsided those flights actually were in actual games played.

The opponent multiplier is the same one FQI uses, so a competitive game-share against a strong opponent counts for more than the same game-share against a weaker opponent. The metric naturally exposes two failure modes that FQI alone can miss: undefeated teams in thin leagues whose flight wins were actually tight in games (low oGS), and teams with losing records on tough schedules whose losses were close in games (higher oGS than their record suggests).

The set type matters. Best-of-3 sets and 8-game pro sets contribute their raw game totals (e.g., a 6–4, 6–2 set count contributes 12 games for the winner and 6 for the loser). When a regular set goes to a tiebreaker (7–6), the tiebreaker counts as a single deciding game, not its raw point total. Match tiebreakers (the 10-point super-tiebreaker that replaces a third set) are treated as one game to the winner and zero to the loser — a 10–7 super-TB is a single decision, not 17 games.

Flights without set-level data fall back to a binary outcome (one game to the winner) so coverage stays high without distorting the metric.

FQI's job is anti-stacking: rewarding teams that win across the lineup and discouraging teams from concentrating talent in a few flights. That mission is unchanged. oGS is additive — it answers a different question (how dominant were those flight wins?) and is intentionally weighted lower (20% vs. FQI's 40%) so it informs the ranking without overriding the structural signals from APR and FQI.

After Power Index scores are calculated, head-to-head results are used as a tiebreaker in two phases:

Phase 1 — In-League: Teams in the same league/conference that are close in their league standings (within 2 league rank positions) are compared. If Team A beat Team B head-to-head, Team A is moved above Team B in the overall ranking. This ensures that league rivals who played each other are ranked in an order consistent with their on-court results.

Phase 2 — Statewide: Adjacent teams in the overall ranking whose Power Index scores are within 2% of each other are compared. If the lower-ranked team beat the higher-ranked team, they swap positions. For split series (1-1), the team with the higher FQI is used as a secondary tiebreaker.

Without a threshold, a single upset result could override large differences in overall performance. The league rank threshold (within 2 positions) prevents a last-place team with a single fluke win from leapfrogging through the standings. The 2% PI threshold for statewide comparisons ensures H2H only breaks ties between teams that are genuinely close in overall rating.

Starting April 26, 2026, the primary Power Index on this site is TOSS. The earlier RPI-based formula — the one used from season start through the April 4/11/18 weekly snapshots — is retained as Legacy for reference. A third model, QWS, continues as an experimental comparison variant while we evaluate it for a possible 2027 adoption.

The reason for the switch: the original formula over-rewarded dominant flight scores against weak-league opponents, because its FWS component had no opponent-strength awareness. 8-0 against a cellar team counted the same as 8-0 against the top of the state, which let teams in thin leagues climb above teams who were demonstrably stronger on stronger schedules. Both TOSS and QWS address this; we ran them in parallel on live data for one week and chose TOSS as the primary for the rest of 2026. Full writeup: AAR →

APR is unchanged (the OSAA-style RPI above). FQI is the opponent-APR-weighted Flight Quality Index. oGS is the opponent-APR-weighted Game Share. Each opponent multiplier is the opponent's APR relative to the median APR, applied uncapped to both FQI and oGS contributions per match.

This is the formula driving the main rankings table, class ranks, head-to-head tiebreakers, league standings, and the playoff simulator for 2026+. JSON fields: power_index, rank, class_rank, plus the same-values power_index_toss, fqi, ogs, schedule_multiplier, rank_toss.

Why three components instead of two? One week of live data on the 50/50 APR + FQI version surfaced a residual bias: undefeated teams in shallow conferences could carry a maxed-out raw flight score even after the opponent multiplier discounted it, because 1.0 × 0.7 = 0.7 still sits above field median. Folding in oGS — which natively distinguishes a 6–2 flight win that came in straight 6–0 sets from a 6–2 flight win that went the distance — pulls those teams into a more honest band without any class-aware logic.

Replaces RPI-based APR with an ITA college-tennis style quality-weighted wins model. Each win earns points equal to the opponent's Power Index × 100; each loss costs a flat 50 points. The formula is iterated (seeded with Win% in iteration 0, then using the previous iteration's Power Index) until the change in values drops below 0.01 or five iterations have run. FWS is unchanged.

Available via the Model selector above the rankings table. Not used for any downstream computation (H2H, playoff sim, etc.) during 2026. JSON fields: power_index_qws, apr_qws, qws_iterations, rank_qws, class_rank_qws.

The formula that drove weekly snapshots through April 18, 2026:

Retained for transparency so you can see how rankings shift under the new primary. JSON fields: power_index_legacy, rank_legacy, class_rank_legacy. The three weekly snapshots published on Saturdays April 4/11/18 use this formula and are preserved unchanged on disk.

Use the Model selector above the main rankings table (TOSS · QWS · Legacy). The table's State Rank, Class Rank, and Power Index columns re-bind to the selected model; other views (playoff simulator, H2H tooltips, league standings) continue to use the primary TOSS model regardless.

For programmatic comparison, every 2026+ team in processed_rankings.json now carries all three PI values and all three ranks. Historical seasons (2021–2025) are unchanged.

No. These are independent rankings published by OregonTennis.org. They are not produced by, endorsed by, or affiliated with the OSAA. The APR component uses the same RPI formula the OSAA uses for other sports, but the Power Index as a whole and its application to tennis are entirely our own work.

Oregon has never had a statewide list of team rankings and standings for high school tennis by conference or district. Every other major team sport has power rankings or RPI used for playoff seeding. Tennis has been the outlier. These rankings are modeled to show what a team rating system could look like if tennis adopted a team playoff, and to give coaches, players, and fans a way to see where their team stands statewide.

RPI alone works well for sports where the final score reflects team quality — basketball, volleyball, soccer. In tennis, the dual match result is a simple win/loss/tie that hides what happened underneath. A team can win a dual match 5-3 while losing badly at the competitive top of the lineup and sweeping the bottom. RPI treats that the same as a dominant 8-0 win. The Flight Quality Index addresses this by looking at the individual flight results, weighting them by competitive significance, and then scaling each match by opponent strength so schedule quality is properly represented.

All match data comes from publicly available OSAA results. Dual match outcomes, individual flight scores, and state tournament results are all sourced from OSAA records for each season.

Dual match ties (e.g., 4-4) count as half a win and half a loss for both teams in the APR calculation. This is consistent with standard RPI handling across all sports.

The rankings currently cover 2021 through 2025. Each season is calculated independently using that year's match data.