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Grupo Sports World, S.A. (SPORTS) Fair Value & Analysis

Communication Services · MX · Market cap 2.1B MXN

Price8.80 MXN
Fair Value18.99 MXN
Upside+115.8%
Quality95/100
Evidence: High Range 10.15 MXN – 21.62 MXN

Fair value as of: Jun 25, 2026

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Analysis

Grupo Sports World, S.A. (SPORTS) currently trades at 8.80 MXN, while our model-based Fair Value estimate is 18.99 MXN — implying the stock looks roughly 115.8% undervalued today. We read business quality at 95/100 (high quality), in the Communication Services sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.

About the company

Grupo Sports World, S.A.B. de C.V. operates sports clubs primarily in Mexico. It offers a range of sports activities and programs, as well as training, health, and nutrition services. The company was founded in 1989 and is based in Mexico City, Mexico.

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Frequently asked questions

Is Grupo Sports World, S.A. (SPORTS) undervalued?
As of Jun 25, 2026, our model estimates a fair value of 18.99 MXN versus a price of 8.80 MXN — about +116% (undervalued). Model-based estimate, not financial advice.
What is the fair value of SPORTS?
Our 21-model fair value for Grupo Sports World, S.A. is 18.99 MXN (as of Jun 25, 2026), built from audited fundamentals. The current price is 8.80 MXN.
What is the quality score of SPORTS?
Grupo Sports World, S.A. has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

How we calculate Fair Value

Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.

Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.