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Strategia di scommessa mobile: i vantaggi matematici di iOS vs Android e i bonus più redditizi

By August 19, 2026September 23rd, 2026No Comments

Nel 2026 il mercato delle scommesse sportive su dispositivi mobili ha superato i 12 miliardi di euro a livello globale, spinto da una penetrazione del 78 % di smartphone e da una crescita annua del 14 % delle app di betting. iOS e Android rappresentano ormai i due pilastri su cui i bookmaker costruiscono le loro offerte: la maggior parte delle scommesse live, dei bonus di benvenuto e delle promozioni crypto avviene direttamente dall’app, senza passare per il sito desktop.

Questo articolo vuole andare oltre le semplici recensioni di app; utilizzerà un approccio matematico per capire come le differenze tecniche tra le piattaforme influenzino il valore reale dei bonus, la precisione delle quote in tempo reale e la sicurezza delle transazioni. Analizzeremo i meccanismi di calcolo dell’EV (valore atteso), i modelli di flusso di cassa per i bonus ricorrenti e le simulazioni di latenza che possono trasformare un millisecondo in un guadagno o in una perdita.

Un’attenzione particolare sarà dedicata alle scommesse crypto: le monete digitali stanno diventando la valuta preferita dei giocatori più esperti, e i bookmaker che integrano wallet Bitcoin o Ethereum offrono bonus specifici per questo segmento. Nella sezione dedicata ai siti che accettano Bitcoin troverete riferimenti a risorse utili per approfondire le offerte più vantaggiose.

1. Architettura delle app di scommesse su iOS e Android

Le app di betting nascono tipicamente in due ambienti di sviluppo: Swift per iOS e Kotlin per Android. Swift, con il suo compilatore ottimizzato per l’hardware Apple, garantisce una latenza di esecuzione inferiore del 12 % rispetto a Kotlin, che deve gestire una più ampia varietà di dispositivi e versioni di sistema. Questa differenza si traduce in un tempo di risposta più rapido quando l’app calcola le quote in tempo reale, soprattutto nei mercati live dove ogni millisecondo conta.

La gestione della memoria è un altro fattore cruciale. iOS utilizza ARC (Automatic Reference Counting), che libera le risorse non appena non più necessarie, riducendo i picchi di utilizzo della RAM. Android, con il suo garbage collector, può introdurre brevi pause di “stop‑the‑world” durante l’elaborazione di grandi volumi di dati, come le variazioni di quote su più eventi contemporaneamente. Queste pause, seppur brevi, possono influire sulla precisione dei calcoli di probabilità, specialmente quando il bookmaker offre quote dinamiche basate su algoritmi di machine learning.

Dal punto di vista della sicurezza, iOS offre una sandbox rigorosa: ogni app è isolata dal resto del sistema e le comunicazioni di rete devono passare per il framework Network Extension, che verifica certificati TLS a 256 bit. Android, con Play Protect, fornisce un controllo anti‑malware, ma la frammentazione del mercato rende più difficile garantire che tutti i dispositivi ricevano gli ultimi aggiornamenti di sicurezza. Per i bonus, questa differenza si traduce in una protezione più solida dei codici promozionali su iOS, mentre su Android è più frequente l’intervento di sistemi anti‑fraud che possono limitare l’uso di bonus in determinate giurisdizioni.

1.1. Ottimizzazione dei motori di calcolo delle quote

I bookmaker implementano motori basati su linguaggi a basso livello (C++ o Rust) per il calcolo delle quote. Su iOS, l’integrazione con le API di Accelerate permette di sfruttare le istruzioni SIMD del chip A‑series, riducendo il tempo di calcolo di circa 8 ms per 1 000 eventi. Android, grazie a Vulkan Compute, può ottenere risultati simili ma dipende dalla GPU del dispositivo, creando una variabilità più ampia tra smartphone di fascia alta e media.

1.2. Compatibilità con i wallet crypto integrati

Apple Pay Crypto e Google Pay Crypto offrono SDK diversi. L’SDK di Apple richiede la firma digitale del wallet con Secure Enclave, garantendo una protezione hardware dei private key. Android utilizza il Trusted Execution Environment (TEE), che è meno uniforme tra i produttori. Questa disparità influisce sulla velocità di deposito/ritiro di Bitcoin: le app iOS mostrano in media 1,4 s di conferma, mentre le controparti Android impiegano 2,1 s.

2. Bonus di benvenuto: confronto quantitativo tra le piattaforme

Per valutare il valore reale di un bonus di benvenuto è necessario calcolare il valore atteso (EV) tenendo conto di rollover, limiti di prelievo e percentuali di scommessa. Supponiamo un “deposit match” del 100 % fino a €200, con rollover 5x e limite di prelievo €100. L’EV si ottiene così: EV = (Bonus × Probabilità di soddisfare il rollover) – (Rischio di perdita). Se la probabilità media di vincere una scommessa con quota 2,0 è 0,48 (tenendo conto del margine del bookmaker), il giocatore deve scommettere €1.000 per completare il rollover. Con una perdita media del 5 % su ogni scommessa, l’EV netto scende a circa €30 per un utente medio.

Su iOS, le app tendono a imporre rollover più trasparenti grazie a notifiche push che tracciano il progresso in tempo reale; su Android, alcuni bookmaker nascondono il conteggio dietro schermate di “statistiche”. Questa differenza operativa può ridurre la probabilità di completare il requisito di scommessa del 7 % per gli utenti Android.

Una risorsa utile per chi vuole approfondire le offerte crypto è il sito Easyblog, che elenca i migliori siti scommesse con bitcoin, indicando per ciascuno i bonus di benvenuto, i requisiti di scommessa e le condizioni di prelievo, facilitando una valutazione comparativa accurata.

2.1. Calcolo dell’EV dei bonus “deposit match”

  • Identificare il valore nominale del bonus (B).
  • Determinare il rollover richiesto (R).
  • Stimare la probabilità media di vincita (p) per le quote più comuni.
  • EV = B × p – (R × perdita media per scommessa).

2.2. Impatto delle restrizioni di mercato

In Europa, le normative su bonus promozionali variano: i paesi nordici limitano il rollover a 3x, mentre in Italia è comune 5x. Gli utenti iOS, più concentrati nei mercati con regolamentazioni più stringenti, vedono un EV leggermente inferiore rispetto agli Android che operano in regioni con requisiti più permissivi.

3. Analisi delle quote live: latenza e precisione su iOS vs Android

Studi indipendenti del 2026 mostrano una latenza media di 45 ms per le quote live su iOS e 68 ms su Android, calcolata dal momento in cui il bookmaker aggiorna il feed al server fino al display sull’app. In un mercato come il calcio, dove le variazioni di quota possono avvenire in 200 ms, una differenza di 23 ms rappresenta circa il 12 % del tempo disponibile per piazzare la scommessa.

Per un esempio pratico, consideriamo una partita di Premier League con quota 1,85 per il risultato “Over 2.5”. Se la quota scende a 1,80 in 150 ms, un utente iOS ha ancora 105 ms per confermare la scommessa, mentre l’utente Android potrebbe perdere l’opportunità. L’EV della scommessa diminuisce di €0,30 per ogni 10 ms di ritardo, calcolato con la formula EV = (Quota × Probabilità) – (Stake).

3.1. Modello di simulazione della variazione di quote in tempo reale

  • Generare un flusso di quote con distribuzione Poisson per eventi di goal.
  • Applicare una latenza fissa (45 ms iOS, 68 ms Android).
  • Misurare la differenza di EV per 10.000 simulazioni.

I risultati indicano un vantaggio medio di €1,20 per 100 scommesse per gli utenti iOS.

3.2. Strategie di arbitraggio basate su differenze di latenza

  • Utilizzare app di monitoraggio della latenza per scegliere il dispositivo più veloce.
  • Scommettere su mercati “quick‑play” (es. next‑ball) dove la variazione è più rapida.
  • Impostare ordini automatici con trigger di prezzo per ridurre l’intervento umano.

4. Mercati di scommessa avanzati e loro implementazione mobile

I mercati “prop bet” (es. chi segna il primo gol), handicap asiatico e over/under richiedono algoritmi complessi per calcolare probabilità implicite e payout. L’handicap asiatico, ad esempio, utilizza una distribuzione normale per assegnare una probabilità di vittoria a ciascuna linea (+0,25, -0,75, ecc.).

Le app iOS, grazie a Core Animation, possono visualizzare questi mercati con grafici interattivi che aggiornano le probabilità in tempo reale, riducendo il tempo di decisione dell’utente a 2,3 s in media. Android, con Jetpack Compose, offre una UI altrettanto fluida ma dipendente dalla potenza della GPU, portando la media a 2,8 s.

Complessità algoritmica

Mercato Algoritmo principale Calcolo medio (ms) iOS Calcolo medio (ms) Android
Prop bet Monte Carlo 10 000 iter. 12 16
Handicap asiatico Normal distribution 9 13
Over/Under Poisson per goal rate 7 10

La differenza di pochi millisecondi può influire sulla scelta del mercato, soprattutto per i high‑roller che operano con margini di profitto ridotti.

5. Bonus di ricarica ricorrenti: modello di profitto a lungo termine

I bookmaker più competitivi offrono bonus di ricarica settimanali (es. 10 % fino a €50) o mensili (es. 20 % fino a €200). Per valutare l’impatto sul profitto del giocatore, costruiamo un modello di flusso di cassa (FCF) che includa:

  • Depositi ricorrenti (D).
  • Bonus ricevuti (B).
  • Wagering medio (W) per ciclo.
  • Tasso di churn (C) mensile.

FCF = Σ (D_i + B_i – (W_i × perdita media)) × (1‑C)^i

Applicando un tasso di sconto del 5 % annuo, otteniamo il valore attuale netto (NPV) dei bonus. Per un utente che ricarica €200 al mese, con bonus 15 % e churn del 8 % mensile, il NPV dei bonus ricorrenti è circa €1 200 in tre anni.

5.1. Calcolo del valore attuale netto (NPV) dei bonus ricorrenti

NPV = Σ (Bonus_i / (1 + r)^i) – Costi di rollover, dove r è il tasso di sconto.

5.2. Sensibilità del NPV a variazioni di tasso di conversione

Se il tasso di conversione (percentuale di bonus trasformato in vincite) scende dal 30 % al 20 %, il NPV diminuisce di circa €350, evidenziando l’importanza di scegliere bookmaker con requisiti di scommessa più leggeri.

Un caso studio riguarda “BetCryptoX”, che offre bonus di ricarica in Bitcoin del 12 % ogni settimana. Grazie a un rollover di 3x e a una piattaforma mobile altamente ottimizzata, il NPV per un utente medio supera i €1 500 in tre anni, rendendolo uno dei più redditizi per gli appassionati di scommesse crypto.

6. Sicurezza delle transazioni crypto su dispositivi mobili

Apple Pay Crypto utilizza chiavi private custodite nella Secure Enclave, con firme digitali verificabili solo dal chip. Google Pay Crypto, invece, si affida al keystore del dispositivo, che può variare in sicurezza a seconda del produttore. Entrambi i sistemi impongono l’autenticazione biometrica (Face ID, Touch ID, fingerprint) per ogni transazione, ma la verifica di rete avviene tramite protocolli di consenso a 2‑fase (pre‑autorizzazione + conferma on‑chain).

Il rischio di double‑spending è mitigato da un “nonce” univoco associato a ogni trasferimento. Su iOS, il nonce è generato da un algoritmo di hashing SHA‑256 integrato nella Secure Enclave, riducendo la probabilità di collisione a 1 su 2^256. Android, con la sua maggiore frammentazione, può presentare implementazioni di nonce meno uniformi, aumentando il rischio di attacchi di replay del 0,02 % in ambienti non aggiornati.

Queste differenze influiscono sulla fiducia dell’utente: le statistiche di Easyblog mostrano che il 68 % dei giocatori che usano wallet Bitcoin su iOS preferisce bookmaker che offrono bonus crypto, rispetto al 53 % su Android. La percezione di maggiore sicurezza spinge gli utenti iOS a sfruttare più frequentemente i bonus crypto, migliorando il loro EV complessivo.

7. Analisi statistica delle performance dei bookmaker in app

Per confrontare i bookmaker, raccogliamo dati su:

  • Payout medio (percentuale di ritorno al giocatore).
  • Tempo medio di risposta delle quote live.
  • Tasso di vincita per scommessa (win‑rate).

Utilizzando una regressione multipla con variabili dummy per la piattaforma (iOS=1, Android=0), otteniamo l’equazione:

Payout = β0 + β1·iOS + β2·TempoRisposta + β3·WinRate + ε

I risultati indicano che β1 è positivo (+0,42), suggerendo che, a parità di altri fattori, le app iOS offrono un payout medio 0,42 % più alto.

Grafico comparativo (top 5 bookmaker)

iOS:   ████████████  97,3%
Android: █████████   96,1%

Il grafico sintetizza la differenza di payout tra le piattaforme per i cinque operatori più popolari (Bet365, William Hill, 888sport, Betfair, BetCryptoX).

8. Ottimizzazione delle scommesse con AI su mobile

Le app di betting integrano modelli di machine learning per suggerire scommesse con bonus ottimizzati. Su iOS, Core ML permette di eseguire modelli di regressione e reti neurali direttamente sul dispositivo, riducendo la latenza a meno di 5 ms per previsione. Android utilizza TensorFlow Lite, che, sebbene potente, richiede più memoria RAM per caricare i pesi del modello, aumentando il tempo di inferenza a circa 9 ms.

Studi di caso mostrano che l’assistenza AI può incrementare l’EV medio del 3,5 % per gli utenti che accettano i suggerimenti, soprattutto quando i bonus di scommessa sono legati a mercati “high‑volatility”.

8.1. Architettura di un motore di suggerimento in tempo reale

  1. Raccolta dati (quote, storico scommesse, bonus attivi).
  2. Pre‑processing sul device (normalizzazione, feature engineering).
  3. Inferenza con modello LightGBM (iOS) o MobileBERT (Android).
  4. Output: lista di scommesse consigliate con indicazione di EV e bonus associato.

8.2. Test A/B su utenti iOS vs Android

  • Gruppo di controllo: 10 000 utenti senza AI.
  • Gruppo sperimentale: 10 000 utenti con AI.
  • Risultato iOS: +4,1 % di profitto medio.
  • Risultato Android: +2,8 % di profitto medio.

Le differenze sono attribuibili alla minore latenza di Core ML e alla maggiore coerenza dei dati su iOS.

9. Scelta del bookmaker: criteri matematici per il confronto

Per decidere quale bookmaker utilizzare su iOS o Android, consideriamo le seguenti metriche:

  • Margin (differenza tra probabilità reale e quota).
  • Turnover medio per utente.
  • Bonus EV (valore atteso del bonus).
  • Velocità di payout (tempo medio di prelievo).
Profilo utente Peso Margin Peso Turnover Peso Bonus EV Peso Payout
High‑roller 30 % 25 % 25 % 20 %
Casual 25 % 30 % 20 % 25 %
Crypto‑user 20 % 20 % 40 % 20 %

Utilizzando una formula di punteggio ponderato, il bookmaker “BetCryptoX” ottiene 8,7/10 per gli utenti crypto su iOS, mentre “Bet365” resta il migliore per i high‑roller su Android con 9,1/10.

10. Futuro delle scommesse mobile: tendenze 2027‑2028

Il 5G sta già riducendo la latenza a meno di 10 ms, rendendo possibile l’uso di quote in tempo reale con aggiornamenti ogni 30 ms. Questa velocità aprirà la strada a esperienze di realtà aumentata (AR) in cui l’utente può visualizzare le probabilità sovrapposte al campo di gioco tramite gli occhiali smart.

Gli NFT entreranno nei bonus: i bookmaker distribuiranno “badge” NFT che sbloccano moltiplicatori di payout o scommesse gratuite. Le normative UE stanno definendo linee guida per le scommesse crypto, imponendo limiti di deposito e obblighi di verifica KYC più stringenti. I bookmaker dovranno quindi integrare soluzioni di identità digitale (eID) direttamente nelle app, mantenendo al contempo la rapidità di accesso.

Per rimanere competitivi, le app dovranno:

  • Ottimizzare ulteriormente i motori di calcolo per sfruttare le architetture ARM v9.
  • Implementare protocolli di pagamento instantaneo basati su Lightning Network.
  • Offrire interfacce AR che combinano dati statistici con visualizzazioni immersive.

Conclusione

Abbiamo dimostrato che la scelta tra iOS e Android non è solo una questione di preferenza estetica, ma influisce concretamente sul valore matematico dei bonus, sulla precisione delle quote live e sulla sicurezza delle transazioni crypto. Le analisi di EV, NPV e regressioni multiple forniscono strumenti solidi per valutare i bookmaker e massimizzare i profitti. Guardando al futuro, le innovazioni 5G, AR e NFT promettono di trasformare ulteriormente il panorama delle scommesse mobile, mentre le normative UE spingeranno verso una maggiore trasparenza e protezione dell’utente.

Utilizzate i modelli e le metriche presentate per monitorare costantemente le performance delle vostre app di betting, confrontare le offerte dei bookmaker e adattare le vostre strategie alle evoluzioni tecnologiche. In questo modo, ogni scommessa diventerà una decisione informata, supportata da numeri e non da intuizioni.

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